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small follow-up PR that marks it for publication. Merging that second PR releases the previously-draft article so that it can automatically publish. On the day the article is scheduled to publish, automation triggers a website build and your article becomes visible. ## Authoring an article {#authoring} After you've pitched, we'll encourage you to use either HackMD (a web Markdown editor) or a Google doc, to share an editable version of the article text. Your writing buddy can read your draft text and then either directly make suggestions or provide other feedback. They should also let you know if what you're drafting feedback isn't in line with the [blog guidelines](/docs/contribute/blog/guidelines/). At the same time, you'll normally be \*\*their\*\* writing buddy and can follow our [guide](/docs/contribute/blog/writing-buddy/) about supporting their work. ### Initial administrative steps You should [sign the CLA](/docs/contribute/new-content/#contributing-basics) if you have not yet done so. It is best to make sure you start this early on; if you are writing as part of your job, you may need to check with the workplace legal team or with your manager, to make sure that you are allowed to sign. ### Initial drafting The blog team recommends that you either use HackMD (a web Markdown editor) or a Google doc, to prepare and share an initial, live-editable version of the article text. {{< note >}} If you choose to use Google Docs, you can set your document into Markdown mode. {{< /note >}} Your writing buddy can provide comments and / or feedback for your draft text and will (or should) check that it's in line with the guidelines. At the same time, you'll be their writing buddy and can follow the [guide](/docs/contribute/blog/writing-buddy/) that explains how you'll be supporting their work. Don't worry too much at this stage about getting the Markdown formatting exactly right, though. If you have images, you can paste in a bitmap copy for early feedback. The blog team can help you (later in the process), to get illustrations ready for final publication. ### Markdown for publication Have a look at the Markdown format for existing blog posts in the [website repository](https://github.com/kubernetes/website/tree/master/content/en/blog/\_posts) in GitHub. If you're not already familiar, read [contributing basics](/docs/contribute/new-content/#contributing-basics). This section of the page assumes that you don't have a local clone of your fork and that you are working within the GitHub web UI. You do need to make a remote fork of the website repository if you haven't already done so. In the GitHub repository, click the \*\*Create new file\*\* button. Copy your existing content from HackMD or Google Docs, then paste it into the editor. There are more details later in the section about what goes into that file. Name the file to match the proposed title of the blog post, but don’t put the date in the file name. The blog reviewers will work with you to set the final file name and the date when the article will be published. 1. When you save the file, GitHub will walk you through the pull request process. 1. Your writing buddy can review your submission and work with you on feedback and final details. A blog editor approves your pull request to merge, as a draft that is not yet scheduled. #### Front matter The Markdown file you write should use YAML-format Hugo [front matter](https://gohugo.io/content-management/front-matter/). Here's an example: ```yaml --- layout: blog title: "Your Title Here" draft: true # will be changed to date: YYYY-MM-DD before publication slug: lowercase-text-for-link-goes-here-no-spaces # optional author: > Author-1 (Affiliation), Author-2 (Affiliation), Author-3 (Affiliation) --- ``` \* initially, don't specify a date for the article \* however, do
| null |
./vendor/kubernetes/content/en/docs/contribute/blog/submission.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/blog/submission.md
|
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[front matter](https://gohugo.io/content-management/front-matter/). Here's an example: ```yaml --- layout: blog title: "Your Title Here" draft: true # will be changed to date: YYYY-MM-DD before publication slug: lowercase-text-for-link-goes-here-no-spaces # optional author: > Author-1 (Affiliation), Author-2 (Affiliation), Author-3 (Affiliation) --- ``` \* initially, don't specify a date for the article \* however, do set the article as draft (put `draft: true` in the article [front matter](https://gohugo.io/content-management/front-matter/)) #### Article content Make sure to use second-level Markdown headings (`##` not `#`) as the topmost heading level in the article. The `title` you set in the front matter becomes the first-level heading for that page. You should follow the [style guide](https://kubernetes.io/docs/contribute/style/style-guide/), but with the following exceptions: - we are OK to have authors write an article in their own writing style, so long as most readers would follow the point being made - it is OK to use “we“ in a blog article that has multiple authors, or where the article introduction clearly indicates that the author is writing on behalf of a specific group. As you'll notice from this section, although we [avoid using “we”](/docs/contribute/style/style-guide/#avoid-using-we) in our documentation, it's OK to make justifiable exceptions. - we avoid using Kubernetes shortcodes for callouts (such as `{{}}`). This is because callouts are aimed at documentation readers, and blog articles aren't documentation. - statements about the future are OK, albeit we use them with care in official announcements on behalf of Kubernetes - code samples used in blog articles don't need to use the `{{}}` shortcode, and often it is better (easier to maintain) if they do not #### Diagrams and illustrations {#illustrations} For illustrations, diagrams or charts, use the [figure shortcode](https://gohugo.io/content-management/shortcodes/#figure) can be used where feasible. You should set an `alt` attribute for accessibility. For illustrations and technical diagrams, try to use vector graphics. The blog team recommend SVG over raster (bitmap / pixel) diagram formats, and also recommend SVG rather than Mermaid (you can still capture the Mermaid source in a comment). The preference for SVG over Mermaid is because when maintainers upgrade Mermaid or make changes to diagram rendering, they may not have an easy way to contact the original blog article author to check that the changes are OK. The [diagram guide](/docs/contribute/style/diagram-guide/) is aimed at Kubernetes documentation, not blog articles. It is still good to align with it but: - there is no need to caption diagrams as Figure 1, Figure 2, etc. The requirement for scalable (vector) imanges makes the process more difficult for less-familiar folks to submit articles; Kubernetes SIG Docs continues to look for ways to lower this bar. If you have ideas on how to lower the barrier, please volunteer to help out. For other images (such as photos), the blog team strongly encourages use of `alt` attributes. It is OK to use an empty `alt` attribute if accessibility software should not mention the image at all, but this is a rare situation. #### Commit messages At the point you mark your pull request ready for review, each commit message should be a short summary of the work being done. The first commit message should make sense as an overall description of the blog post. Examples of a good commit message: - \_Add blog post on the foo kubernetes feature\_ - \_blog: foobar announcement\_ Examples of bad commit messages: - \_Placeholder commit for announcement about foo\_ - \_Add blog post\_ - \_asdf\_ - \_initial commit\_ - \_draft post\_ #### Squashing Once you think the article is ready to merge, you should [squash](https://www.k8s.dev/docs/guide/pull-requests/#squashing) the commits in your pull request; if you're not sure how to, it's OK to ask the blog
| null |
./vendor/kubernetes/content/en/docs/contribute/blog/submission.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/blog/submission.md
|
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] | 0.093202
|
\_Placeholder commit for announcement about foo\_ - \_Add blog post\_ - \_asdf\_ - \_initial commit\_ - \_draft post\_ #### Squashing Once you think the article is ready to merge, you should [squash](https://www.k8s.dev/docs/guide/pull-requests/#squashing) the commits in your pull request; if you're not sure how to, it's OK to ask the blog team for help.
| null |
./vendor/kubernetes/content/en/docs/contribute/blog/submission.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/blog/submission.md
|
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There are two official Kubernetes blogs, and the CNCF has [its own blog](https://www.cncf.io/blog/) where you can cover Kubernetes too. For the main Kubernetes blog, we (the Kubernetes project) like to publish articles with different perspectives and special focuses, that have a link to Kubernetes. With only a few special case exceptions, we only publish content that hasn't been submitted or published anywhere else. Read the [blog guidelines](/docs/contribute/blog/guidelines/#what-we-publish) for more about that aspect. ## Official Kubernetes blogs ### Main blog The main [Kubernetes blog](/blog/) is used by the project to communicate new features, community reports, and any news that might be relevant to the Kubernetes community. This includes end users and developers. Most of the blog's content is about things happening in the core project, but Kubernetes as a project encourages you to submit about things happening elsewhere in the ecosystem too! Anyone can write a blog post and submit it for publication. With only a few special case exceptions, we only publish content that hasn't been submitted or published anywhere else. ### Contributor blog The [Kubernetes contributor blog](https://k8s.dev/blog/) is aimed at an audience of people who work \*\*on\*\* Kubernetes more than people who work \*\*with\*\* Kubernetes. The Kubernetes project deliberately publishes some articles to both blogs. Anyone can write a blog post and submit it for review. ## Article updates and maintenance {#maintenance} The Kubernetes project does not maintain older articles for its blogs. This means that any published article more than one year old will normally \*\*not\*\* be eligible for issues or pull requests that ask for changes. To avoid establishing precedent, even technically correct pull requests are likely to be rejected. However, there are exceptions like the following: \* (updates to) articles marked as [evergreen](#maintenance-evergreen) \* removing or correcting articles giving advice that is now wrong and dangerous to follow \* fixes to ensure that an existing article still renders correctly For any article that is over a year old and not marked as \_evergreen\_, the website automatically displays a notice that the content may be stale. ### Evergreen articles {#maintenance-evergreen} You can mark an article as evergreen by setting `evergreen: true` in the front matter. We only mark blog articles as maintained (`evergreen: true` in front matter) if the Kubernetes project can commit to maintaining them indefinitely. Some blog articles absolutely merit this; for example, the release comms team always marks official release announcements as evergreen. ## {{% heading "whatsnext" %}} \* Discover the official blogs: \* [Kubernetes blog](/blog/) \* [Kubernetes contributor blog](https://k8s.dev/blog/) \* Read about [reviewing blog pull requests](/docs/contribute/review/reviewing-prs/#blog)
| null |
./vendor/kubernetes/content/en/docs/contribute/blog/_index.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/blog/_index.md
|
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|
Anyone can review a documentation pull request. Visit the [pull requests](https://github.com/kubernetes/website/pulls) section in the Kubernetes website repository to see open pull requests. Reviewing documentation pull requests is a great way to introduce yourself to the Kubernetes community. It helps you learn the code base and build trust with other contributors. Before reviewing, it's a good idea to: - Read the [content guide](/docs/contribute/style/content-guide/) and [style guide](/docs/contribute/style/style-guide/) so you can leave informed comments. - Understand the different [roles and responsibilities](/docs/contribute/participate/roles-and-responsibilities/) in the Kubernetes documentation community. ## Before you begin Before you start a review: - Read the [CNCF Code of Conduct](https://github.com/cncf/foundation/blob/main/code-of-conduct.md) and ensure that you abide by it at all times. - Be polite, considerate, and helpful. - Comment on positive aspects of PRs as well as changes. - Be empathetic and mindful of how your review may be received. - Assume good intent and ask clarifying questions. - Experienced contributors, consider pairing with new contributors whose work requires extensive changes. ## Review process In general, review pull requests for content and style in English. Figure 1 outlines the steps for the review process. The details for each step follow. {{< mermaid >}} flowchart LR subgraph fourth[Start review] direction TB S[ ] -.- M[add comments] --> N[review changes] N --> O[new contributors should choose Comment] end subgraph third[Select PR] direction TB T[ ] -.- J[read description and comments]--> K[preview changes in Netlify preview build] end A[Review open PR list]--> B[Filter open PRs by label] B --> third --> fourth classDef grey fill:#dddddd,stroke:#ffffff,stroke-width:px,color:#000000, font-size:15px; classDef white fill:#ffffff,stroke:#000,stroke-width:px,color:#000,font-weight:bold classDef spacewhite fill:#ffffff,stroke:#fff,stroke-width:0px,color:#000 class A,B,J,K,M,N,O grey class S,T spacewhite class third,fourth white {{}} Figure 1. Review process steps. 1. Go to [https://github.com/kubernetes/website/pulls](https://github.com/kubernetes/website/pulls). You see a list of every open pull request against the Kubernetes website and docs. 2. Filter the open PRs using one or all of the following labels: - `cncf-cla: yes` (Recommended): PRs submitted by contributors who have not signed the CLA cannot be merged. See [Sign the CLA](/docs/contribute/new-content/#sign-the-cla) for more information. - `language/en` (Recommended): Filters for english language PRs only. - `size/`: filters for PRs of a certain size. If you're new, start with smaller PRs. Additionally, ensure the PR isn't marked as a work in progress. PRs using the `work in progress` label are not ready for review yet. 3. Once you've selected a PR to review, understand the change by: - Reading the PR description to understand the changes made, and read any linked issues - Reading any comments by other reviewers - Clicking the \*\*Files changed\*\* tab to see the files and lines changed - Previewing the changes in the Netlify preview build by scrolling to the PR's build check section at the bottom of the \*\*Conversation\*\* tab. Here's a screenshot (this shows GitHub's desktop site; if you're reviewing on a tablet or smartphone device, the GitHub web UI is slightly different): {{< figure src="/images/docs/github\_netlify\_deploy\_preview.png" alt="GitHub pull request details including link to Netlify preview" >}} To open the preview, click on the \*\*Details\*\* link of the \*\*deploy/netlify\*\* line in the list of checks. 4. Go to the \*\*Files changed\*\* tab to start your review. 1. Click on the `+` symbol beside the line you want to comment on. 1. Fill in any comments you have about the line and click either \*\*Add single comment\*\* (if you have only one comment to make) or \*\*Start a review\*\* (if you have multiple comments to make). 1. When finished, click \*\*Review changes\*\* at the top of the page. Here, you can add a summary of your review (and leave some positive comments for the contributor!). Please always use the "Comment" - Avoid clicking
| null |
./vendor/kubernetes/content/en/docs/contribute/review/reviewing-prs.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/review/reviewing-prs.md
|
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|
to make) or \*\*Start a review\*\* (if you have multiple comments to make). 1. When finished, click \*\*Review changes\*\* at the top of the page. Here, you can add a summary of your review (and leave some positive comments for the contributor!). Please always use the "Comment" - Avoid clicking the "Request changes" button when finishing your review. If you want to block a PR from being merged before some further changes are made, you can leave a "/hold" comment. Mention why you are setting a hold, and optionally specify the conditions under which the hold can be removed by you or other reviewers. - Avoid clicking the "Approve" button when finishing your review. Leaving a "/approve" comment is recommended most of the time. ## Reviewing checklist When reviewing, use the following as a starting point. ### Language and grammar - Are there any obvious errors in language or grammar? Is there a better way to phrase something? - Focus on the language and grammar of the parts of the page that the author is changing. Unless the author is clearly aiming to update the entire page, they have no obligation to fix every issue on the page. - When a PR updates an existing page, you should focus on reviewing the parts of the page that are being updated. That changed content should be reviewed for technical and editorial correctness. If you find errors on the page that don't directly relate to what the PR author is attempting to address, then it should be treated as a separate issue (check that there isn't an existing issue about this first). - Watch out for pull requests that \_move\_ content. If an author renames a page or combines two pages, we (Kubernetes SIG Docs) usually avoid asking that author to fix every grammar or spelling nit that we could spot within that moved content. - Are there any complicated or archaic words which could be replaced with a simpler word? - Are there any words, terms or phrases in use which could be replaced with a non-discriminatory alternative? - Does the word choice and its capitalization follow the [style guide](/docs/contribute/style/style-guide/)? - Are there long sentences which could be shorter or less complex? - Are there any long paragraphs which might work better as a list or table? ### Content - Does similar content exist elsewhere on the Kubernetes site? - Does the content excessively link to off-site, individual vendor or non-open source documentation? ### Documentation Some checks to consider: - Did this PR change or remove a page title, slug/alias or anchor link? If so, are there broken links as a result of this PR? Is there another option, like changing the page title without changing the slug? - Does the PR introduce a new page? If so: - Is the page using the right [page content type](/docs/contribute/style/page-content-types/) and associated Hugo shortcodes? - Does the page appear correctly in the section's side navigation (or at all)? - Should the page appear on the [Docs Home](/docs/home/) listing? - Do the changes show up in the Netlify preview? Be particularly vigilant about lists, code blocks, tables, notes and images. ### Blog Early feedback on blog posts is welcome via a Google Doc or HackMD. Please request input early from the [#sig-docs-blog Slack channel](https://kubernetes.slack.com/archives/CJDHVD54J). Before reviewing blog PRs, be familiar with the [blog guidelines](/docs/contribute/blog/guidelines/) and with [submitting blog posts and case studies](/docs/contribute/new-content/blogs-case-studies/). Make sure you also know about [evergreen](/docs/contribute/blog/#maintenance-evergreen) articles and how to decide if an article is evergreen. Blog articles may contain [direct quotes](https://en.wikipedia.org/wiki/Direct\_discourse) and [indirect speech](https://en.wikipedia.org/wiki/Indirect\_speech). Avoid suggesting a rewording for anything
| null |
./vendor/kubernetes/content/en/docs/contribute/review/reviewing-prs.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/review/reviewing-prs.md
|
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|
Before reviewing blog PRs, be familiar with the [blog guidelines](/docs/contribute/blog/guidelines/) and with [submitting blog posts and case studies](/docs/contribute/new-content/blogs-case-studies/). Make sure you also know about [evergreen](/docs/contribute/blog/#maintenance-evergreen) articles and how to decide if an article is evergreen. Blog articles may contain [direct quotes](https://en.wikipedia.org/wiki/Direct\_discourse) and [indirect speech](https://en.wikipedia.org/wiki/Indirect\_speech). Avoid suggesting a rewording for anything that is attributed to someone or part of a dialog that has happened - even if you think the original speaker's grammar was not correct. For those cases, also, try to respect the article author's suggested punctuation unless it is obviously wrong. As a project, we only mark blog articles as maintained (`evergreen: true` in front matter) if the Kubernetes project is happy to commit to maintaining them indefinitely. Some blog articles absolutely merit this, and we always mark our release announcements evergreen. Check with other contributors if you are not sure how to review on this point. The [content guide](/docs/contribute/style/content-guide/) applies unconditionally to blog articles and the PRs that add them. Bear in mind that some restrictions in the guide state that they are only relevant to documentation; those restrictions don't apply to blog articles. Check if the Markdown source is using the right [page content type](/docs/contribute/style/page-content-types/) and / or `layout`. ### Other Watch out for [trivial edits](https://www.kubernetes.dev/docs/guide/pull-requests/#trivial-edits); if you see a change that you think is a trivial edit, please point out that policy (it's still OK to accept the change if it is genuinely an improvement). Encourage authors who are making whitespace fixes to do so in the first commit of their PR, and then add other changes on top of that. This makes both merges and reviews easier. Watch out especially for a trivial change that happens in a single commit along with a large amount of whitespace cleanup (and if you see that, encourage the author to fix it). As a reviewer, if you identify small issues with a PR that aren't essential to the meaning, such as typos or incorrect whitespace, prefix your comments with `nit:`. This lets the author know that this part of your feedback is non-critical. If you are considering a pull request for approval and all the remaining feedback is marked as a nit, you can merge the PR anyway. In that case, it's often useful to open an issue about the remaining nits. Consider whether you're able to meet the requirements for marking that new issue as a [Good First Issue](https://www.kubernetes.dev/docs/guide/help-wanted/#good-first-issue); if you can, these are a good source.
| null |
./vendor/kubernetes/content/en/docs/contribute/review/reviewing-prs.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/review/reviewing-prs.md
|
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] | 0.065199
|
SIG Docs [Reviewers](/docs/contribute/participate/#reviewers) and [Approvers](/docs/contribute/participate/#approvers) do a few extra things when reviewing a change. Every week a specific docs approver volunteers to triage and review pull requests. This person is the "PR Wrangler" for the week. See the [PR Wrangler scheduler](https://github.com/kubernetes/website/wiki/PR-Wranglers) for more information. To become a PR Wrangler, attend the weekly SIG Docs meeting and volunteer. Even if you are not on the schedule for the current week, you can still review pull requests (PRs) that are not already under active review. In addition to the rotation, a bot assigns reviewers and approvers for the PR based on the owners for the affected files. ## Reviewing a PR Kubernetes documentation follows the [Kubernetes code review process](https://github.com/kubernetes/community/blob/master/contributors/guide/owners.md#the-code-review-process). Everything described in [Reviewing a pull request](/docs/contribute/review/reviewing-prs) applies, but Reviewers and Approvers should also do the following: - Using the `/assign` Prow command to assign a specific reviewer to a PR as needed. This is extra important when it comes to requesting technical review from code contributors. {{< note >}} Look at the `reviewers` field in the front-matter at the top of a Markdown file to see who can provide technical review. {{< /note >}} - Making sure the PR follows the [Content](/docs/contribute/style/content-guide/) and [Style](/docs/contribute/style/style-guide/) guides; link the author to the relevant part of the guide(s) if it doesn't. - Using the GitHub \*\*Request Changes\*\* option when applicable to suggest changes to the PR author. - Changing your review status in GitHub using the `/approve` or `/lgtm` Prow commands, if your suggestions are implemented. ## Commit into another person's PR Leaving PR comments is helpful, but there might be times when you need to commit into another person's PR instead. Do not "take over" for another person unless they explicitly ask you to, or you want to resurrect a long-abandoned PR. While it may be faster in the short term, it deprives the person of the chance to contribute. The process you use depends on whether you need to edit a file that is already in the scope of the PR, or a file that the PR has not yet touched. You can't commit into someone else's PR if either of the following things is true: - If the PR author pushed their branch directly to the [https://github.com/kubernetes/website/](https://github.com/kubernetes/website/) repository. Only a reviewer with push access can commit to another user's PR. {{< note >}} Encourage the author to push their branch to their fork before opening the PR next time. {{< /note >}} - The PR author explicitly disallows edits from approvers. ## Prow commands for reviewing [Prow](https://github.com/kubernetes/test-infra/blob/master/prow/README.md) is the Kubernetes-based CI/CD system that runs jobs against pull requests (PRs). Prow enables chatbot-style commands to handle GitHub actions across the Kubernetes organization, like [adding and removing labels](#adding-and-removing-issue-labels), closing issues, and assigning an approver. Enter Prow commands as GitHub comments using the `/` format. The most common prow commands reviewers and approvers use are: {{< table caption="Prow commands for reviewing" >}} Prow Command | Role Restrictions | Description :------------|:------------------|:----------- `/lgtm` | Organization members | Signals that you've finished reviewing a PR and are satisfied with the changes. `/approve` | Approvers | Approves a PR for merging. `/assign` | Anyone | Assigns a person to review or approve a PR `/close` | Organization members | Closes an issue or PR. `/hold` | Anyone | Adds the `do-not-merge/hold` label, indicating the PR cannot be automatically merged. `/hold cancel` | Anyone | Removes the `do-not-merge/hold` label. {{< /table >}} To view the commands that you can use in a PR, see the [Prow Command Reference](https://prow.k8s.io/command-help?repo=kubernetes%2Fwebsite). ## Triage and categorize issues In general, SIG Docs follows the [Kubernetes
| null |
./vendor/kubernetes/content/en/docs/contribute/review/for-approvers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/review/for-approvers.md
|
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] | 0.091706
|
the `do-not-merge/hold` label, indicating the PR cannot be automatically merged. `/hold cancel` | Anyone | Removes the `do-not-merge/hold` label. {{< /table >}} To view the commands that you can use in a PR, see the [Prow Command Reference](https://prow.k8s.io/command-help?repo=kubernetes%2Fwebsite). ## Triage and categorize issues In general, SIG Docs follows the [Kubernetes issue triage](https://github.com/kubernetes/community/blob/master/contributors/guide/issue-triage.md) process and uses the same labels. This GitHub Issue [filter](https://github.com/kubernetes/website/issues?q=is%3Aissue+is%3Aopen+-label%3Apriority%2Fbacklog+-label%3Apriority%2Fimportant-longterm+-label%3Apriority%2Fimportant-soon+-label%3Atriage%2Fneeds-information+-label%3Atriage%2Fsupport+sort%3Acreated-asc) finds issues that might need triage. ### Triaging an issue 1. Validate the issue - Make sure the issue is about website documentation. Some issues can be closed quickly by answering a question or pointing the reporter to a resource. See the [Support requests or code bug reports](#support-requests-or-code-bug-reports) section for details. - Assess whether the issue has merit. - Add the `triage/needs-information` label if the issue doesn't have enough detail to be actionable or the template is not filled out adequately. - Close the issue if it has both the `lifecycle/stale` and `triage/needs-information` labels. 2. Add a priority label (the [Issue Triage Guidelines](https://github.com/kubernetes/community/blob/master/contributors/guide/issue-triage.md#define-priority) define priority labels in detail) {{< table caption="Issue labels" >}} Label | Description :------------|:------------------ `priority/critical-urgent` | Do this right now. `priority/important-soon` | Do this within 3 months. `priority/important-longterm` | Do this within 6 months. `priority/backlog` | Deferrable indefinitely. Do when resources are available. `priority/awaiting-more-evidence` | Placeholder for a potentially good issue so it doesn't get lost. `help` or `good first issue` | Suitable for someone with very little Kubernetes or SIG Docs experience. See [Help Wanted and Good First Issue Labels](https://kubernetes.dev/docs/guide/help-wanted/) for more information. {{< /table >}} At your discretion, take ownership of an issue and submit a PR for it (especially if it's quick or relates to work you're already doing). If you have questions about triaging an issue, ask in `#sig-docs` on Slack or the [kubernetes-sig-docs mailing list](https://groups.google.com/forum/#!forum/kubernetes-sig-docs). ## Adding and removing issue labels To add a label, leave a comment in one of the following formats: - `/` (for example, `/good-first-issue`) - `/ ` (for example, `/triage needs-information` or `/language ja`) To remove a label, leave a comment in one of the following formats: - `/remove-` (for example, `/remove-help`) - `/remove- ` (for example, `/remove-triage needs-information`) In both cases, the label must already exist. If you try to add a label that does not exist, the command is silently ignored. For a list of all labels, see the [website repository's Labels section](https://github.com/kubernetes/website/labels). Not all labels are used by SIG Docs. ### Issue lifecycle labels Issues are generally opened and closed quickly. However, sometimes an issue is inactive after its opened. Other times, an issue may need to remain open for longer than 90 days. {{< table caption="Issue lifecycle labels" >}} Label | Description :------------|:------------------ `lifecycle/stale` | After 90 days with no activity, an issue is automatically labeled as stale. The issue will be automatically closed if the lifecycle is not manually reverted using the `/remove-lifecycle stale` command. `lifecycle/frozen` | An issue with this label will not become stale after 90 days of inactivity. A user manually adds this label to issues that need to remain open for much longer than 90 days, such as those with a `priority/important-longterm` label. {{< /table >}} ## Handling special issue types SIG Docs encounters the following types of issues often enough to document how to handle them. ### Duplicate issues If a single problem has one or more issues open for it, combine them into a single issue. You should decide which issue to keep open (or open a new issue), then move over all relevant information and link related issues. Finally, label all other issues that describe the same problem with `triage/duplicate` and close them.
| null |
./vendor/kubernetes/content/en/docs/contribute/review/for-approvers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/review/for-approvers.md
|
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] | 0.135376
|
or more issues open for it, combine them into a single issue. You should decide which issue to keep open (or open a new issue), then move over all relevant information and link related issues. Finally, label all other issues that describe the same problem with `triage/duplicate` and close them. Only having a single issue to work on reduces confusion and avoids duplicate work on the same problem. ### Dead link issues If the dead link issue is in the API or `kubectl` documentation, assign them `/priority critical-urgent` until the problem is fully understood. Assign all other dead link issues `/priority important-longterm`, as they must be manually fixed. ### Blog issues We expect [Kubernetes Blog](/blog/) entries to become outdated over time. Therefore, we only maintain blog entries less than a year old. If an issue is related to a blog entry that is more than one year old, you should typically close the issue without fixing. You can send a link to [article updates and maintenance](/docs/contribute/blog/#maintenance) as part of the message you send when you close the PR. It is OK to make an exception where a relevant justification applies. ### Support requests or code bug reports Some docs issues are actually issues with the underlying code, or requests for assistance when something, for example a tutorial, doesn't work. For issues unrelated to docs, close the issue with the `kind/support` label and a comment directing the requester to support venues (Slack, Stack Overflow) and, if relevant, the repository to file an issue for bugs with features (`kubernetes/kubernetes` is a great place to start). Sample response to a request for support: ```none This issue sounds more like a request for support and less like an issue specifically for docs. I encourage you to bring your question to the `#kubernetes-users` channel in [Kubernetes slack](https://slack.k8s.io/). You can also search resources like [Stack Overflow](https://stackoverflow.com/questions/tagged/kubernetes) for answers to similar questions. You can also open issues for Kubernetes functionality in https://github.com/kubernetes/kubernetes. If this is a documentation issue, please re-open this issue. ``` Sample code bug report response: ```none This sounds more like an issue with the code than an issue with the documentation. Please open an issue at https://github.com/kubernetes/kubernetes/issues. If this is a documentation issue, please re-open this issue. ``` ### Squashing As an approver, when you review pull requests (PRs), there are various cases where you might do the following: - Advise the contributor to squash their commits. - Squash the commits for the contributor. - Advise the contributor not to squash yet. - Prevent squashing. \*\*Advising contributors to squash\*\*: A new contributor might not know that they should squash commits in their pull requests (PRs). If this is the case, advise them to do so, provide links to useful information, and offer to arrange help if they need it. Some useful links: - [Opening pull requests and squashing your commits](/docs/contribute/new-content/open-a-pr#squashing-commits) for documentation contributors. - [GitHub Workflow](https://www.k8s.dev/docs/guide/github-workflow/), including diagrams, for developers. \*\*Squashing commits for contributors\*\*: If a contributor might have difficulty squashing commits or there is time pressure to merge a PR, you can perform the squash for them: - The kubernetes/website repo is [configured to allow squashing for pull request merges](https://docs.github.com/en/repositories/configuring-branches-and-merges-in-your-repository/configuring-pull-request-merges/configuring-commit-squashing-for-pull-requests). Simply select the \*Squash commits\* button. - In the PR, if the contributor enables maintainers to manage the PR, you can squash their commits and update their fork with the result. Before you squash, advise them to save and push their latest changes to the PR. After you squash, advise them to pull the squashed commit to their local clone. - You can get GitHub to squash the commits by using a label
| null |
./vendor/kubernetes/content/en/docs/contribute/review/for-approvers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/review/for-approvers.md
|
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] | 0.117485
|
commits and update their fork with the result. Before you squash, advise them to save and push their latest changes to the PR. After you squash, advise them to pull the squashed commit to their local clone. - You can get GitHub to squash the commits by using a label so that Tide / GitHub performs the squash or by clicking the \*Squash commits\* button when you merge the PR. \*\*Advise contributors to avoid squashing\*\* - If one commit does something broken or unwise, and the last commit reverts this error, don't squash the commits. Even though the "Files changed" tab in the PR on GitHub and the Netlify preview will both look OK, merging this PR might create rebase or merge conflicts for other folks. Intervene as you see fit to avoid that risk to other contributors. \*\*Never squash\*\* - If you're launching a localization or releasing the docs for a new version, you are merging in a branch that's not from a user's fork, \_never squash the commits\_. Not squashing is essential because you must maintain the commit history for those files.
| null |
./vendor/kubernetes/content/en/docs/contribute/review/for-approvers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/review/for-approvers.md
|
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] | 0.038506
|
This page demonstrates the generation of metrics reference documentation. ## {{% heading "prerequisites" %}} {{< include "prerequisites-ref-docs.md" >}} ## Clone the Kubernetes repository The metric generation happens in the Kubernetes repository. To clone the repository, change directories to where you want the clone to exist. Then, execute the following command: ```shell git clone https://www.github.com/kubernetes/kubernetes ``` This creates a `kubernetes` folder in your current working directory. ## Generate the metrics Inside the cloned Kubernetes repository, locate the `test/instrumentation/documentation` directory. The metrics documentation is generated in this directory. With each release, new metrics are added. After you run the metrics documentation generator script, copy the metrics documentation to the Kubernetes website and publish the updated metrics documentation. To generate the latest metrics, make sure you are in the root of the cloned Kubernetes directory. Then, execute the following command: ```shell ./test/instrumentation/update-documentation.sh ``` To check for changes, execute: ```shell git status ``` The output is similar to: ``` ./test/instrumentation/documentation/documentation.md ./test/instrumentation/documentation/documentation-list.yaml ``` ## Copy the generated metrics documentation file to the Kubernetes website repository 1. Set the Kubernetes website root environment variable. Execute the following command to set the website root: ```shell export WEBSITE\_ROOT= ``` 2. Copy the generated metrics file to the Kubernetes website repository. ```shell cp ./test/instrumentation/documentation/documentation.md "${WEBSITE\_ROOT}/content/en/docs/reference/instrumentation/metrics.md" ``` {{< note >}} If you get an error, check that you have permission to copy the file. You can use `chown` to change the file ownership back to your own user. {{< /note >}} ## Create a pull request To create a pull request, follow the instructions in [Opening a pull request](/docs/contribute/new-content/open-a-pr/). ## {{% heading "whatsnext" %}} \* [Contribute-upstream](/docs/contribute/generate-ref-docs/contribute-upstream/) \* [Generating Reference Docs for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/) \* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/)
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/metrics-reference.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/metrics-reference.md
|
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] | 0.105404
|
This page shows how to update the Kubernetes API reference documentation. The Kubernetes API reference documentation is built from the [Kubernetes OpenAPI spec](https://github.com/kubernetes/kubernetes/blob/master/api/openapi-spec/swagger.json) using the [kubernetes-sigs/reference-docs](https://github.com/kubernetes-sigs/reference-docs) generation code. If you find bugs in the generated documentation, you need to [fix them upstream](/docs/contribute/generate-ref-docs/contribute-upstream/). If you need only to regenerate the reference documentation from the [OpenAPI](https://github.com/OAI/OpenAPI-Specification) spec, continue reading this page. ## {{% heading "prerequisites" %}} {{< include "prerequisites-ref-docs.md" >}} ## Set up the local repositories Create a local workspace and set your `GOPATH`: ```shell mkdir -p $HOME/ export GOPATH=$HOME/ ``` Get a local clone of the following repositories: ```shell git clone github.com/kubernetes-sigs/reference-docs ``` Move into the `gen-apidocs` directory of the `reference-docs` repository and install the required Go packages: ```shell go get -u github.com/go-openapi/loads go get -u github.com/go-openapi/spec ``` If you don't already have the kubernetes/website repository, get it now: ```shell git clone https://github.com//website ``` Get a clone of the kubernetes/kubernetes repository: ```shell git clone https://github.com/kubernetes/kubernetes ``` \* The base directory of your clone of the [kubernetes/kubernetes](https://github.com/kubernetes/kubernetes) repository is `/kubernetes/kubernetes.` The remaining steps refer to your base directory as ``. \* The base directory of your clone of the [kubernetes/website](https://github.com/kubernetes/website) repository is `/website`. The remaining steps refer to your base directory as ``. \* The base directory of your clone of the [kubernetes-sigs/reference-docs](https://github.com/kubernetes-sigs/reference-docs) repository is `/reference-docs`. The remaining steps refer to your base directory as ``. ## Generate the API reference docs This section shows how to generate the [published Kubernetes API reference documentation](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/). ### Set build variables \* Set `K8S\_ROOT` to ``. \* Set `K8S\_WEBROOT` to ``. \* Set `K8S\_RELEASE` to the version of the docs you want to build. For example, if you want to build docs for Kubernetes 1.17.0, set `K8S\_RELEASE` to 1.17.0. For example: ```shell export K8S\_WEBROOT=/website export K8S\_ROOT=/kubernetes export K8S\_RELEASE=1.17.0 ``` ### Create versioned directory and fetch Open API spec The `updateapispec` build target creates the versioned build directory. After the directory is created, the Open API spec is fetched from the `` repository. These steps ensure that the version of the configuration files and Kubernetes Open API spec match the release version. The versioned directory name follows the pattern of `v\_`. In the `` directory, run the following build target: ```shell cd make updateapispec ``` ### Build the API reference docs The `copyapi` target builds the API reference and copies the generated files to directories in ``. Run the following command in ``: ```shell cd make copyapi ``` Verify that these two files have been generated: ```shell [ -e "/gen-apidocs/build/index.html" ] && echo "index.html built" || echo "no index.html" [ -e "/gen-apidocs/build/navData.js" ] && echo "navData.js built" || echo "no navData.js" ``` Go to the base of your local ``, and view which files have been modified: ```shell cd git status ``` The output is similar to: ``` static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/css/bootstrap.min.css static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/css/font-awesome.min.css static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/css/stylesheet.css static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/FontAwesome.otf static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.eot static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.svg static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.ttf static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.woff static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.woff2 static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/index.html static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/js/jquery.scrollTo.min.js static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/js/navData.js static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/js/scroll.js ``` ## API reference location and versioning The generated API reference files (HTML version) are copied to `/static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/`. This directory contains the standalone HTML API documentation. {{< note >}} The Markdown version of the API reference located at `/content/en/docs/reference/kubernetes-api/` is generated separately using the [gen-resourcesdocs](https://github.com/kubernetes-sigs/reference-docs/tree/master/gen-resourcesdocs) generator. {{< /note >}} ## Locally test the API reference Publish a local version of the API reference. Verify the [local preview](http://localhost:1313/docs/reference/generated/kubernetes-api/{{< param "version">}}/). ```shell cd git submodule update --init --recursive --depth 1 # if
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/kubernetes-api.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/kubernetes-api.md
|
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] | 0.051327
|
Markdown version of the API reference located at `/content/en/docs/reference/kubernetes-api/` is generated separately using the [gen-resourcesdocs](https://github.com/kubernetes-sigs/reference-docs/tree/master/gen-resourcesdocs) generator. {{< /note >}} ## Locally test the API reference Publish a local version of the API reference. Verify the [local preview](http://localhost:1313/docs/reference/generated/kubernetes-api/{{< param "version">}}/). ```shell cd git submodule update --init --recursive --depth 1 # if not already done make container-serve ``` ## Commit the changes In ``, run `git add` and `git commit` to commit the change. Submit your changes as a [pull request](/docs/contribute/new-content/open-a-pr/) to the [kubernetes/website](https://github.com/kubernetes/website) repository. Monitor your pull request, and respond to reviewer comments as needed. Continue to monitor your pull request until it has been merged. ## {{% heading "whatsnext" %}} \* [Generating Reference Documentation Quickstart](/docs/contribute/generate-ref-docs/quickstart/) \* [Generating Reference Docs for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/) \* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/)
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/kubernetes-api.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/kubernetes-api.md
|
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] | 0.078114
|
This page shows how to generate the `kubectl` command reference. {{< note >}} This topic shows how to generate reference documentation for [kubectl commands](/docs/reference/generated/kubectl/kubectl-commands) like [kubectl apply](/docs/reference/generated/kubectl/kubectl-commands#apply) and [kubectl taint](/docs/reference/generated/kubectl/kubectl-commands#taint). This topic does not show how to generate the [kubectl](/docs/reference/generated/kubectl/kubectl-commands/) options reference page. For instructions on how to generate the kubectl options reference page, see [Generating Reference Pages for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/). {{< /note >}} ## {{% heading "prerequisites" %}} {{< include "prerequisites-ref-docs.md" >}} ## Set up the local repositories Create a local workspace and set your `GOPATH`: ```shell mkdir -p $HOME/ export GOPATH=$HOME/ ``` Get a local clone of the following repositories: ```shell go get -u github.com/spf13/pflag go get -u github.com/spf13/cobra go get -u gopkg.in/yaml.v2 go get -u github.com/kubernetes-sigs/reference-docs ``` If you don't already have the kubernetes/website repository, get it now: ```shell git clone https://github.com//website $GOPATH/src/github.com//website ``` Get a clone of the kubernetes/kubernetes repository as k8s.io/kubernetes: ```shell git clone https://github.com/kubernetes/kubernetes $GOPATH/src/k8s.io/kubernetes ``` Remove the spf13 package from `$GOPATH/src/k8s.io/kubernetes/vendor/github.com`: ```shell rm -rf $GOPATH/src/k8s.io/kubernetes/vendor/github.com/spf13 ``` The kubernetes/kubernetes repository provides the `kubectl` and `kustomize` source code. \* Determine the base directory of your clone of the [kubernetes/kubernetes](https://github.com/kubernetes/kubernetes) repository. For example, if you followed the preceding step to get the repository, your base directory is `$GOPATH/src/k8s.io/kubernetes`. The remaining steps refer to your base directory as ``. \* Determine the base directory of your clone of the [kubernetes/website](https://github.com/kubernetes/website) repository. For example, if you followed the preceding step to get the repository, your base directory is `$GOPATH/src/github.com//website`. The remaining steps refer to your base directory as ``. \* Determine the base directory of your clone of the [kubernetes-sigs/reference-docs](https://github.com/kubernetes-sigs/reference-docs) repository. For example, if you followed the preceding step to get the repository, your base directory is `$GOPATH/src/github.com/kubernetes-sigs/reference-docs`. The remaining steps refer to your base directory as ``. In your local k8s.io/kubernetes repository, check out the branch of interest, and make sure it is up to date. For example, if you want to generate docs for Kubernetes {{< skew prevMinorVersion >}}.0, you could use these commands: ```shell cd git checkout v{{< skew prevMinorVersion >}}.0 git pull https://github.com/kubernetes/kubernetes {{< skew prevMinorVersion >}}.0 ``` If you do not need to edit the `kubectl` source code, follow the instructions for [Setting build variables](#set-build-variables). ## Edit the kubectl source code The kubectl command reference documentation is automatically generated from the kubectl source code. If you want to change the reference documentation, the first step is to change one or more comments in the kubectl source code. Make the change in your local kubernetes/kubernetes repository, and then submit a pull request to the master branch of [github.com/kubernetes/kubernetes](https://github.com/kubernetes/kubernetes). [PR 56673](https://github.com/kubernetes/kubernetes/pull/56673/files) is an example of a pull request that fixes a typo in the kubectl source code. Monitor your pull request, and respond to reviewer comments. Continue to monitor your pull request until it is merged into the target branch of the kubernetes/kubernetes repository. ## Cherry pick your change into a release branch Your change is now in the master branch, which is used for development of the next Kubernetes release. If you want your change to appear in the docs for a Kubernetes version that has already been released, you need to propose that your change be cherry picked into the release branch. For example, suppose the master branch is being used to develop Kubernetes {{< skew currentVersion >}} and you want to backport your change to the release-{{< skew prevMinorVersion >}} branch. For instructions on how to do this, see [Propose a Cherry Pick](https://git.k8s.io/community/contributors/devel/sig-release/cherry-picks.md). Monitor your cherry-pick pull request until it is merged into the release branch. {{< note >}} Proposing a cherry pick requires that you have permission to set
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/kubectl.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/kubectl.md
|
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] | 0.058272
|
to backport your change to the release-{{< skew prevMinorVersion >}} branch. For instructions on how to do this, see [Propose a Cherry Pick](https://git.k8s.io/community/contributors/devel/sig-release/cherry-picks.md). Monitor your cherry-pick pull request until it is merged into the release branch. {{< note >}} Proposing a cherry pick requires that you have permission to set a label and a milestone in your pull request. If you don't have those permissions, you will need to work with someone who can set the label and milestone for you. {{< /note >}} ## Set build variables Go to ``. On you command line, set the following environment variables. \* Set `K8S\_ROOT` to ``. \* Set `K8S\_WEBROOT` to ``. \* Set `K8S\_RELEASE` to the version of the docs you want to build. For example, if you want to build docs for Kubernetes {{< skew prevMinorVersion >}}, set `K8S\_RELEASE` to {{< skew prevMinorVersion >}}. For example: ```shell export K8S\_WEBROOT=$GOPATH/src/github.com//website export K8S\_ROOT=$GOPATH/src/k8s.io/kubernetes export K8S\_RELEASE={{< skew prevMinorVersion >}} ``` ## Creating a versioned directory The `createversiondirs` build target creates a versioned directory and copies the kubectl reference configuration files to the versioned directory. The versioned directory name follows the pattern of `v\_`. In the `` directory, run the following build target: ```shell cd make createversiondirs ``` ## Check out a release tag in k8s.io/kubernetes In your local `` repository, check out the branch that has the version of Kubernetes that you want to document. For example, if you want to generate docs for Kubernetes {{< skew prevMinorVersion >}}.0, check out the `v{{< skew prevMinorVersion >}}` tag. Make sure your local branch is up to date. ```shell cd git checkout v{{< skew prevMinorVersion >}}.0 git pull https://github.com/kubernetes/kubernetes v{{< skew prevMinorVersion >}}.0 ``` ## Run the doc generation code In your local ``, run the `copycli` build target. The command runs as `root`: ```shell cd make copycli ``` The `copycli` command cleans the temporary build directory, generates the kubectl command files, and copies the collated kubectl command reference HTML page and assets to ``. ## Locate the generated files Verify that these two files have been generated: ```shell [ -e "/gen-kubectldocs/generators/build/index.html" ] && echo "index.html built" || echo "no index.html" [ -e "/gen-kubectldocs/generators/build/navData.js" ] && echo "navData.js built" || echo "no navData.js" ``` ## Locate the copied files Verify that all generated files have been copied to your ``: ```shell cd git status ``` The output should include the modified files: ``` static/docs/reference/generated/kubectl/kubectl-commands.html static/docs/reference/generated/kubectl/navData.js ``` The output may also include: ``` static/docs/reference/generated/kubectl/scroll.js static/docs/reference/generated/kubectl/stylesheet.css static/docs/reference/generated/kubectl/tabvisibility.js static/docs/reference/generated/kubectl/node\_modules/bootstrap/dist/css/bootstrap.min.css static/docs/reference/generated/kubectl/node\_modules/highlight.js/styles/default.css static/docs/reference/generated/kubectl/node\_modules/jquery.scrollto/jquery.scrollTo.min.js static/docs/reference/generated/kubectl/node\_modules/jquery/dist/jquery.min.js static/docs/reference/generated/kubectl/node\_modules/font-awesome/css/font-awesome.min.css ``` ## Locally test the documentation Build the Kubernetes documentation in your local ``. ```shell cd git submodule update --init --recursive --depth 1 # if not already done make container-serve ``` View the [local preview](https://localhost:1313/docs/reference/generated/kubectl/kubectl-commands/). ## Add and commit changes in kubernetes/website Run `git add` and `git commit` to commit the files. ## Create a pull request Create a pull request to the `kubernetes/website` repository. Monitor your pull request, and respond to review comments as needed. Continue to monitor your pull request until it is merged. A few minutes after your pull request is merged, your updated reference topics will be visible in the [published documentation](/docs/home). ## {{% heading "whatsnext" %}} \* [Generating Reference Documentation Quickstart](/docs/contribute/generate-ref-docs/quickstart/) \* [Generating Reference Documentation for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/) \* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/kubectl.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/kubectl.md
|
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|
This page shows how to use the `update-imported-docs.py` script to generate the Kubernetes reference documentation. The script automates the build setup and generates the reference documentation for a release. ## {{% heading "prerequisites" %}} {{< include "prerequisites-ref-docs.md" >}} ## Getting the docs repository Make sure your `website` fork is up-to-date with the `kubernetes/website` remote on GitHub (`main` branch), and clone your `website` fork. ```shell mkdir github.com cd github.com git clone git@github.com:/website.git ``` Determine the base directory of your clone. For example, if you followed the preceding step to get the repository, your base directory is `github.com/website.` The remaining steps refer to your base directory as ``. {{< note>}} If you want to change the content of the component tools and API reference, see the [contributing upstream guide](/docs/contribute/generate-ref-docs/contribute-upstream). {{< /note >}} ## Overview of update-imported-docs The `update-imported-docs.py` script is located in the `/update-imported-docs/` directory. The script builds the following references: \* Component and tool reference pages \* The `kubectl` command reference \* The Kubernetes API reference {{< note >}} The [`kubelet` reference page](/docs/reference/command-line-tools-reference/kubelet/) is not generated by this script and is maintained manually. To update the kubelet reference, follow the standard contribution process described in [Opening a pull request](/docs/contribute/new-content/open-a-pr/). {{< /note >}} The `update-imported-docs.py` script generates the Kubernetes reference documentation from the Kubernetes source code. The script creates a temporary directory under `/tmp` on your machine and clones the required repositories: `kubernetes/kubernetes` and `kubernetes-sigs/reference-docs` into this directory. The script sets your `GOPATH` to this temporary directory. Three additional environment variables are set: \* `K8S\_RELEASE` \* `K8S\_ROOT` \* `K8S\_WEBROOT` The script requires two arguments to run successfully: \* A YAML configuration file (`reference.yml`) \* A release version, for example:`1.17` The configuration file contains a `generate-command` field. The `generate-command` field defines a series of build instructions from `kubernetes-sigs/reference-docs/Makefile`. The `K8S\_RELEASE` variable determines the version of the release. The `update-imported-docs.py` script performs the following steps: 1. Clones the related repositories specified in a configuration file. For the purpose of generating reference docs, the repository that is cloned by default is `kubernetes-sigs/reference-docs`. 1. Runs commands under the cloned repositories to prepare the docs generator and then generates the HTML and Markdown files. 1. Copies the generated HTML and Markdown files to a local clone of the `` repository under locations specified in the configuration file. 1. Updates `kubectl` command links from `kubectl`.md to the refer to the sections in the `kubectl` command reference. When the generated files are in your local clone of the `` repository, you can submit them in a [pull request](/docs/contribute/new-content/open-a-pr/) to ``. ## Configuration file format Each configuration file may contain multiple repos that will be imported together. When necessary, you can customize the configuration file by manually editing it. You may create new config files for importing other groups of documents. The following is an example of the YAML configuration file: ```yaml repos: - name: community remote: https://github.com/kubernetes/community.git branch: master files: - src: contributors/devel/README.md dst: docs/imported/community/devel.md - src: contributors/guide/README.md dst: docs/imported/community/guide.md ``` Single page Markdown documents, imported by the tool, must adhere to the [Documentation Style Guide](/docs/contribute/style/style-guide/). ## Customizing reference.yml Open `/update-imported-docs/reference.yml` for editing. Do not change the content for the `generate-command` field unless you understand how the command is used to build the references. You should not need to update `reference.yml`. At times, changes in the upstream source code, may require changes to the configuration file (for example: golang version dependencies and third-party library changes). If you encounter build issues, contact the SIG-Docs team on the [#sig-docs Kubernetes Slack channel](https://kubernetes.slack.com). {{< note >}} The `generate-command` is an optional entry, which can be used to run a given command or
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/quickstart.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/quickstart.md
|
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] | 0.012434
|
may require changes to the configuration file (for example: golang version dependencies and third-party library changes). If you encounter build issues, contact the SIG-Docs team on the [#sig-docs Kubernetes Slack channel](https://kubernetes.slack.com). {{< note >}} The `generate-command` is an optional entry, which can be used to run a given command or a short script to generate the docs from within a repository. {{< /note >}} In `reference.yml`, `files` contains a list of `src` and `dst` fields. The `src` field contains the location of a generated Markdown file in the cloned `kubernetes-sigs/reference-docs` build directory, and the `dst` field specifies where to copy this file in the cloned `kubernetes/website` repository. For example: ```yaml repos: - name: reference-docs remote: https://github.com/kubernetes-sigs/reference-docs.git files: - src: gen-compdocs/build/kube-apiserver.md dst: content/en/docs/reference/command-line-tools-reference/kube-apiserver.md ... ``` Note that when there are many files to be copied from the same source directory to the same destination directory, you can use wildcards in the value given to `src`. You must provide the directory name as the value for `dst`. For example: ```yaml files: - src: gen-compdocs/build/kubeadm\*.md dst: content/en/docs/reference/setup-tools/kubeadm/generated/ ``` ## Running the update-imported-docs tool You can run the `update-imported-docs.py` tool as follows: ```shell cd /update-imported-docs ./update-imported-docs.py ``` For example: ```shell ./update-imported-docs.py reference.yml 1.17 ``` ## Fixing Links The `release.yml` configuration file contains instructions to fix relative links. To fix relative links within your imported files, set the`gen-absolute-links` property to `true`. You can find an example of this in [`release.yml`](https://github.com/kubernetes/website/blob/main/update-imported-docs/release.yml). ## Adding and committing changes in kubernetes/website List the files that were generated and copied to ``: ```shell cd git status ``` The output shows the new and modified files. The generated output varies depending upon changes made to the upstream source code. ### Generated component tool files ``` content/en/docs/reference/command-line-tools-reference/kube-apiserver.md content/en/docs/reference/command-line-tools-reference/kube-controller-manager.md content/en/docs/reference/command-line-tools-reference/kube-proxy.md content/en/docs/reference/command-line-tools-reference/kube-scheduler.md content/en/docs/reference/setup-tools/kubeadm/generated/kubeadm.md content/en/docs/reference/kubectl/kubectl.md ``` ### Generated kubectl command reference files ``` static/docs/reference/generated/kubectl/kubectl-commands.html static/docs/reference/generated/kubectl/navData.js static/docs/reference/generated/kubectl/scroll.js static/docs/reference/generated/kubectl/stylesheet.css static/docs/reference/generated/kubectl/tabvisibility.js static/docs/reference/generated/kubectl/node\_modules/bootstrap/dist/css/bootstrap.min.css static/docs/reference/generated/kubectl/node\_modules/highlight.js/styles/default.css static/docs/reference/generated/kubectl/node\_modules/jquery.scrollto/jquery.scrollTo.min.js static/docs/reference/generated/kubectl/node\_modules/jquery/dist/jquery.min.js static/docs/reference/generated/kubectl/css/font-awesome.min.css ``` ### Generated Kubernetes API reference directories and files ``` static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/index.html static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/js/navData.js static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/js/scroll.js static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/js/query.scrollTo.min.js static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/css/font-awesome.min.css static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/css/bootstrap.min.css static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/css/stylesheet.css static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/FontAwesome.otf static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.eot static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.svg static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.ttf static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.woff static/docs/reference/generated/kubernetes-api/{{< param "version" >}}/fonts/fontawesome-webfont.woff2 ``` Run `git add` and `git commit` to commit the files. ## Creating a pull request Create a pull request to the `kubernetes/website` repository. Monitor your pull request, and respond to review comments as needed. Continue to monitor your pull request until it is merged. A few minutes after your pull request is merged, your updated reference topics will be visible in the [published documentation](/docs/home/). ## {{% heading "whatsnext" %}} To generate the individual reference documentation by manually setting up the required build repositories and running the build targets, see the following guides: \* [Generating Reference Documentation for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/) \* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/) \* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/quickstart.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/quickstart.md
|
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|
This page shows how to build the Kubernetes component and tool reference pages. ## {{% heading "prerequisites" %}} Start with the [Prerequisites section](/docs/contribute/generate-ref-docs/quickstart/#before-you-begin) in the Reference Documentation Quickstart guide. Follow the [Reference Documentation Quickstart](/docs/contribute/generate-ref-docs/quickstart/) to generate the Kubernetes component and tool reference pages. ## {{% heading "whatsnext" %}} \* [Generating Reference Documentation Quickstart](/docs/contribute/generate-ref-docs/quickstart/) \* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/) \* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/) \* [Contributing to the Upstream Kubernetes Project for Documentation](/docs/contribute/generate-ref-docs/contribute-upstream/)
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/kubernetes-components.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/kubernetes-components.md
|
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] | 0.017572
|
### Requirements: - You need a machine that is running Linux or macOS. - You need to have these tools installed: - [Python](https://www.python.org/downloads/) v3.7.x+ - [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) - [Golang](https://go.dev/dl/) version 1.13+ - [Pip](https://pypi.org/project/pip/) used to install PyYAML - [PyYAML](https://pyyaml.org/) v5.1.2 - [make](https://www.gnu.org/software/make/) - [gcc compiler/linker](https://gcc.gnu.org/) - [Docker](https://docs.docker.com/engine/installation/) (Required only for `kubectl` command reference) - Your `PATH` environment variable must include the required build tools, such as the `Go` binary and `python`. - You need to know how to create a pull request to a GitHub repository. This involves creating your own fork of the repository. For more information, see [Work from a local clone](/docs/contribute/new-content/open-a-pr/#fork-the-repo).
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/prerequisites-ref-docs.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/prerequisites-ref-docs.md
|
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] | 0.029252
|
This page shows how to contribute to the upstream `kubernetes/kubernetes` project. You can fix bugs found in the Kubernetes API documentation or the content of the Kubernetes components such as `kubeadm`, `kube-apiserver`, and `kube-controller-manager`. If you instead want to regenerate the reference documentation for the Kubernetes API or the `kube-\*` components from the upstream code, see the following instructions: - [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/) - [Generating Reference Documentation for the Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/) ## {{% heading "prerequisites" %}} - You need to have these tools installed: - [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) - [Golang](https://go.dev/doc/install) version 1.13+ - [Docker](https://docs.docker.com/engine/installation/) - [etcd](https://github.com/coreos/etcd/) - [make](https://www.gnu.org/software/make/) - [gcc compiler/linker](https://gcc.gnu.org/) - Your `GOPATH` environment variable must be set, and the location of `etcd` must be in your `PATH` environment variable. - You need to know how to create a pull request to a GitHub repository. Typically, this involves creating a fork of the repository. For more information, see [Creating a Pull Request](https://help.github.com/articles/creating-a-pull-request/) and [GitHub Standard Fork & Pull Request Workflow](https://gist.github.com/Chaser324/ce0505fbed06b947d962). ## The big picture The reference documentation for the Kubernetes API and the `kube-\*` components such as `kube-apiserver`, `kube-controller-manager` are automatically generated from the source code in the [upstream Kubernetes](https://github.com/kubernetes/kubernetes/). When you see bugs in the generated documentation, you may want to consider creating a patch to fix it in the upstream project. ## Clone the Kubernetes repository If you don't already have the kubernetes/kubernetes repository, get it now: ```shell mkdir $GOPATH/src cd $GOPATH/src go get github.com/kubernetes/kubernetes ``` Determine the base directory of your clone of the [kubernetes/kubernetes](https://github.com/kubernetes/kubernetes) repository. For example, if you followed the preceding step to get the repository, your base directory is `$GOPATH/src/github.com/kubernetes/kubernetes`. The remaining steps refer to your base directory as ``. Determine the base directory of your clone of the [kubernetes-sigs/reference-docs](https://github.com/kubernetes-sigs/reference-docs) repository. For example, if you followed the preceding step to get the repository, your base directory is `$GOPATH/src/github.com/kubernetes-sigs/reference-docs`. The remaining steps refer to your base directory as ``. ## Edit the Kubernetes source code The Kubernetes API reference documentation is automatically generated from an OpenAPI spec, which is generated from the Kubernetes source code. If you want to change the API reference documentation, the first step is to change one or more comments in the Kubernetes source code. The documentation for the `kube-\*` components is also generated from the upstream source code. You must change the code related to the component you want to fix in order to fix the generated documentation. ### Make changes to the upstream source code {{< note >}} The following steps are an example, not a general procedure. Details will be different in your situation. {{< /note >}} Here's an example of editing a comment in the Kubernetes source code. In your local kubernetes/kubernetes repository, check out the default branch, and make sure it is up to date: ```shell cd git checkout master git pull https://github.com/kubernetes/kubernetes master ``` Suppose this source file in that default branch has the typo "atmost": [kubernetes/kubernetes/staging/src/k8s.io/api/apps/v1/types.go](https://github.com/kubernetes/kubernetes/blob/master/staging/src/k8s.io/api/apps/v1/types.go) In your local environment, open `types.go`, and change "atmost" to "at most". Verify that you have changed the file: ```shell git status ``` The output shows that you are on the master branch, and that the `types.go` source file has been modified: ```shell On branch master ... modified: staging/src/k8s.io/api/apps/v1/types.go ``` ### Commit your edited file Run `git add` and `git commit` to commit the changes you have made so far. In the next step, you will do a second commit. It is important to keep your changes separated into two commits. ### Generate the OpenAPI spec and related files Go to `` and run these scripts: ```shell ./hack/update-codegen.sh ./hack/update-openapi-spec.sh ``` Run `git status`
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/contribute-upstream.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/contribute-upstream.md
|
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] | 0.045703
|
the changes you have made so far. In the next step, you will do a second commit. It is important to keep your changes separated into two commits. ### Generate the OpenAPI spec and related files Go to `` and run these scripts: ```shell ./hack/update-codegen.sh ./hack/update-openapi-spec.sh ``` Run `git status` to see what was generated. ```shell On branch master ... modified: api/openapi-spec/swagger.json modified: api/openapi-spec/v3/apis\_\_apps\_\_v1\_openapi.json modified: pkg/generated/openapi/zz\_generated.openapi.go modified: staging/src/k8s.io/api/apps/v1/generated.proto modified: staging/src/k8s.io/api/apps/v1/types\_swagger\_doc\_generated.go ``` View the contents of `api/openapi-spec/swagger.json` to make sure the typo is fixed. For example, you could run `git diff -a api/openapi-spec/swagger.json`. This is important, because `swagger.json` is the input to the second stage of the doc generation process. Run `git add` and `git commit` to commit your changes. Now you have two commits: one that contains the edited `types.go` file, and one that contains the generated OpenAPI spec and related files. Keep these two commits separate. That is, do not squash your commits. Submit your changes as a [pull request](https://help.github.com/articles/creating-a-pull-request/) to the master branch of the [kubernetes/kubernetes](https://github.com/kubernetes/kubernetes) repository. Monitor your pull request, and respond to reviewer comments as needed. Continue to monitor your pull request until it is merged. [PR 57758](https://github.com/kubernetes/kubernetes/pull/57758) is an example of a pull request that fixes a typo in the Kubernetes source code. {{< note >}} It can be tricky to determine the correct source file to be changed. In the preceding example, the authoritative source file is in the `staging` directory in the `kubernetes/kubernetes` repository. But in your situation,the `staging` directory might not be the place to find the authoritative source. For guidance, check the `README` files in [kubernetes/kubernetes](https://github.com/kubernetes/kubernetes/tree/master/staging) repository and in related repositories, such as [kubernetes/apiserver](https://github.com/kubernetes/apiserver/blob/master/README.md). {{< /note >}} ### Cherry pick your commit into a release branch In the preceding section, you edited a file in the master branch and then ran scripts to generate an OpenAPI spec and related files. Then you submitted your changes in a pull request to the master branch of the kubernetes/kubernetes repository. Now suppose you want to backport your change into a release branch. For example, suppose the master branch is being used to develop Kubernetes version {{< skew latestVersion >}}, and you want to backport your change into the release-{{< skew prevMinorVersion >}} branch. Recall that your pull request has two commits: one for editing `types.go` and one for the files generated by scripts. The next step is to propose a cherry pick of your first commit into the release-{{< skew prevMinorVersion >}} branch. The idea is to cherry pick the commit that edited `types.go`, but not the commit that has the results of running the scripts. For instructions, see [Propose a Cherry Pick](https://git.k8s.io/community/contributors/devel/sig-release/cherry-picks.md). {{< note >}} Proposing a cherry pick requires that you have permission to set a label and a milestone in your pull request. If you don't have those permissions, you will need to work with someone who can set the label and milestone for you. {{< /note >}} When you have a pull request in place for cherry picking your one commit into the release-{{< skew prevMinorVersion >}} branch, the next step is to run these scripts in the release-{{< skew prevMinorVersion >}} branch of your local environment. ```shell ./hack/update-codegen.sh ./hack/update-openapi-spec.sh ``` Now add a commit to your cherry-pick pull request that has the recently generated OpenAPI spec and related files. Monitor your pull request until it gets merged into the release-{{< skew prevMinorVersion >}} branch. At this point, both the master branch and the release-{{< skew prevMinorVersion >}} branch have your updated `types.go` file and a set of generated files that reflect the change you made to `types.go`. Note that
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/contribute-upstream.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/contribute-upstream.md
|
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0.019003920257091522
] | 0.040783
|
Monitor your pull request until it gets merged into the release-{{< skew prevMinorVersion >}} branch. At this point, both the master branch and the release-{{< skew prevMinorVersion >}} branch have your updated `types.go` file and a set of generated files that reflect the change you made to `types.go`. Note that the generated OpenAPI spec and other generated files in the release-{{< skew prevMinorVersion >}} branch are not necessarily the same as the generated files in the master branch. The generated files in the release-{{< skew prevMinorVersion >}} branch contain API elements only from Kubernetes {{< skew prevMinorVersion >}}. The generated files in the master branch might contain API elements that are not in {{< skew prevMinorVersion >}}, but are under development for {{< skew latestVersion >}}. ## Generate the published reference docs The preceding section showed how to edit a source file and then generate several files, including `api/openapi-spec/swagger.json` in the `kubernetes/kubernetes` repository. The `swagger.json` file is the OpenAPI definition file to use for generating the API reference documentation. You are now ready to follow the [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/) guide to generate the [published Kubernetes API reference documentation](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/). ## {{% heading "whatsnext" %}} \* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/) \* [Generating Reference Docs for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/) \* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/)
| null |
./vendor/kubernetes/content/en/docs/contribute/generate-ref-docs/contribute-upstream.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/contribute/generate-ref-docs/contribute-upstream.md
|
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|
{{< glossary\_definition term\_id="configmap" prepend="A ConfigMap is" length="all" >}} {{< caution >}} ConfigMap does not provide secrecy or encryption. If the data you want to store are confidential, use a {{< glossary\_tooltip text="Secret" term\_id="secret" >}} rather than a ConfigMap, or use additional (third party) tools to keep your data private. {{< /caution >}} ## Motivation Use a ConfigMap for setting configuration data separately from application code. For example, imagine that you are developing an application that you can run on your own computer (for development) and in the cloud (to handle real traffic). You write the code to look in an environment variable named `DATABASE\_HOST`. Locally, you set that variable to `localhost`. In the cloud, you set it to refer to a Kubernetes {{< glossary\_tooltip text="Service" term\_id="service" >}} that exposes the database component to your cluster. This lets you fetch a container image running in the cloud and debug the exact same code locally if needed. {{< note >}} A ConfigMap is not designed to hold large chunks of data. The data stored in a ConfigMap cannot exceed 1 MiB. If you need to store settings that are larger than this limit, you may want to consider mounting a volume or use a separate database or file service. {{< /note >}} ## ConfigMap object A ConfigMap is an {{< glossary\_tooltip text="API object" term\_id="object" >}} that lets you store configuration for other objects to use. Unlike most Kubernetes objects that have a `spec`, a ConfigMap has `data` and `binaryData` fields. These fields accept key-value pairs as their values. Both the `data` field and the `binaryData` are optional. The `data` field is designed to contain UTF-8 strings while the `binaryData` field is designed to contain binary data as base64-encoded strings. The name of a ConfigMap must be a valid [DNS subdomain name](/docs/concepts/overview/working-with-objects/names#dns-subdomain-names). Each key under the `data` or the `binaryData` field must consist of alphanumeric characters, `-`, `\_` or `.`. The keys stored in `data` must not overlap with the keys in the `binaryData` field. Starting from v1.19, you can add an `immutable` field to a ConfigMap definition to create an [immutable ConfigMap](#configmap-immutable). ## ConfigMaps and Pods You can write a Pod `spec` that refers to a ConfigMap and configures the container(s) in that Pod based on the data in the ConfigMap. The Pod and the ConfigMap must be in the same {{< glossary\_tooltip text="namespace" term\_id="namespace" >}}. {{< note >}} The `spec` of a {{< glossary\_tooltip text="static Pod" term\_id="static-pod" >}} cannot refer to a ConfigMap or any other API objects. {{< /note >}} Here's an example ConfigMap that has some keys with single values, and other keys where the value looks like a fragment of a configuration format. ```yaml apiVersion: v1 kind: ConfigMap metadata: name: game-demo data: # property-like keys; each key maps to a simple value player\_initial\_lives: "3" ui\_properties\_file\_name: "user-interface.properties" # file-like keys game.properties: | enemy.types=aliens,monsters player.maximum-lives=5 user-interface.properties: | color.good=purple color.bad=yellow allow.textmode=true ``` There are four different ways that you can use a ConfigMap to configure a container inside a Pod: 1. Inside a container command and args 1. Environment variables for a container 1. Add a file in read-only volume, for the application to read 1. Write code to run inside the Pod that uses the Kubernetes API to read a ConfigMap These different methods lend themselves to different ways of modeling the data being consumed. For the first three methods, the {{< glossary\_tooltip text="kubelet" term\_id="kubelet" >}} uses the data from the ConfigMap when it launches container(s) for a Pod. The fourth method means you have to write code to read the ConfigMap and its data. However, because you're using the
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/configmap.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/configmap.md
|
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] | 0.069074
|
modeling the data being consumed. For the first three methods, the {{< glossary\_tooltip text="kubelet" term\_id="kubelet" >}} uses the data from the ConfigMap when it launches container(s) for a Pod. The fourth method means you have to write code to read the ConfigMap and its data. However, because you're using the Kubernetes API directly, your application can subscribe to get updates whenever the ConfigMap changes, and react when that happens. By accessing the Kubernetes API directly, this technique also lets you access a ConfigMap in a different namespace. Here's an example Pod that uses values from `game-demo` to configure a Pod: {{% code\_sample file="configmap/configure-pod.yaml" %}} A ConfigMap doesn't differentiate between single line property values and multi-line file-like values. What matters is how Pods and other objects consume those values. For this example, defining a volume and mounting it inside the `demo` container as `/config` creates two files, `/config/game.properties` and `/config/user-interface.properties`, even though there are four keys in the ConfigMap. This is because the Pod definition specifies an `items` array in the `volumes` section. If you omit the `items` array entirely, every key in the ConfigMap becomes a file with the same name as the key, and you get 4 files. ## Using ConfigMaps ConfigMaps can be mounted as data volumes. ConfigMaps can also be used by other parts of the system, without being directly exposed to the Pod. For example, ConfigMaps can hold data that other parts of the system should use for configuration. The most common way to use ConfigMaps is to configure settings for containers running in a Pod in the same namespace. You can also use a ConfigMap separately. For example, you might encounter {{< glossary\_tooltip text="addons" term\_id="addons" >}} or {{< glossary\_tooltip text="operators" term\_id="operator-pattern" >}} that adjust their behavior based on a ConfigMap. ### Using ConfigMaps as files from a Pod To consume a ConfigMap in a volume in a Pod: 1. Create a ConfigMap or use an existing one. Multiple Pods can reference the same ConfigMap. 1. Modify your Pod definition to add a volume under `.spec.volumes[]`. Name the volume anything, and have a `.spec.volumes[].configMap.name` field set to reference your ConfigMap object. 1. Add a `.spec.containers[].volumeMounts[]` to each container that needs the ConfigMap. Specify `.spec.containers[].volumeMounts[].readOnly = true` and `.spec.containers[].volumeMounts[].mountPath` to an unused directory name where you would like the ConfigMap to appear. 1. Modify your image or command line so that the program looks for files in that directory. Each key in the ConfigMap `data` map becomes the filename under `mountPath`. This is an example of a Pod that mounts a ConfigMap in a volume: ```yaml apiVersion: v1 kind: Pod metadata: name: mypod spec: containers: - name: mypod image: redis volumeMounts: - name: foo mountPath: "/etc/foo" readOnly: true volumes: - name: foo configMap: name: myconfigmap ``` Each ConfigMap you want to use needs to be referred to in `.spec.volumes`. If there are multiple containers in the Pod, then each container needs its own `volumeMounts` block, but only one `.spec.volumes` is needed per ConfigMap. #### Mounted ConfigMaps are updated automatically When a ConfigMap currently consumed in a volume is updated, projected keys are eventually updated as well. The kubelet checks whether the mounted ConfigMap is fresh on every periodic sync. However, the kubelet uses its local cache for getting the current value of the ConfigMap. The type of the cache is configurable using the `configMapAndSecretChangeDetectionStrategy` field in the [KubeletConfiguration struct](/docs/reference/config-api/kubelet-config.v1beta1/). A ConfigMap can be either propagated by watch (default), ttl-based, or by redirecting all requests directly to the API server. As a result, the total delay from the moment when the ConfigMap is updated to the moment when
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/configmap.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/configmap.md
|
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|
the cache is configurable using the `configMapAndSecretChangeDetectionStrategy` field in the [KubeletConfiguration struct](/docs/reference/config-api/kubelet-config.v1beta1/). A ConfigMap can be either propagated by watch (default), ttl-based, or by redirecting all requests directly to the API server. As a result, the total delay from the moment when the ConfigMap is updated to the moment when new keys are projected to the Pod can be as long as the kubelet sync period + cache propagation delay, where the cache propagation delay depends on the chosen cache type (it equals to watch propagation delay, ttl of cache, or zero correspondingly). ConfigMaps consumed as environment variables are not updated automatically and require a pod restart. {{< note >}} A container using a ConfigMap as a [subPath](/docs/concepts/storage/volumes#using-subpath) volume mount will not receive ConfigMap updates. {{< /note >}} ### Using Configmaps as environment variables To use a Configmap in an {{< glossary\_tooltip text="environment variable" term\_id="container-env-variables" >}} in a Pod: 1. For each container in your Pod specification, add an environment variable for each Configmap key that you want to use to the `env[].valueFrom.configMapKeyRef` field. 1. Modify your image and/or command line so that the program looks for values in the specified environment variables. This is an example of defining a ConfigMap as a pod environment variable: The following ConfigMap (myconfigmap.yaml) stores two properties: username and access\_level: ```yaml apiVersion: v1 kind: ConfigMap metadata: name: myconfigmap data: username: k8s-admin access\_level: "1" ``` The following command will create the ConfigMap object: ```shell kubectl apply -f myconfigmap.yaml ``` The following Pod consumes the content of the ConfigMap as environment variables: {{% code\_sample file="configmap/env-configmap.yaml" %}} The `envFrom` field instructs Kubernetes to create environment variables from the sources nested within it. The inner `configMapRef` refers to a ConfigMap by its name and selects all its key-value pairs. Add the Pod to your cluster, then retrieve its logs to see the output from the printenv command. This should confirm that the two key-value pairs from the ConfigMap have been set as environment variables: ```shell kubectl apply -f env-configmap.yaml ``` ```shell kubectl logs pod/env-configmap ``` The output is similar to this: ```console ... username: "k8s-admin" access\_level: "1" ... ``` Sometimes a Pod won't require access to all the values in a ConfigMap. For example, you could have another Pod which only uses the username value from the ConfigMap. For this use case, you can use the `env.valueFrom` syntax instead, which lets you select individual keys in a ConfigMap. The name of the environment variable can also be different from the key within the ConfigMap. For example: ```yaml apiVersion: v1 kind: Pod metadata: name: env-configmap spec: containers: - name: envars-test-container image: nginx env: - name: CONFIGMAP\_USERNAME valueFrom: configMapKeyRef: name: myconfigmap key: username ``` In the Pod created from this manifest, you will see that the environment variable `CONFIGMAP\_USERNAME` is set to the value of the `username` value from the ConfigMap. Other keys from the ConfigMap data are not copied into the environment. It's important to note that the range of characters allowed for environment variable names in pods is [restricted](/docs/tasks/inject-data-application/define-environment-variable-container/#using-environment-variables-inside-of-your-config). If any keys do not meet the rules, those keys are not made available to your container, though the Pod is allowed to start. ## Immutable ConfigMaps {#configmap-immutable} {{< feature-state for\_k8s\_version="v1.21" state="stable" >}} The Kubernetes feature \_Immutable Secrets and ConfigMaps\_ provides an option to set individual Secrets and ConfigMaps as immutable. For clusters that extensively use ConfigMaps (at least tens of thousands of unique ConfigMap to Pod mounts), preventing changes to their data has the following advantages: - protects you from accidental (or unwanted) updates that could cause applications outages - improves performance of your cluster by significantly reducing
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/configmap.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/configmap.md
|
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] | 0.126792
|
as immutable. For clusters that extensively use ConfigMaps (at least tens of thousands of unique ConfigMap to Pod mounts), preventing changes to their data has the following advantages: - protects you from accidental (or unwanted) updates that could cause applications outages - improves performance of your cluster by significantly reducing load on kube-apiserver, by closing watches for ConfigMaps marked as immutable. You can create an immutable ConfigMap by setting the `immutable` field to `true`. For example: ```yaml apiVersion: v1 kind: ConfigMap metadata: ... data: ... immutable: true ``` Once a ConfigMap is marked as immutable, it is \_not\_ possible to revert this change nor to mutate the contents of the `data` or the `binaryData` field. You can only delete and recreate the ConfigMap. Because existing Pods maintain a mount point to the deleted ConfigMap, it is recommended to recreate these pods. ## {{% heading "whatsnext" %}} \* Read about [Secrets](/docs/concepts/configuration/secret/). \* Read [Configure a Pod to Use a ConfigMap](/docs/tasks/configure-pod-container/configure-pod-configmap/). \* Read about [changing a ConfigMap (or any other Kubernetes object)](/docs/tasks/manage-kubernetes-objects/update-api-object-kubectl-patch/) \* Read [The Twelve-Factor App](https://12factor.net/) to understand the motivation for separating code from configuration.
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/configmap.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/configmap.md
|
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] | 0.206985
|
A Secret is an object that contains a small amount of sensitive data such as a password, a token, or a key. Such information might otherwise be put in a {{< glossary\_tooltip term\_id="pod" >}} specification or in a {{< glossary\_tooltip text="container image" term\_id="image" >}}. Using a Secret means that you don't need to include confidential data in your application code. Because Secrets can be created independently of the Pods that use them, there is less risk of the Secret (and its data) being exposed during the workflow of creating, viewing, and editing Pods. Kubernetes, and applications that run in your cluster, can also take additional precautions with Secrets, such as avoiding writing sensitive data to nonvolatile storage. Secrets are similar to {{< glossary\_tooltip text="ConfigMaps" term\_id="configmap" >}} but are specifically intended to hold confidential data. {{< caution >}} Kubernetes Secrets are, by default, stored unencrypted in the API server's underlying data store (etcd). Anyone with API access can retrieve or modify a Secret, and so can anyone with access to etcd. Additionally, anyone who is authorized to create a Pod in a namespace can use that access to read any Secret in that namespace; this includes indirect access such as the ability to create a Deployment. In order to safely use Secrets, take at least the following steps: 1. [Enable Encryption at Rest](/docs/tasks/administer-cluster/encrypt-data/) for Secrets. 1. [Enable or configure RBAC rules](/docs/reference/access-authn-authz/authorization/) with least-privilege access to Secrets. 1. Restrict Secret access to specific containers. 1. [Consider using external Secret store providers](https://secrets-store-csi-driver.sigs.k8s.io/concepts.html#provider-for-the-secrets-store-csi-driver). For more guidelines to manage and improve the security of your Secrets, refer to [Good practices for Kubernetes Secrets](/docs/concepts/security/secrets-good-practices). {{< /caution >}} See [Information security for Secrets](#information-security-for-secrets) for more details. ## Uses for Secrets You can use Secrets for purposes such as the following: - [Set environment variables for a container](/docs/tasks/inject-data-application/distribute-credentials-secure/#define-container-environment-variables-using-secret-data). - [Provide credentials such as SSH keys or passwords to Pods](/docs/tasks/inject-data-application/distribute-credentials-secure/#provide-prod-test-creds). - [Allow the kubelet to pull container images from private registries](/docs/tasks/configure-pod-container/pull-image-private-registry/). The Kubernetes control plane also uses Secrets; for example, [bootstrap token Secrets](#bootstrap-token-secrets) are a mechanism to help automate node registration. ### Use case: dotfiles in a secret volume You can make your data "hidden" by defining a key that begins with a dot. This key represents a dotfile or "hidden" file. For example, when the following Secret is mounted into a volume, `secret-volume`, the volume will contain a single file, called `.secret-file`, and the `dotfile-test-container` will have this file present at the path `/etc/secret-volume/.secret-file`. {{< note >}} Files beginning with dot characters are hidden from the output of `ls -l`; you must use `ls -la` to see them when listing directory contents. {{< /note >}} {{% code language="yaml" file="secret/dotfile-secret.yaml" %}} ### Use case: Secret visible to one container in a Pod Consider a program that needs to handle HTTP requests, do some complex business logic, and then sign some messages with an HMAC. Because it has complex application logic, there might be an unnoticed remote file reading exploit in the server, which could expose the private key to an attacker. This could be divided into two processes in two containers: a frontend container which handles user interaction and business logic, but which cannot see the private key; and a signer container that can see the private key, and responds to simple signing requests from the frontend (for example, over localhost networking). With this partitioned approach, an attacker now has to trick the application server into doing something rather arbitrary, which may be harder than getting it to read a file. ### Alternatives to Secrets Rather than using a Secret to protect confidential data, you can pick from alternatives.
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/secret.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/secret.md
|
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|
over localhost networking). With this partitioned approach, an attacker now has to trick the application server into doing something rather arbitrary, which may be harder than getting it to read a file. ### Alternatives to Secrets Rather than using a Secret to protect confidential data, you can pick from alternatives. Here are some of your options: - If your cloud-native component needs to authenticate to another application that you know is running within the same Kubernetes cluster, you can use a [ServiceAccount](/docs/reference/access-authn-authz/authentication/#service-account-tokens) and its tokens to identify your client. - There are third-party tools that you can run, either within or outside your cluster, that manage sensitive data. For example, a service that Pods access over HTTPS, that reveals a Secret if the client correctly authenticates (for example, with a ServiceAccount token). - For authentication, you can implement a custom signer for X.509 certificates, and use [CertificateSigningRequests](/docs/reference/access-authn-authz/certificate-signing-requests/) to let that custom signer issue certificates to Pods that need them. - You can use a [device plugin](/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/) to expose node-local encryption hardware to a specific Pod. For example, you can schedule trusted Pods onto nodes that provide a Trusted Platform Module, configured out-of-band. You can also combine two or more of those options, including the option to use Secret objects themselves. For example: implement (or deploy) an {{< glossary\_tooltip text="operator" term\_id="operator-pattern" >}} that fetches short-lived session tokens from an external service, and then creates Secrets based on those short-lived session tokens. Pods running in your cluster can make use of the session tokens, and operator ensures they are valid. This separation means that you can run Pods that are unaware of the exact mechanisms for issuing and refreshing those session tokens. ## Types of Secret {#secret-types} When creating a Secret, you can specify its type using the `type` field of the [Secret](/docs/reference/kubernetes-api/config-and-storage-resources/secret-v1/) resource, or certain equivalent `kubectl` command line flags (if available). The Secret type is used to facilitate programmatic handling of the Secret data. Kubernetes provides several built-in types for some common usage scenarios. These types vary in terms of the validations performed and the constraints Kubernetes imposes on them. | Built-in Type | Usage | | ------------------------------------- |---------------------------------------- | | `Opaque` | arbitrary user-defined data | | `kubernetes.io/service-account-token` | ServiceAccount token | | `kubernetes.io/dockercfg` | serialized `~/.dockercfg` file | | `kubernetes.io/dockerconfigjson` | serialized `~/.docker/config.json` file | | `kubernetes.io/basic-auth` | credentials for basic authentication | | `kubernetes.io/ssh-auth` | credentials for SSH authentication | | `kubernetes.io/tls` | data for a TLS client or server | | `bootstrap.kubernetes.io/token` | bootstrap token data | You can define and use your own Secret type by assigning a non-empty string as the `type` value for a Secret object (an empty string is treated as an `Opaque` type). Kubernetes doesn't impose any constraints on the type name. However, if you are using one of the built-in types, you must meet all the requirements defined for that type. If you are defining a type of Secret that's for public use, follow the convention and structure the Secret type to have your domain name before the name, separated by a `/`. For example: `cloud-hosting.example.net/cloud-api-credentials`. ### Opaque Secrets `Opaque` is the default Secret type if you don't explicitly specify a type in a Secret manifest. When you create a Secret using `kubectl`, you must use the `generic` subcommand to indicate an `Opaque` Secret type. For example, the following command creates an empty Secret of type `Opaque`: ```shell kubectl create secret generic empty-secret kubectl get secret empty-secret ``` The output looks like: ``` NAME TYPE DATA AGE empty-secret Opaque 0 2m6s ``` The `DATA` column shows the number of data
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/secret.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/secret.md
|
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] | 0.070657
|
indicate an `Opaque` Secret type. For example, the following command creates an empty Secret of type `Opaque`: ```shell kubectl create secret generic empty-secret kubectl get secret empty-secret ``` The output looks like: ``` NAME TYPE DATA AGE empty-secret Opaque 0 2m6s ``` The `DATA` column shows the number of data items stored in the Secret. In this case, `0` means you have created an empty Secret. ### ServiceAccount token Secrets A `kubernetes.io/service-account-token` type of Secret is used to store a token credential that identifies a {{< glossary\_tooltip text="ServiceAccount" term\_id="service-account" >}}. This is a legacy mechanism that provides long-lived ServiceAccount credentials to Pods. In Kubernetes v1.22 and later, the recommended approach is to obtain a short-lived, automatically rotating ServiceAccount token by using the [`TokenRequest`](/docs/reference/kubernetes-api/authentication-resources/token-request-v1/) API instead. You can get these short-lived tokens using the following methods: \* Call the `TokenRequest` API either directly or by using an API client like `kubectl`. For example, you can use the [`kubectl create token`](/docs/reference/generated/kubectl/kubectl-commands#-em-token-em-) command. \* Request a mounted token in a [projected volume](/docs/reference/access-authn-authz/service-accounts-admin/#bound-service-account-token-volume) in your Pod manifest. Kubernetes creates the token and mounts it in the Pod. The token is automatically invalidated when the Pod that it's mounted in is deleted. For details, see [Launch a Pod using service account token projection](/docs/tasks/configure-pod-container/configure-service-account/#launch-a-pod-using-service-account-token-projection). {{< note >}} You should only create a ServiceAccount token Secret if you can't use the `TokenRequest` API to obtain a token, and the security exposure of persisting a non-expiring token credential in a readable API object is acceptable to you. For instructions, see [Manually create a long-lived API token for a ServiceAccount](/docs/tasks/configure-pod-container/configure-service-account/#manually-create-an-api-token-for-a-serviceaccount). {{< /note >}} When using this Secret type, you need to ensure that the `kubernetes.io/service-account.name` annotation is set to an existing ServiceAccount name. If you are creating both the ServiceAccount and the Secret objects, you should create the ServiceAccount object first. After the Secret is created, a Kubernetes {{< glossary\_tooltip text="controller" term\_id="controller" >}} fills in some other fields such as the `kubernetes.io/service-account.uid` annotation, and the `token` key in the `data` field, which is populated with an authentication token. The following example configuration declares a ServiceAccount token Secret: {{% code language="yaml" file="secret/serviceaccount-token-secret.yaml" %}} After creating the Secret, wait for Kubernetes to populate the `token` key in the `data` field. See the [ServiceAccount](/docs/concepts/security/service-accounts/) documentation for more information on how ServiceAccounts work. You can also check the `automountServiceAccountToken` field and the `serviceAccountName` field of the [`Pod`](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#pod-v1-core) for information on referencing ServiceAccount credentials from within Pods. ### Docker config Secrets If you are creating a Secret to store credentials for accessing a container image registry, you must use one of the following `type` values for that Secret: - `kubernetes.io/dockercfg`: store a serialized `~/.dockercfg` which is the legacy format for configuring Docker command line. The Secret `data` field contains a `.dockercfg` key whose value is the content of a base64 encoded `~/.dockercfg` file. - `kubernetes.io/dockerconfigjson`: store a serialized JSON that follows the same format rules as the `~/.docker/config.json` file, which is a new format for `~/.dockercfg`. The Secret `data` field must contain a `.dockerconfigjson` key for which the value is the content of a base64 encoded `~/.docker/config.json` file. Below is an example for a `kubernetes.io/dockercfg` type of Secret: {{% code language="yaml" file="secret/dockercfg-secret.yaml" %}} {{< note >}} If you do not want to perform the base64 encoding, you can choose to use the `stringData` field instead. {{< /note >}} When you create Docker config Secrets using a manifest, the API server checks whether the expected key exists in the `data` field, and it verifies if the value provided can be parsed as a valid JSON. The API server doesn't validate if the
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/secret.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/secret.md
|
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] | 0.094626
|
the `stringData` field instead. {{< /note >}} When you create Docker config Secrets using a manifest, the API server checks whether the expected key exists in the `data` field, and it verifies if the value provided can be parsed as a valid JSON. The API server doesn't validate if the JSON actually is a Docker config file. You can also use `kubectl` to create a Secret for accessing a container registry, such as when you don't have a Docker configuration file: ```shell kubectl create secret docker-registry secret-tiger-docker \ --docker-email=tiger@acme.example \ --docker-username=tiger \ --docker-password=pass1234 \ --docker-server=my-registry.example:5000 ``` This command creates a Secret of type `kubernetes.io/dockerconfigjson`. Retrieve the `.data.dockerconfigjson` field from that new Secret and decode the data: ```shell kubectl get secret secret-tiger-docker -o jsonpath='{.data.\*}' | base64 -d ``` The output is equivalent to the following JSON document (which is also a valid Docker configuration file): ```json { "auths": { "my-registry.example:5000": { "username": "tiger", "password": "pass1234", "email": "tiger@acme.example", "auth": "dGlnZXI6cGFzczEyMzQ=" } } } ``` {{< caution >}} The `auth` value there is base64 encoded; it is obscured but not secret. Anyone who can read that Secret can learn the registry access bearer token. It is suggested to use [credential providers](/docs/tasks/administer-cluster/kubelet-credential-provider/) to dynamically and securely provide pull secrets on-demand. {{< /caution >}} ### Basic authentication Secret The `kubernetes.io/basic-auth` type is provided for storing credentials needed for basic authentication. When using this Secret type, the `data` field of the Secret must contain one of the following two keys: - `username`: the user name for authentication - `password`: the password or token for authentication Both values for the above two keys are base64 encoded strings. You can alternatively provide the clear text content using the `stringData` field in the Secret manifest. The following manifest is an example of a basic authentication Secret: {{% code language="yaml" file="secret/basicauth-secret.yaml" %}} {{< note >}} The `stringData` field for a Secret does not work well with server-side apply. {{< /note >}} The basic authentication Secret type is provided only for convenience. You can create an `Opaque` type for credentials used for basic authentication. However, using the defined and public Secret type (`kubernetes.io/basic-auth`) helps other people to understand the purpose of your Secret, and sets a convention for what key names to expect. ### SSH authentication Secrets The builtin type `kubernetes.io/ssh-auth` is provided for storing data used in SSH authentication. When using this Secret type, you will have to specify a `ssh-privatekey` key-value pair in the `data` (or `stringData`) field as the SSH credential to use. The following manifest is an example of a Secret used for SSH public/private key authentication: {{% code language="yaml" file="secret/ssh-auth-secret.yaml" %}} The SSH authentication Secret type is provided only for convenience. You can create an `Opaque` type for credentials used for SSH authentication. However, using the defined and public Secret type (`kubernetes.io/ssh-auth`) helps other people to understand the purpose of your Secret, and sets a convention for what key names to expect. The Kubernetes API verifies that the required keys are set for a Secret of this type. {{< caution >}} SSH private keys do not establish trusted communication between an SSH client and host server on their own. A secondary means of establishing trust is needed to mitigate "man in the middle" attacks, such as a `known\_hosts` file added to a ConfigMap. {{< /caution >}} ### TLS Secrets The `kubernetes.io/tls` Secret type is for storing a certificate and its associated key that are typically used for TLS. One common use for TLS Secrets is to configure encryption in transit for an [Ingress](/docs/concepts/services-networking/ingress/), but you can also use it with other resources or directly in your
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/secret.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/secret.md
|
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] | 0.028481
|
### TLS Secrets The `kubernetes.io/tls` Secret type is for storing a certificate and its associated key that are typically used for TLS. One common use for TLS Secrets is to configure encryption in transit for an [Ingress](/docs/concepts/services-networking/ingress/), but you can also use it with other resources or directly in your workload. When using this type of Secret, the `tls.key` and the `tls.crt` key must be provided in the `data` (or `stringData`) field of the Secret configuration, although the API server doesn't actually validate the values for each key. As an alternative to using `stringData`, you can use the `data` field to provide the base64 encoded certificate and private key. For details, see [Constraints on Secret names and data](#restriction-names-data). The following YAML contains an example config for a TLS Secret: {{% code language="yaml" file="secret/tls-auth-secret.yaml" %}} The TLS Secret type is provided only for convenience. You can create an `Opaque` type for credentials used for TLS authentication. However, using the defined and public Secret type (`kubernetes.io/tls`) helps ensure the consistency of Secret format in your project. The API server verifies if the required keys are set for a Secret of this type. To create a TLS Secret using `kubectl`, use the `tls` subcommand: ```shell kubectl create secret tls my-tls-secret \ --cert=path/to/cert/file \ --key=path/to/key/file ``` The public/private key pair must exist before hand. The public key certificate for `--cert` must be .PEM encoded and must match the given private key for `--key`. ### Bootstrap token Secrets The `bootstrap.kubernetes.io/token` Secret type is for tokens used during the node bootstrap process. It stores tokens used to sign well-known ConfigMaps. A bootstrap token Secret is usually created in the `kube-system` namespace and named in the form `bootstrap-token-` where `` is a 6 character string of the token ID. As a Kubernetes manifest, a bootstrap token Secret might look like the following: {{% code language="yaml" file="secret/bootstrap-token-secret-base64.yaml" %}} A bootstrap token Secret has the following keys specified under `data`: - `token-id`: A random 6 character string as the token identifier. Required. - `token-secret`: A random 16 character string as the actual token Secret. Required. - `description`: A human-readable string that describes what the token is used for. Optional. - `expiration`: An absolute UTC time using [RFC3339](https://datatracker.ietf.org/doc/html/rfc3339) specifying when the token should be expired. Optional. - `usage-bootstrap-`: A boolean flag indicating additional usage for the bootstrap token. - `auth-extra-groups`: A comma-separated list of group names that will be authenticated as in addition to the `system:bootstrappers` group. You can alternatively provide the values in the `stringData` field of the Secret without base64 encoding them: {{% code language="yaml" file="secret/bootstrap-token-secret-literal.yaml" %}} {{< note >}} The `stringData` field for a Secret does not work well with server-side apply. {{< /note >}} ## Working with Secrets ### Creating a Secret There are several options to create a Secret: - [Use `kubectl`](/docs/tasks/configmap-secret/managing-secret-using-kubectl/) - [Use a configuration file](/docs/tasks/configmap-secret/managing-secret-using-config-file/) - [Use the Kustomize tool](/docs/tasks/configmap-secret/managing-secret-using-kustomize/) #### Constraints on Secret names and data {#restriction-names-data} The name of a Secret object must be a valid [DNS subdomain name](/docs/concepts/overview/working-with-objects/names#dns-subdomain-names). You can specify the `data` and/or the `stringData` field when creating a configuration file for a Secret. The `data` and the `stringData` fields are optional. The values for all keys in the `data` field have to be base64-encoded strings. If the conversion to base64 string is not desirable, you can choose to specify the `stringData` field instead, which accepts arbitrary strings as values. The keys of `data` and `stringData` must consist of alphanumeric characters, `-`, `\_` or `.`. All key-value pairs in the `stringData` field are internally merged into the `data` field. If a key appears in both the `data` and the
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/secret.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/secret.md
|
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] | 0.068437
|
specify the `stringData` field instead, which accepts arbitrary strings as values. The keys of `data` and `stringData` must consist of alphanumeric characters, `-`, `\_` or `.`. All key-value pairs in the `stringData` field are internally merged into the `data` field. If a key appears in both the `data` and the `stringData` field, the value specified in the `stringData` field takes precedence. #### Size limit {#restriction-data-size} Individual Secrets are limited to 1MiB in size. This is to discourage creation of very large Secrets that could exhaust the API server and kubelet memory. However, creation of many smaller Secrets could also exhaust memory. You can use a [resource quota](/docs/concepts/policy/resource-quotas/) to limit the number of Secrets (or other resources) in a namespace. ### Editing a Secret You can edit an existing Secret unless it is [immutable](#secret-immutable). To edit a Secret, use one of the following methods: - [Use `kubectl`](/docs/tasks/configmap-secret/managing-secret-using-kubectl/#edit-secret) - [Use a configuration file](/docs/tasks/configmap-secret/managing-secret-using-config-file/#edit-secret) You can also edit the data in a Secret using the [Kustomize tool](/docs/tasks/configmap-secret/managing-secret-using-kustomize/#edit-secret). However, this method creates a new `Secret` object with the edited data. Depending on how you created the Secret, as well as how the Secret is used in your Pods, updates to existing `Secret` objects are propagated automatically to Pods that use the data. For more information, refer to [Using Secrets as files from a Pod](#using-secrets-as-files-from-a-pod) section. ### Using a Secret Secrets can be mounted as data volumes or exposed as {{< glossary\_tooltip text="environment variables" term\_id="container-env-variables" >}} to be used by a container in a Pod. Secrets can also be used by other parts of the system, without being directly exposed to the Pod. For example, Secrets can hold credentials that other parts of the system should use to interact with external systems on your behalf. Secret volume sources are validated to ensure that the specified object reference actually points to an object of type Secret. Therefore, a Secret needs to be created before any Pods that depend on it. If the Secret cannot be fetched (perhaps because it does not exist, or due to a temporary lack of connection to the API server) the kubelet periodically retries running that Pod. The kubelet also reports an Event for that Pod, including details of the problem fetching the Secret. #### Optional Secrets {#restriction-secret-must-exist} When you reference a Secret in a Pod, you can mark the Secret as \_optional\_, such as in the following example. If an optional Secret doesn't exist, Kubernetes ignores it. {{% code language="yaml" file="secret/optional-secret.yaml" %}} By default, Secrets are required. None of a Pod's containers will start until all non-optional Secrets are available. If a Pod references a specific key in a non-optional Secret and that Secret does exist, but is missing the named key, the Pod fails during startup. ### Using Secrets as files from a Pod {#using-secrets-as-files-from-a-pod} If you want to access data from a Secret in a Pod, one way to do that is to have Kubernetes make the value of that Secret be available as a file inside the filesystem of one or more of the Pod's containers. For instructions, refer to [Create a Pod that has access to the secret data through a Volume](/docs/tasks/inject-data-application/distribute-credentials-secure/#create-a-pod-that-has-access-to-the-secret-data-through-a-volume). When a volume contains data from a Secret, and that Secret is updated, Kubernetes tracks this and updates the data in the volume, using an eventually-consistent approach. {{< note >}} A container using a Secret as a [subPath](/docs/concepts/storage/volumes#using-subpath) volume mount does not receive automated Secret updates. {{< /note >}} The kubelet keeps a cache of the current keys and values for the Secrets that are used in volumes for pods on that node. You can
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/secret.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/secret.md
|
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] | 0.099937
|
eventually-consistent approach. {{< note >}} A container using a Secret as a [subPath](/docs/concepts/storage/volumes#using-subpath) volume mount does not receive automated Secret updates. {{< /note >}} The kubelet keeps a cache of the current keys and values for the Secrets that are used in volumes for pods on that node. You can configure the way that the kubelet detects changes from the cached values. The `configMapAndSecretChangeDetectionStrategy` field in the [kubelet configuration](/docs/reference/config-api/kubelet-config.v1beta1/) controls which strategy the kubelet uses. The default strategy is `Watch`. Updates to Secrets can be either propagated by an API watch mechanism (the default), based on a cache with a defined time-to-live, or polled from the cluster API server on each kubelet synchronisation loop. As a result, the total delay from the moment when the Secret is updated to the moment when new keys are projected to the Pod can be as long as the kubelet sync period + cache propagation delay, where the cache propagation delay depends on the chosen cache type (following the same order listed in the previous paragraph, these are: watch propagation delay, the configured cache TTL, or zero for direct polling). ### Using Secrets as environment variables To use a Secret in an {{< glossary\_tooltip text="environment variable" term\_id="container-env-variables" >}} in a Pod: 1. For each container in your Pod specification, add an environment variable for each Secret key that you want to use to the `env[].valueFrom.secretKeyRef` field. 1. Modify your image and/or command line so that the program looks for values in the specified environment variables. For instructions, refer to [Define container environment variables using Secret data](/docs/tasks/inject-data-application/distribute-credentials-secure/#define-container-environment-variables-using-secret-data). It's important to note that the range of characters allowed for environment variable names in pods is [restricted](/docs/tasks/inject-data-application/define-environment-variable-container/#using-environment-variables-inside-of-your-config). If any keys do not meet the rules, those keys are not made available to your container, though the Pod is allowed to start. ### Container image pull Secrets {#using-imagepullsecrets} If you want to fetch container images from a private repository, you need a way for the kubelet on each node to authenticate to that repository. You can configure \_image pull Secrets\_ to make this possible. These Secrets are configured at the Pod level. #### Using imagePullSecrets The `imagePullSecrets` field is a list of references to Secrets in the same namespace. You can use an `imagePullSecrets` to pass a Secret that contains a Docker (or other) image registry password to the kubelet. The kubelet uses this information to pull a private image on behalf of your Pod. See the [PodSpec API](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#podspec-v1-core) for more information about the `imagePullSecrets` field. ##### Manually specifying an imagePullSecret You can learn how to specify `imagePullSecrets` from the [container images](/docs/concepts/containers/images/#specifying-imagepullsecrets-on-a-pod) documentation. ##### Arranging for imagePullSecrets to be automatically attached You can manually create `imagePullSecrets`, and reference these from a ServiceAccount. Any Pods created with that ServiceAccount or created with that ServiceAccount by default, will get their `imagePullSecrets` field set to that of the service account. See [Add ImagePullSecrets to a service account](/docs/tasks/configure-pod-container/configure-service-account/#add-imagepullsecrets-to-a-service-account) for a detailed explanation of that process. ### Using Secrets with static Pods {#restriction-static-pod} You cannot use ConfigMaps or Secrets with {{< glossary\_tooltip text="static Pods" term\_id="static-pod" >}}. ## Immutable Secrets {#secret-immutable} {{< feature-state for\_k8s\_version="v1.21" state="stable" >}} Kubernetes lets you mark specific Secrets (and ConfigMaps) as \_immutable\_. Preventing changes to the data of an existing Secret has the following benefits: - protects you from accidental (or unwanted) updates that could cause applications outages - (for clusters that extensively use Secrets - at least tens of thousands of unique Secret to Pod mounts), switching to immutable Secrets improves the performance of your cluster by significantly reducing load on kube-apiserver. The kubelet does not
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/secret.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/secret.md
|
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] | 0.152235
|
you from accidental (or unwanted) updates that could cause applications outages - (for clusters that extensively use Secrets - at least tens of thousands of unique Secret to Pod mounts), switching to immutable Secrets improves the performance of your cluster by significantly reducing load on kube-apiserver. The kubelet does not need to maintain a [watch] on any Secrets that are marked as immutable. ### Marking a Secret as immutable {#secret-immutable-create} You can create an immutable Secret by setting the `immutable` field to `true`. For example, ```yaml apiVersion: v1 kind: Secret metadata: ... data: ... immutable: true ``` You can also update any existing mutable Secret to make it immutable. {{< note >}} Once a Secret or ConfigMap is marked as immutable, it is \_not\_ possible to revert this change nor to mutate the contents of the `data` field. You can only delete and recreate the Secret. Existing Pods maintain a mount point to the deleted Secret - it is recommended to recreate these pods. {{< /note >}} ## Information security for Secrets Although ConfigMap and Secret work similarly, Kubernetes applies some additional protection for Secret objects. Secrets often hold values that span a spectrum of importance, many of which can cause escalations within Kubernetes (e.g. service account tokens) and to external systems. Even if an individual app can reason about the power of the Secrets it expects to interact with, other apps within the same namespace can render those assumptions invalid. A Secret is only sent to a node if a Pod on that node requires it. For mounting Secrets into Pods, the kubelet stores a copy of the data into a `tmpfs` so that the confidential data is not written to durable storage. Once the Pod that depends on the Secret is deleted, the kubelet deletes its local copy of the confidential data from the Secret. There may be several containers in a Pod. By default, containers you define only have access to the default ServiceAccount and its related Secret. You must explicitly define environment variables or map a volume into a container in order to provide access to any other Secret. There may be Secrets for several Pods on the same node. However, only the Secrets that a Pod requests are potentially visible within its containers. Therefore, one Pod does not have access to the Secrets of another Pod. ### Configure least-privilege access to Secrets To enhance the security measures around Secrets, use separate namespaces to isolate access to mounted secrets. {{< warning >}} Any containers that run with `privileged: true` on a node can access all Secrets used on that node. {{< /warning >}} ## {{% heading "whatsnext" %}} - For guidelines to manage and improve the security of your Secrets, refer to [Good practices for Kubernetes Secrets](/docs/concepts/security/secrets-good-practices). - Learn how to [manage Secrets using `kubectl`](/docs/tasks/configmap-secret/managing-secret-using-kubectl/) - Learn how to [manage Secrets using config file](/docs/tasks/configmap-secret/managing-secret-using-config-file/) - Learn how to [manage Secrets using kustomize](/docs/tasks/configmap-secret/managing-secret-using-kustomize/) - Read the [API reference](/docs/reference/kubernetes-api/config-and-storage-resources/secret-v1/) for `Secret`
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/secret.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/secret.md
|
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|
When you specify a {{< glossary\_tooltip term\_id="pod" >}}, you can optionally specify how much of each resource a {{< glossary\_tooltip text="container" term\_id="container" >}} needs. The most common resources to specify are CPU and memory (RAM); there are others. When you specify the resource \_request\_ for containers in a Pod, the {{< glossary\_tooltip text="kube-scheduler" term\_id="kube-scheduler" >}} uses this information to decide which node to place the Pod on. When you specify a resource \_limit\_ for a container, the {{< glossary\_tooltip text="kubelet" term\_id="kubelet" >}} enforces those limits so that the running container is not allowed to use more of that resource than the limit you set. The kubelet also reserves at least the \_request\_ amount of that system resource specifically for that container to use. ## Requests and limits If the node where a Pod is running has enough of a resource available, it's possible (and allowed) for a container to use more resource than its `request` for that resource specifies. For example, if you set a `memory` request of 256 MiB for a container, and that container is in a Pod scheduled to a Node with 8GiB of memory and no other Pods, then the container can try to use more RAM. Limits are a different story. Both `cpu` and `memory` limits are applied by the kubelet (and {{< glossary\_tooltip text="container runtime" term\_id="container-runtime" >}}), and are ultimately enforced by the kernel. On Linux nodes, the Linux kernel enforces limits with {{< glossary\_tooltip text="cgroups" term\_id="cgroup" >}}. The behavior of `cpu` and `memory` limit enforcement is slightly different. `cpu` limits are enforced by CPU throttling. When a container approaches its `cpu` limit, the kernel will restrict access to the CPU corresponding to the container's limit. Thus, a `cpu` limit is a hard limit the kernel enforces. Containers may not use more CPU than is specified in their `cpu` limit. `memory` limits are enforced by the kernel with out of memory (OOM) kills. When a container uses more than its `memory` limit, the kernel may terminate it. However, terminations only happen when the kernel detects memory pressure. Thus, a container that over allocates memory may not be immediately killed. This means `memory` limits are enforced reactively. A container may use more memory than its `memory` limit, but if it does, it may get killed. {{< note >}} There is an alpha feature `MemoryQoS` which attempts to add more preemptive limit enforcement for memory (as opposed to reactive enforcement by the OOM killer). However, this effort is [stalled](https://github.com/kubernetes/enhancements/tree/a47155b340/keps/sig-node/2570-memory-qos#latest-update-stalled) due to a potential livelock situation a memory hungry can cause. {{< /note >}} {{< note >}} If you specify a limit for a resource, but do not specify any request, and no admission-time mechanism has applied a default request for that resource, then Kubernetes copies the limit you specified and uses it as the requested value for the resource. {{< /note >}} ## Resource types \*CPU\* and \*memory\* are each a \*resource type\*. A resource type has a base unit. CPU represents compute processing and is specified in units of [Kubernetes CPUs](#meaning-of-cpu). Memory is specified in units of bytes. For Linux workloads, you can specify \_huge page\_ resources. Huge pages are a Linux-specific feature where the node kernel allocates blocks of memory that are much larger than the default page size. For example, on a system where the default page size is 4KiB, you could specify a limit, `hugepages-2Mi: 80Mi`. If the container tries allocating over 40 2MiB huge pages (a total of 80 MiB), that allocation fails. {{< note >}} You cannot overcommit `hugepages-\*` resources. This is different from the `memory` and `cpu` resources. {{<
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/manage-resources-containers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/manage-resources-containers.md
|
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|
where the default page size is 4KiB, you could specify a limit, `hugepages-2Mi: 80Mi`. If the container tries allocating over 40 2MiB huge pages (a total of 80 MiB), that allocation fails. {{< note >}} You cannot overcommit `hugepages-\*` resources. This is different from the `memory` and `cpu` resources. {{< /note >}} CPU and memory are collectively referred to as \*compute resources\*, or \*resources\*. Compute resources are measurable quantities that can be requested, allocated, and consumed. They are distinct from [API resources](/docs/concepts/overview/kubernetes-api/). API resources, such as Pods and [Services](/docs/concepts/services-networking/service/) are objects that can be read and modified through the Kubernetes API server. ## Resource requests and limits of Pod and container For each container, you can specify resource limits and requests, including the following: \* `spec.containers[].resources.limits.cpu` \* `spec.containers[].resources.limits.memory` \* `spec.containers[].resources.limits.hugepages-` \* `spec.containers[].resources.requests.cpu` \* `spec.containers[].resources.requests.memory` \* `spec.containers[].resources.requests.hugepages-` Although you can only specify requests and limits for individual containers, it is also useful to think about the overall resource requests and limits for a Pod. For a particular resource, a \*Pod resource request/limit\* is the sum of the resource requests/limits of that type for each container in the Pod. ## Pod-level resource specification {{< feature-state feature\_gate\_name="PodLevelResources" >}} Provided your cluster has the `PodLevelResources` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/) enabled, you can specify resource requests and limits at the Pod level. At the Pod level, Kubernetes {{< skew currentVersion >}} only supports resource requests or limits for specific resource types: `cpu` and / or `memory` and / or `hugepages`. With this feature, Kubernetes allows you to declare an overall resource budget for the Pod, which is especially helpful when dealing with a large number of containers where it can be difficult to accurately gauge individual resource needs. Additionally, it enables containers within a Pod to share idle resources with each other, improving resource utilization. For a Pod, you can specify resource limits and requests for CPU and memory by including the following: \* `spec.resources.limits.cpu` \* `spec.resources.limits.memory` \* `spec.resources.limits.hugepages-` \* `spec.resources.requests.cpu` \* `spec.resources.requests.memory` \* `spec.resources.requests.hugepages-` ## Resource units in Kubernetes ### CPU resource units {#meaning-of-cpu} Limits and requests for CPU resources are measured in \*cpu\* units. In Kubernetes, 1 CPU unit is equivalent to \*\*1 physical CPU core\*\*, or \*\*1 virtual core\*\*, depending on whether the node is a physical host or a virtual machine running inside a physical machine. Fractional requests are allowed. When you define a container with `spec.containers[].resources.requests.cpu` set to `0.5`, you are requesting half as much CPU time compared to if you asked for `1.0` CPU. For CPU resource units, the [quantity](/docs/reference/kubernetes-api/common-definitions/quantity/) expression `0.1` is equivalent to the expression `100m`, which can be read as "one hundred millicpu". Some people say "one hundred millicores", and this is understood to mean the same thing. CPU resource is always specified as an absolute amount of resource, never as a relative amount. For example, `500m` CPU represents the roughly same amount of computing power whether that container runs on a single-core, dual-core, or 48-core machine. {{< note >}} Kubernetes doesn't allow you to specify CPU resources with a precision finer than `1m` or `0.001` CPU. To avoid accidentally using an invalid CPU quantity, it's useful to specify CPU units using the milliCPU form instead of the decimal form when using less than 1 CPU unit. For example, you have a Pod that uses `5m` or `0.005` CPU and would like to decrease its CPU resources. By using the decimal form, it's harder to spot that `0.0005` CPU is an invalid value, while by using the milliCPU form, it's easier to spot that `0.5m` is an invalid value. {{< /note >}} ### Memory resource units {#meaning-of-memory} Limits
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/manage-resources-containers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/manage-resources-containers.md
|
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] | 0.131507
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CPU and would like to decrease its CPU resources. By using the decimal form, it's harder to spot that `0.0005` CPU is an invalid value, while by using the milliCPU form, it's easier to spot that `0.5m` is an invalid value. {{< /note >}} ### Memory resource units {#meaning-of-memory} Limits and requests for `memory` are measured in bytes. You can express memory as a plain integer or as a fixed-point number using one of these [quantity](/docs/reference/kubernetes-api/common-definitions/quantity/) suffixes: E, P, T, G, M, k. You can also use the power-of-two equivalents: Ei, Pi, Ti, Gi, Mi, Ki. For example, the following represent roughly the same value: ```shell 128974848, 129e6, 129M, 128974848000m, 123Mi ``` Pay attention to the case of the suffixes. If you request `400m` of memory, this is a request for 0.4 bytes. Someone who types that probably meant to ask for 400 mebibytes (`400Mi`) or 400 megabytes (`400M`). ## Container resources example {#example-1} The following Pod has two containers. Both containers are defined with a request for 0.25 CPU and 64MiB (226 bytes) of memory. Each container has a limit of 0.5 CPU and 128MiB of memory. You can say the Pod has a request of 0.5 CPU and 128 MiB of memory, and a limit of 1 CPU and 256MiB of memory. ```yaml --- apiVersion: v1 kind: Pod metadata: name: frontend spec: containers: - name: app image: images.my-company.example/app:v4 resources: requests: memory: "64Mi" cpu: "250m" limits: memory: "128Mi" cpu: "500m" - name: log-aggregator image: images.my-company.example/log-aggregator:v6 resources: requests: memory: "64Mi" cpu: "250m" limits: memory: "128Mi" cpu: "500m" ``` ## Pod resources example {#example-2} {{< feature-state feature\_gate\_name="PodLevelResources" >}} This feature can be enabled by setting the `PodLevelResources` [feature gate](/docs/reference/command-line-tools-reference/feature-gates). The following Pod has an explicit request of 1 CPU and 100 MiB of memory, and an explicit limit of 1 CPU and 200 MiB of memory. The `pod-resources-demo-ctr-1` container has explicit requests and limits set. However, the `pod-resources-demo-ctr-2` container will simply share the resources available within the Pod resource boundaries, as it does not have explicit requests and limits set. {{% code\_sample file="pods/resource/pod-level-resources.yaml" %}} ## How Pods with resource requests are scheduled When you create a Pod, the Kubernetes scheduler selects a node for the Pod to run on. Each node has a maximum capacity for each of the resource types: the amount of CPU and memory it can provide for Pods. The scheduler ensures that, for each resource type, the sum of the resource requests of the scheduled containers is less than the capacity of the node. Note that although actual memory or CPU resource usage on nodes is very low, the scheduler still refuses to place a Pod on a node if the capacity check fails. This protects against a resource shortage on a node when resource usage later increases, for example, during a daily peak in request rate. ## How Kubernetes applies resource requests and limits {#how-pods-with-resource-limits-are-run} When the kubelet starts a container as part of a Pod, the kubelet passes that container's requests and limits for memory and CPU to the container runtime. On Linux, the container runtime typically configures kernel {{< glossary\_tooltip text="cgroups" term\_id="cgroup" >}} that apply and enforce the limits you defined. - The CPU limit defines a hard ceiling on how much CPU time the container can use. During each scheduling interval (time slice), the Linux kernel checks to see if this limit is exceeded; if so, the kernel waits before allowing that cgroup to resume execution. - The CPU request typically defines a weighting. If several different containers (cgroups) want to run on a contended system, workloads with larger CPU requests are allocated
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/manage-resources-containers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/manage-resources-containers.md
|
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|
the Linux kernel checks to see if this limit is exceeded; if so, the kernel waits before allowing that cgroup to resume execution. - The CPU request typically defines a weighting. If several different containers (cgroups) want to run on a contended system, workloads with larger CPU requests are allocated more CPU time than workloads with small requests. - The memory request is mainly used during (Kubernetes) Pod scheduling. On a node that uses cgroups v2, the container runtime might use the memory request as a hint to set `memory.min` and `memory.low`. - The memory limit defines a memory limit for that cgroup. If the container tries to allocate more memory than this limit, the Linux kernel out-of-memory subsystem activates and, typically, intervenes by stopping one of the processes in the container that tried to allocate memory. If that process is the container's PID 1, and the container is marked as restartable, Kubernetes restarts the container. - The memory limit for the Pod or container can also apply to pages in memory backed volumes, such as an `emptyDir`. The kubelet tracks `tmpfs` emptyDir volumes as container memory use, rather than as local [ephemeral storage](/docs/concepts/storage/ephemeral-storage/). When using memory backed `emptyDir`, be sure to check the notes [below](#memory-backed-emptydir). If a container exceeds its memory request and the node that it runs on becomes short of memory overall, it is likely that the Pod the container belongs to will be {{< glossary\_tooltip text="evicted" term\_id="eviction" >}}. A container might or might not be allowed to exceed its CPU limit for extended periods of time. However, container runtimes don't terminate Pods or containers for excessive CPU usage. To determine whether a container cannot be scheduled or is being killed due to resource limits, see the [Troubleshooting](#troubleshooting) section. ### Monitoring compute & memory resource usage The kubelet reports the resource usage of a Pod as part of the Pod [`status`](/docs/concepts/overview/working-with-objects/#object-spec-and-status). If optional [tools for monitoring](/docs/tasks/debug/debug-cluster/resource-usage-monitoring/) are available in your cluster, then Pod resource usage can be retrieved either from the [Metrics API](/docs/tasks/debug/debug-cluster/resource-metrics-pipeline/#metrics-api) directly or from your monitoring tools. ### Considerations for memory backed `emptyDir` volumes {#memory-backed-emptydir} {{< caution >}} If you do not specify a `sizeLimit` for an `emptyDir` volume, that volume may consume up to that pod's memory limit (`Pod.spec.containers[].resources.limits.memory`). If you do not set a memory limit, the pod has no upper bound on memory consumption, and can consume all available memory on the node. Kubernetes schedules pods based on resource requests (`Pod.spec.containers[].resources.requests`) and will not consider memory usage above the request when deciding if another pod can fit on a given node. This can result in a denial of service and cause the OS to do out-of-memory (OOM) handling. It is possible to create any number of `emptyDir`s that could potentially consume all available memory on the node, making OOM more likely. {{< /caution >}} From the perspective of memory management, there are some similarities between when a process uses memory as a work area and when using memory-backed `emptyDir`. But when using memory as a volume, like memory-backed `emptyDir`, there are additional points below that you should be careful of: \* Files stored on a memory-backed volume are almost entirely managed by the user application. Unlike when used as a work area for a process, you can not rely on things like language-level garbage collection. \* The purpose of writing files to a volume is to save data or pass it between applications. Neither Kubernetes nor the OS may automatically delete files from a volume, so memory used by those files can not be reclaimed when the system or the pod are
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/manage-resources-containers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/manage-resources-containers.md
|
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] | 0.171581
|
language-level garbage collection. \* The purpose of writing files to a volume is to save data or pass it between applications. Neither Kubernetes nor the OS may automatically delete files from a volume, so memory used by those files can not be reclaimed when the system or the pod are under memory pressure. \* A memory-backed `emptyDir` is useful because of its performance, but memory is generally much smaller in size and much higher in cost than other storage media, such as disks or SSDs. Using large amounts of memory for `emptyDir` volumes may affect the normal operation of your pod or of the whole node, so should be used carefully. If you are administering a cluster or namespace, you can also set [ResourceQuota](/docs/concepts/policy/resource-quotas/) that limits memory use; you may also want to define a [LimitRange](/docs/concepts/policy/limit-range/) for additional enforcement. If you specify a `spec.containers[].resources.limits.memory` for each Pod, then the maximum size of an `emptyDir` volume will be the pod's memory limit. As an alternative, a cluster administrator can enforce size limits for `emptyDir` volumes in new Pods using a policy mechanism such as [ValidationAdmissionPolicy](/docs/reference/access-authn-authz/validating-admission-policy). ## Local ephemeral storage For general concepts about local ephemeral storage and hints about configuring the requests and/or limits of ephemeral storage for a container, please check the [local ephemeral storage](/docs/concepts/storage/ephemeral-storage/) page. ### Resource monitoring for local ephemeral storage The kubelet can measure how much local ephemeral storage is being used. It does this as long as you have enabled local ephemeral storage capacity isolation. Kubernetes tracks the amount of ephemeral storage a Pod uses from the following: \* Writing to the container's writable layer (rootfs), container images, or both. \* Writing to local `emptyDir` volumes. \* The Pod's own logs (usually stored under `/var/log/pods`). \* System files managed by Kubernetes that are mapped into the Pod, such as `/etc/hosts`. ## Extended resources Extended resources are fully-qualified resource names outside the `kubernetes.io` domain. They allow cluster operators to advertise and users to consume the non-Kubernetes-built-in resources. There are two steps required to use Extended Resources. First, the cluster operator must advertise an Extended Resource. Second, users must request the Extended Resource in Pods. ### Managing extended resources #### Node-level extended resources Node-level extended resources are tied to nodes. ##### Device plugin managed resources See [Device Plugin](/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/) for how to advertise device plugin managed resources on each node. ##### Other resources To advertise a new node-level extended resource, the cluster operator can submit a `PATCH` HTTP request to the API server to specify the available quantity in the `status.capacity` for a node in the cluster. After this operation, the node's `status.capacity` will include a new resource. The `status.allocatable` field is updated automatically with the new resource asynchronously by the kubelet. Because the scheduler uses the node's `status.allocatable` value when evaluating Pod fitness, the scheduler only takes account of the new value after that asynchronous update. There may be a short delay between patching the node capacity with a new resource and the time when the first Pod that requests the resource can be scheduled on that node. \*\*Example:\*\* Here is an example showing how to use `curl` to form an HTTP request that advertises five "example.com/foo" resources on node `k8s-node-1` whose master is `k8s-master`. ```shell curl --header "Content-Type: application/json-patch+json" \ --request PATCH \ --data '[{"op": "add", "path": "/status/capacity/example.com~1foo", "value": "5"}]' \ http://k8s-master:8080/api/v1/nodes/k8s-node-1/status ``` {{< note >}} In the preceding request, `~1` is the encoding for the character `/` in the patch path. The operation path value in JSON-Patch is interpreted as a JSON-Pointer. For more details, see [IETF RFC 6901, section 3](https://tools.ietf.org/html/rfc6901#section-3). {{< /note >}} #### Cluster-level
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/manage-resources-containers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/manage-resources-containers.md
|
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|
"/status/capacity/example.com~1foo", "value": "5"}]' \ http://k8s-master:8080/api/v1/nodes/k8s-node-1/status ``` {{< note >}} In the preceding request, `~1` is the encoding for the character `/` in the patch path. The operation path value in JSON-Patch is interpreted as a JSON-Pointer. For more details, see [IETF RFC 6901, section 3](https://tools.ietf.org/html/rfc6901#section-3). {{< /note >}} #### Cluster-level extended resources Cluster-level extended resources are not tied to nodes. They are usually managed by scheduler extenders, which handle the resource consumption and resource quota. You can specify the extended resources that are handled by scheduler extenders in [scheduler configuration](/docs/reference/config-api/kube-scheduler-config.v1/) \*\*Example:\*\* The following configuration for a scheduler policy indicates that the cluster-level extended resource "example.com/foo" is handled by the scheduler extender. - The scheduler sends a Pod to the scheduler extender only if the Pod requests "example.com/foo". - The `ignoredByScheduler` field specifies that the scheduler does not check the "example.com/foo" resource in its `PodFitsResources` predicate. ```json { "kind": "Policy", "apiVersion": "v1", "extenders": [ { "urlPrefix":"", "bindVerb": "bind", "managedResources": [ { "name": "example.com/foo", "ignoredByScheduler": true } ] } ] } ``` #### Extended resources allocation by DRA Extended resources allocation by DRA allows cluster administrators to specify an `extendedResourceName` in DeviceClass, then the devices matching the DeviceClass can be requested from a pod's extended resource requests. Read more about [Extended Resource allocation by DRA](/docs/concepts/scheduling-eviction/dynamic-resource-allocation/#extended-resource). ### Consuming extended resources Users can consume extended resources in Pod specs like CPU and memory. The scheduler takes care of the resource accounting so that no more than the available amount is simultaneously allocated to Pods. The API server restricts quantities of extended resources to whole numbers. Examples of \_valid\_ quantities are `3`, `3000m` and `3Ki`. Examples of \_invalid\_ quantities are `0.5` and `1500m` (because `1500m` would result in `1.5`). {{< note >}} Extended resources replace Opaque Integer Resources. Users can use any domain name prefix other than `kubernetes.io` which is reserved. {{< /note >}} To consume an extended resource in a Pod, include the resource name as a key in the `spec.containers[].resources.limits` map in the container spec. {{< note >}} Extended resources cannot be overcommitted, so request and limit must be equal if both are present in a container spec. {{< /note >}} A Pod is scheduled only if all of the resource requests are satisfied, including CPU, memory and any extended resources. The Pod remains in the `PENDING` state as long as the resource request cannot be satisfied. \*\*Example:\*\* The Pod below requests 2 CPUs and 1 "example.com/foo" (an extended resource). ```yaml apiVersion: v1 kind: Pod metadata: name: my-pod spec: containers: - name: my-container image: myimage resources: requests: cpu: 2 example.com/foo: 1 limits: example.com/foo: 1 ``` ## PID limiting Process ID (PID) limits allow for the configuration of a kubelet to limit the number of PIDs that a given Pod can consume. See [PID Limiting](/docs/concepts/policy/pid-limiting/) for information. ## Troubleshooting ### My Pods are pending with event message `FailedScheduling` If the scheduler cannot find any node where a Pod can fit, the Pod remains unscheduled until a place can be found. An [Event](/docs/reference/kubernetes-api/cluster-resources/event-v1/) is produced each time the scheduler fails to find a place for the Pod. You can use `kubectl` to view the events for a Pod; for example: ```shell kubectl describe pod frontend | grep -A 9999999999 Events ``` ``` Events: Type Reason Age From Message ---- ------ ---- ---- ------- Warning FailedScheduling 23s default-scheduler 0/42 nodes available: insufficient cpu ``` In the preceding example, the Pod named "frontend" fails to be scheduled due to insufficient CPU resource on any node. Similar error messages can also suggest failure due to insufficient memory (PodExceedsFreeMemory). In general, if a Pod is pending with a message
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/manage-resources-containers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/manage-resources-containers.md
|
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] | 0.210848
|
23s default-scheduler 0/42 nodes available: insufficient cpu ``` In the preceding example, the Pod named "frontend" fails to be scheduled due to insufficient CPU resource on any node. Similar error messages can also suggest failure due to insufficient memory (PodExceedsFreeMemory). In general, if a Pod is pending with a message of this type, there are several things to try: - Add more nodes to the cluster. - Terminate unneeded Pods to make room for pending Pods. - Check that the Pod is not larger than all the nodes. For example, if all the nodes have a capacity of `cpu: 1`, then a Pod with a request of `cpu: 1.1` will never be scheduled. - Check for node taints. If most of your nodes are tainted, and the new Pod does not tolerate that taint, the scheduler only considers placements onto the remaining nodes that don't have that taint. You can check node capacities and amounts allocated with the `kubectl describe nodes` command. For example: ```shell kubectl describe nodes e2e-test-node-pool-4lw4 ``` ``` Name: e2e-test-node-pool-4lw4 [ ... lines removed for clarity ...] Capacity: cpu: 2 memory: 7679792Ki pods: 110 Allocatable: cpu: 1800m memory: 7474992Ki pods: 110 [ ... lines removed for clarity ...] Non-terminated Pods: (5 in total) Namespace Name CPU Requests CPU Limits Memory Requests Memory Limits --------- ---- ------------ ---------- --------------- ------------- kube-system fluentd-gcp-v1.38-28bv1 100m (5%) 0 (0%) 200Mi (2%) 200Mi (2%) kube-system kube-dns-3297075139-61lj3 260m (13%) 0 (0%) 100Mi (1%) 170Mi (2%) kube-system kube-proxy-e2e-test-... 100m (5%) 0 (0%) 0 (0%) 0 (0%) kube-system monitoring-influxdb-grafana-v4-z1m12 200m (10%) 200m (10%) 600Mi (8%) 600Mi (8%) kube-system node-problem-detector-v0.1-fj7m3 20m (1%) 200m (10%) 20Mi (0%) 100Mi (1%) Allocated resources: (Total limits may be over 100 percent, i.e., overcommitted.) CPU Requests CPU Limits Memory Requests Memory Limits ------------ ---------- --------------- ------------- 680m (34%) 400m (20%) 920Mi (11%) 1070Mi (13%) ``` In the preceding output, you can see that if a Pod requests more than 1.120 CPUs or more than 6.23Gi of memory, that Pod will not fit on the node. By looking at the “Pods” section, you can see which Pods are taking up space on the node. The amount of resources available to Pods is less than the node capacity because system daemons use a portion of the available resources. Within the Kubernetes API, each Node has a `.status.allocatable` field (see [NodeStatus](/docs/reference/kubernetes-api/cluster-resources/node-v1/#NodeStatus) for details). The `.status.allocatable` field describes the amount of resources that are available to Pods on that node (for example: 15 virtual CPUs and 7538 MiB of memory). For more information on node allocatable resources in Kubernetes, see [Reserve Compute Resources for System Daemons](/docs/tasks/administer-cluster/reserve-compute-resources/). You can configure [resource quotas](/docs/concepts/policy/resource-quotas/) to limit the total amount of resources that a namespace can consume. Kubernetes enforces quotas for objects in particular namespace when there is a ResourceQuota in that namespace. For example, if you assign specific namespaces to different teams, you can add ResourceQuotas into those namespaces. Setting resource quotas helps to prevent one team from using so much of any resource that this over-use affects other teams. You should also consider what access you grant to that namespace: \*\*full\*\* write access to a namespace allows someone with that access to remove any resource, including a configured ResourceQuota. ### My container is terminated Your container might get terminated because it is resource-starved. To check whether a container is being killed because it is hitting a resource limit, call `kubectl describe pod` on the Pod of interest: ```shell kubectl describe pod simmemleak-hra99 ``` The output is similar to: ``` Name: simmemleak-hra99 Namespace: default Image(s): saadali/simmemleak Node: kubernetes-node-tf0f/10.240.216.66 Labels: name=simmemleak Status: Running Reason: Message: IP: 10.244.2.75 Containers: simmemleak:
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/manage-resources-containers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/manage-resources-containers.md
|
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] | 0.143166
|
container is being killed because it is hitting a resource limit, call `kubectl describe pod` on the Pod of interest: ```shell kubectl describe pod simmemleak-hra99 ``` The output is similar to: ``` Name: simmemleak-hra99 Namespace: default Image(s): saadali/simmemleak Node: kubernetes-node-tf0f/10.240.216.66 Labels: name=simmemleak Status: Running Reason: Message: IP: 10.244.2.75 Containers: simmemleak: Image: saadali/simmemleak:latest Limits: cpu: 100m memory: 50Mi State: Running Started: Tue, 07 Jul 2019 12:54:41 -0700 Last State: Terminated Reason: OOMKilled Exit Code: 137 Started: Fri, 07 Jul 2019 12:54:30 -0700 Finished: Fri, 07 Jul 2019 12:54:33 -0700 Ready: False Restart Count: 5 Conditions: Type Status Ready False Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 42s default-scheduler Successfully assigned simmemleak-hra99 to kubernetes-node-tf0f Normal Pulled 41s kubelet Container image "saadali/simmemleak:latest" already present on machine Normal Created 41s kubelet Created container simmemleak Normal Started 40s kubelet Started container simmemleak Normal Killing 32s kubelet Killing container with id ead3fb35-5cf5-44ed-9ae1-488115be66c6: Need to kill Pod ``` In the preceding example, the `Restart Count: 5` indicates that the `simmemleak` container in the Pod was terminated and restarted five times (so far). The `OOMKilled` reason shows that the container tried to use more memory than its limit. Your next step might be to check the application code for a memory leak. If you find that the application is behaving how you expect, consider setting a higher memory limit (and possibly request) for that container. ## {{% heading "whatsnext" %}} \* Get hands-on experience [assigning Memory resources to containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/). \* Get hands-on experience [assigning CPU resources to containers and Pods](/docs/tasks/configure-pod-container/assign-cpu-resource/). \* Read how the API reference defines a [container](/docs/reference/kubernetes-api/workload-resources/pod-v1/#Container) and its [resource requirements](/docs/reference/kubernetes-api/workload-resources/pod-v1/#resources) \* Read more about the [local ephemeral storage](/docs/concepts/storage/ephemeral-storage/) \* Read more about the [kube-scheduler configuration reference (v1)](/docs/reference/config-api/kube-scheduler-config.v1/) \* Read more about [Quality of Service classes for Pods](/docs/concepts/workloads/pods/pod-qos/) \* Read more about [Extended Resource allocation by DRA](/docs/concepts/scheduling-eviction/dynamic-resource-allocation/#extended-resource)
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/manage-resources-containers.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/manage-resources-containers.md
|
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] | 0.191316
|
Use kubeconfig files to organize information about clusters, users, namespaces, and authentication mechanisms. The `kubectl` command-line tool uses kubeconfig files to find the information it needs to choose a cluster and communicate with the API server of a cluster. {{< note >}} A file that is used to configure access to clusters is called a \*kubeconfig file\*. This is a generic way of referring to configuration files. It does not mean that there is a file named `kubeconfig`. {{< /note >}} {{< warning >}} Only use kubeconfig files from trusted sources. Using a specially-crafted kubeconfig file could result in malicious code execution or file exposure. If you must use an untrusted kubeconfig file, inspect it carefully first, much as you would a shell script. {{< /warning>}} By default, `kubectl` looks for a file named `config` in the `$HOME/.kube` directory. You can specify other kubeconfig files by setting the `KUBECONFIG` environment variable or by setting the [`--kubeconfig`](/docs/reference/generated/kubectl/kubectl/) flag. For step-by-step instructions on creating and specifying kubeconfig files, see [Configure Access to Multiple Clusters](/docs/tasks/access-application-cluster/configure-access-multiple-clusters). ## Supporting multiple clusters, users, and authentication mechanisms Suppose you have several clusters, and your users and components authenticate in a variety of ways. For example: - A running kubelet might authenticate using certificates. - A user might authenticate using tokens. - Administrators might have sets of certificates that they provide to individual users. With kubeconfig files, you can organize your clusters, users, and namespaces. You can also define contexts to quickly and easily switch between clusters and namespaces. ## Context A \*context\* element in a kubeconfig file is used to group access parameters under a convenient name. Each context has three parameters: cluster, namespace, and user. By default, the `kubectl` command-line tool uses parameters from the \*current context\* to communicate with the cluster. To choose the current context: ``` kubectl config use-context ``` ## The KUBECONFIG environment variable The `KUBECONFIG` environment variable holds a list of kubeconfig files. For Linux and Mac, the list is colon-delimited. For Windows, the list is semicolon-delimited. The `KUBECONFIG` environment variable is not required. If the `KUBECONFIG` environment variable doesn't exist, `kubectl` uses the default kubeconfig file, `$HOME/.kube/config`. If the `KUBECONFIG` environment variable does exist, `kubectl` uses an effective configuration that is the result of merging the files listed in the `KUBECONFIG` environment variable. ## Merging kubeconfig files To see your configuration, enter this command: ```shell kubectl config view ``` As described previously, the output might be from a single kubeconfig file, or it might be the result of merging several kubeconfig files. Here are the rules that `kubectl` uses when it merges kubeconfig files: 1. If the `--kubeconfig` flag is set, use only the specified file. Do not merge. Only one instance of this flag is allowed. Otherwise, if the `KUBECONFIG` environment variable is set, use it as a list of files that should be merged. Merge the files listed in the `KUBECONFIG` environment variable according to these rules: \* Ignore empty filenames. \* Produce errors for files with content that cannot be deserialized. \* The first file to set a particular value or map key wins. \* Never change the value or map key. Example: Preserve the context of the first file to set `current-context`. Example: If two files specify a `red-user`, use only values from the first file's `red-user`. Even if the second file has non-conflicting entries under `red-user`, discard them. For an example of setting the `KUBECONFIG` environment variable, see [Setting the KUBECONFIG environment variable](/docs/tasks/access-application-cluster/configure-access-multiple-clusters/#set-the-kubeconfig-environment-variable). Otherwise, use the default kubeconfig file, `$HOME/.kube/config`, with no merging. 1. Determine the context to use based on the first hit in this
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/organize-cluster-access-kubeconfig.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/organize-cluster-access-kubeconfig.md
|
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] | 0.193996
|
Even if the second file has non-conflicting entries under `red-user`, discard them. For an example of setting the `KUBECONFIG` environment variable, see [Setting the KUBECONFIG environment variable](/docs/tasks/access-application-cluster/configure-access-multiple-clusters/#set-the-kubeconfig-environment-variable). Otherwise, use the default kubeconfig file, `$HOME/.kube/config`, with no merging. 1. Determine the context to use based on the first hit in this chain: 1. Use the `--context` command-line flag if it exists. 1. Use the `current-context` from the merged kubeconfig files. An empty context is allowed at this point. 1. Determine the cluster and user. At this point, there might or might not be a context. Determine the cluster and user based on the first hit in this chain, which is run twice: once for user and once for cluster: 1. Use a command-line flag if it exists: `--user` or `--cluster`. 1. If the context is non-empty, take the user or cluster from the context. The user and cluster can be empty at this point. 1. Determine the actual cluster information to use. At this point, there might or might not be cluster information. Build each piece of the cluster information based on this chain; the first hit wins: 1. Use command line flags if they exist: `--server`, `--certificate-authority`, `--insecure-skip-tls-verify`. 1. If any cluster information attributes exist from the merged kubeconfig files, use them. 1. If there is no server location, fail. 1. Determine the actual user information to use. Build user information using the same rules as cluster information, except allow only one authentication technique per user: 1. Use command line flags if they exist: `--client-certificate`, `--client-key`, `--username`, `--password`, `--token`. 1. Use the `user` fields from the merged kubeconfig files. 1. If there are two conflicting techniques, fail. 1. For any information still missing, use default values and potentially prompt for authentication information. ## File references File and path references in a kubeconfig file are relative to the location of the kubeconfig file. File references on the command line are relative to the current working directory. In `$HOME/.kube/config`, relative paths are stored relatively, and absolute paths are stored absolutely. ## Proxy You can configure `kubectl` to use a proxy per cluster using `proxy-url` in your kubeconfig file, like this: ```yaml apiVersion: v1 kind: Config clusters: - cluster: proxy-url: http://proxy.example.org:3128 server: https://k8s.example.org/k8s/clusters/c-xxyyzz name: development users: - name: developer contexts: - context: name: development ``` ## {{% heading "whatsnext" %}} \* [Configure Access to Multiple Clusters](/docs/tasks/access-application-cluster/configure-access-multiple-clusters/) \* [`kubectl config`](/docs/reference/generated/kubectl/kubectl-commands#config)
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/organize-cluster-access-kubeconfig.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/organize-cluster-access-kubeconfig.md
|
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] | 0.09051
|
Kubernetes has various types of probes: - [Liveness probe](#liveness-probe) - [Readiness probe](#readiness-probe) - [Startup probe](#startup-probe) ## Liveness probe Liveness probes determine when to restart a container. For example, liveness probes could catch a deadlock when an application is running but unable to make progress. If a container fails its liveness probe repeatedly, the kubelet restarts the container. Liveness probes do not wait for readiness probes to succeed. If you want to wait before executing a liveness probe, you can either define `initialDelaySeconds` or use a [startup probe](#startup-probe). ## Readiness probe Readiness probes determine when a container is ready to accept traffic. This is useful when waiting for an application to perform time-consuming initial tasks that depend on its backing services; for example: establishing network connections, loading files, and warming caches. Readiness probes can also be useful later in the container’s lifecycle, for example, when recovering from temporary faults or overloads. If the readiness probe returns a failed state, Kubernetes removes the pod from all matching service endpoints. Readiness probes run on the container during its whole lifecycle. ## Startup probe A startup probe verifies whether the application within a container is started. This can be used to adopt liveness checks on slow starting containers, avoiding them getting killed by the kubelet before they are up and running. If such a probe is configured, it disables liveness and readiness checks until it succeeds. This type of probe is only executed at startup, unlike liveness and readiness probes, which are run periodically. \* Read more about the [Configure Liveness, Readiness and Startup Probes](/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes).
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/liveness-readiness-startup-probes.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/liveness-readiness-startup-probes.md
|
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|
This page outlines the differences in how resources are managed between Linux and Windows. On Linux nodes, {{< glossary\_tooltip text="cgroups" term\_id="cgroup" >}} are used as a pod boundary for resource control. Containers are created within that boundary for network, process and file system isolation. The Linux cgroup APIs can be used to gather CPU, I/O, and memory use statistics. In contrast, Windows uses a [\_job object\_](https://docs.microsoft.com/windows/win32/procthread/job-objects) per container with a system namespace filter to contain all processes in a container and provide logical isolation from the host. (Job objects are a Windows process isolation mechanism and are different from what Kubernetes refers to as a {{< glossary\_tooltip term\_id="job" text="Job" >}}). There is no way to run a Windows container without the namespace filtering in place. This means that system privileges cannot be asserted in the context of the host, and thus privileged containers are not available on Windows. Containers cannot assume an identity from the host because the Security Account Manager (SAM) is separate. ## Memory management {#resource-management-memory} Windows does not have an out-of-memory process killer as Linux does. Windows always treats all user-mode memory allocations as virtual, and pagefiles are mandatory. Windows nodes do not overcommit memory for processes. The net effect is that Windows won't reach out of memory conditions the same way Linux does, and processes page to disk instead of being subject to out of memory (OOM) termination. If memory is over-provisioned and all physical memory is exhausted, then paging can slow down performance. ## CPU management {#resource-management-cpu} Windows can limit the amount of CPU time allocated for different processes but cannot guarantee a minimum amount of CPU time. On Windows, the kubelet supports a command-line flag to set the [scheduling priority](https://docs.microsoft.com/windows/win32/procthread/scheduling-priorities) of the kubelet process: `--windows-priorityclass`. This flag allows the kubelet process to get more CPU time slices when compared to other processes running on the Windows host. More information on the allowable values and their meaning is available at [Windows Priority Classes](https://docs.microsoft.com/en-us/windows/win32/procthread/scheduling-priorities#priority-class). To ensure that running Pods do not starve the kubelet of CPU cycles, set this flag to `ABOVE\_NORMAL\_PRIORITY\_CLASS` or above. ## Resource reservation {#resource-reservation} To account for memory and CPU used by the operating system, the container runtime, and by Kubernetes host processes such as the kubelet, you can (and should) reserve memory and CPU resources with the `--kube-reserved` and/or `--system-reserved` kubelet flags. On Windows these values are only used to calculate the node's [allocatable](/docs/tasks/administer-cluster/reserve-compute-resources/#node-allocatable) resources. {{< caution >}} As you deploy workloads, set resource memory and CPU limits on containers. This also subtracts from `NodeAllocatable` and helps the cluster-wide scheduler in determining which pods to place on which nodes. Scheduling pods without limits may over-provision the Windows nodes and in extreme cases can cause the nodes to become unhealthy. {{< /caution >}} On Windows, a good practice is to reserve at least 2GiB of memory. To determine how much CPU to reserve, identify the maximum pod density for each node and monitor the CPU usage of the system services running there, then choose a value that meets your workload needs.
| null |
./vendor/kubernetes/content/en/docs/concepts/configuration/windows-resource-management.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/configuration/windows-resource-management.md
|
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] | 0.180944
|
This checklist aims to provide basic guidelines on securing applications running in Kubernetes from a developer's perspective. This list is not meant to be exhaustive and is intended to evolve over time. On how to read and use this document: - The order of topics does not reflect an order of priority. - Some checklist items are detailed in the paragraph below the list of each section. - This checklist assumes that a `developer` is a Kubernetes cluster user who interacts with namespaced scope objects. {{< caution >}} Checklists are \*\*not\*\* sufficient for attaining a good security posture on their own. A good security posture requires constant attention and improvement, but a checklist can be the first step on the never-ending journey towards security preparedness. Some recommendations in this checklist may be too restrictive or too lax for your specific security needs. Since Kubernetes security is not "one size fits all", each category of checklist items should be evaluated on its merits. {{< /caution >}} ## Base security hardening The following checklist provides base security hardening recommendations that would apply to most applications deploying to Kubernetes. ### Application design - [ ] Follow the right [security principles](https://www.cncf.io/wp-content/uploads/2022/06/CNCF\_cloud-native-security-whitepaper-May2022-v2.pdf) when designing applications. - [ ] Application configured with appropriate {{< glossary\_tooltip text="QoS class" term\_id="QoS-class" >}} through resource request and limits. - [ ] Memory limit is set for the workloads with a limit equal to or greater than the request. - [ ] CPU limit might be set on sensitive workloads. ### Service account - [ ] Avoid using the `default` ServiceAccount. Instead, create ServiceAccounts for each workload or microservice. - [ ] `automountServiceAccountToken` should be set to `false` unless the pod specifically requires access to the Kubernetes API to operate. ### Pod-level `securityContext` recommendations {#security-context-pod} - [ ] Set `runAsNonRoot: true`. - [ ] Configure the container to execute as a less privileged user (for example, using `runAsUser` and `runAsGroup`), and configure appropriate permissions on files or directories inside the container image. - [ ] Optionally add a supplementary group with `fsGroup` to access persistent volumes. - [ ] The application deploys into a namespace that enforces an appropriate [Pod security standard](/docs/concepts/security/pod-security-standards/). If you cannot control this enforcement for the cluster(s) where the application is deployed, take this into account either through documentation or additional defense in depth. ### Container-level `securityContext` recommendations {#security-context-container} - [ ] Disable privilege escalations using `allowPrivilegeEscalation: false`. - [ ] Configure the root filesystem to be read-only with `readOnlyRootFilesystem: true`. - [ ] Avoid running privileged containers (set `privileged: false`). - [ ] Drop all capabilities from the containers and add back only specific ones that are needed for operation of the container. ### Role Based Access Control (RBAC) {#rbac} - [ ] Permissions such as \*\*create\*\*, \*\*patch\*\*, \*\*update\*\* and \*\*delete\*\* should be only granted if necessary. - [ ] Avoid creating RBAC permissions to create or update roles which can lead to [privilege escalation](/docs/reference/access-authn-authz/rbac/#privilege-escalation-prevention-and-bootstrapping). - [ ] Review bindings for the `system:unauthenticated` group and remove them where possible, as this gives access to anyone who can contact the API server at a network level. The \*\*create\*\*, \*\*update\*\* and \*\*delete\*\* verbs should be permitted judiciously. The \*\*patch\*\* verb if allowed on a Namespace can [allow users to update labels on the namespace or deployments](/docs/concepts/security/rbac-good-practices/#namespace-modification) which can increase the attack surface. For sensitive workloads, consider providing a recommended ValidatingAdmissionPolicy that further restricts the permitted write actions. ### Image security - [ ] Using an image scanning tool to scan an image before deploying containers in the Kubernetes cluster. - [ ] Use container signing to validate the
| null |
./vendor/kubernetes/content/en/docs/concepts/security/application-security-checklist.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/application-security-checklist.md
|
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] | 0.169235
|
increase the attack surface. For sensitive workloads, consider providing a recommended ValidatingAdmissionPolicy that further restricts the permitted write actions. ### Image security - [ ] Using an image scanning tool to scan an image before deploying containers in the Kubernetes cluster. - [ ] Use container signing to validate the container image signature before deploying to the Kubernetes cluster. ### Network policies - [ ] Configure [NetworkPolicies](/docs/concepts/services-networking/network-policies/) to only allow expected ingress and egress traffic from the pods. Make sure that your cluster provides and enforces NetworkPolicy. If you are writing an application that users will deploy to different clusters, consider whether you can assume that NetworkPolicy is available and enforced. ## Advanced security hardening {#advanced} This section of this guide covers some advanced security hardening points which might be valuable based on different Kubernetes environment setup. ### Linux container security Configure {{< glossary\_tooltip text="Security Context" term\_id="Security-Context" >}} for the pod-container. - [ ] [Set the Seccomp Profile for a Container](/docs/tasks/configure-pod-container/security-context/#set-the-seccomp-profile-for-a-container). - [ ] [Restrict a Container's Access to Resources with AppArmor](/docs/tutorials/security/apparmor/). - [ ] [Assign SELinux Labels to a Container](/docs/tasks/configure-pod-container/security-context/#assign-selinux-labels-to-a-container). ### Runtime classes - [ ] Configure appropriate runtime classes for containers. {{% thirdparty-content %}} Some containers may require a different isolation level from what is provided by the default runtime of the cluster. `runtimeClassName` can be used in a podspec to define a different runtime class. For sensitive workloads consider using kernel emulation tools like [gVisor](https://gvisor.dev/docs/), or virtualized isolation using a mechanism such as [kata-containers](https://katacontainers.io/). In high trust environments, consider using [confidential virtual machines](/blog/2023/07/06/confidential-kubernetes/) to improve cluster security even further.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/application-security-checklist.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/application-security-checklist.md
|
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|
This page describes some of the security features that are built into the Linux kernel that you can use in your Kubernetes workloads. To learn how to apply these features to your Pods and containers, refer to [Configure a SecurityContext for a Pod or Container](/docs/tasks/configure-pod-container/security-context/). You should already be familiar with Linux and with the basics of Kubernetes workloads. ## Run workloads without root privileges {#run-without-root} When you deploy a workload in Kubernetes, use the Pod specification to restrict that workload from running as the root user on the node. You can use the Pod `securityContext` to define the specific Linux user and group for the processes in the Pod, and explicitly restrict containers from running as root users. Setting these values in the Pod manifest takes precedence over similar values in the container image, which is especially useful if you're running images that you don't own. {{< caution >}} Ensure that the user or group that you assign to the workload has the permissions required for the application to function correctly. Changing the user or group to one that doesn't have the correct permissions could lead to file access issues or failed operations. {{< /caution >}} Configuring the kernel security features on this page provides fine-grained control over the actions that processes in your cluster can take, but managing these configurations can be challenging at scale. Running containers as non-root, or in user namespaces if you need root privileges, helps to reduce the chance that you'll need to enforce your configured kernel security capabilities. ## Security features in the Linux kernel {#linux-security-features} Kubernetes lets you configure and use Linux kernel features to improve isolation and harden your containerized workloads. Common features include the following: \* \*\*Secure computing mode (seccomp)\*\*: Filter which system calls a process can make \* \*\*AppArmor\*\*: Restrict the access privileges of individual programs \* \*\*Security Enhanced Linux (SELinux)\*\*: Assign security labels to objects for more manageable security policy enforcement To configure settings for one of these features, the operating system that you choose for your nodes must enable the feature in the kernel. For example, Ubuntu 7.10 and later enable AppArmor by default. To learn whether your OS enables a specific feature, consult the OS documentation. You use the `securityContext` field in your Pod specification to define the constraints that apply to those processes. The `securityContext` field also supports other security settings, such as specific Linux capabilities or file access permissions using UIDs and GIDs. To learn more, refer to [Configure a SecurityContext for a Pod or Container](/docs/tasks/configure-pod-container/security-context/). ### seccomp Some of your workloads might need privileges to perform specific actions as the root user on your node's host machine. Linux uses \*capabilities\* to divide the available privileges into categories, so that processes can get the privileges required to perform specific actions without being granted all privileges. Each capability has a set of system calls (syscalls) that a process can make. seccomp lets you restrict these individual syscalls. It can be used to sandbox the privileges of a process, restricting the calls it is able to make from userspace into the kernel. In Kubernetes, you use a \*container runtime\* on each node to run your containers. Example runtimes include CRI-O, Docker, or containerd. Each runtime allows only a subset of Linux capabilities by default. You can further limit the allowed syscalls individually by using a seccomp profile. Container runtimes usually include a default seccomp profile. Kubernetes lets you automatically apply seccomp profiles loaded onto a node to your Pods and containers. {{}} Kubernetes also has the `allowPrivilegeEscalation` setting for Pods and containers. When set to `false`,
| null |
./vendor/kubernetes/content/en/docs/concepts/security/linux-kernel-security-constraints.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/linux-kernel-security-constraints.md
|
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] | 0.142586
|
further limit the allowed syscalls individually by using a seccomp profile. Container runtimes usually include a default seccomp profile. Kubernetes lets you automatically apply seccomp profiles loaded onto a node to your Pods and containers. {{}} Kubernetes also has the `allowPrivilegeEscalation` setting for Pods and containers. When set to `false`, this prevents processes from gaining new capabilities and restricts unprivileged users from changing the applied seccomp profile to a more permissive profile. {{}} To learn how to implement seccomp in Kubernetes, refer to [Restrict a Container's Syscalls with seccomp](/docs/tutorials/security/seccomp/) or the [Seccomp node reference](/docs/reference/node/seccomp/) To learn more about seccomp, see [Seccomp BPF](https://www.kernel.org/doc/html/latest/userspace-api/seccomp\_filter.html) in the Linux kernel documentation. #### Considerations for seccomp {#seccomp-considerations} seccomp is a low-level security configuration that you should only configure yourself if you require fine-grained control over Linux syscalls. Using seccomp, especially at scale, has the following risks: \* Configurations might break during application updates \* Attackers can still use allowed syscalls to exploit vulnerabilities \* Profile management for individual applications becomes challenging at scale \*\*Recommendation\*\*: Use the default seccomp profile that's bundled with your container runtime. If you need a more isolated environment, consider using a sandbox, such as gVisor. Sandboxes solve the preceding risks with custom seccomp profiles, but require more compute resources on your nodes and might have compatibility issues with GPUs and other specialized hardware. ### AppArmor and SELinux: policy-based mandatory access control {#policy-based-mac} You can use Linux policy-based mandatory access control (MAC) mechanisms, such as AppArmor and SELinux, to harden your Kubernetes workloads. #### AppArmor [AppArmor](https://apparmor.net/) is a Linux kernel security module that supplements the standard Linux user and group based permissions to confine programs to a limited set of resources. AppArmor can be configured for any application to reduce its potential attack surface and provide greater in-depth defense. It is configured through profiles tuned to allow the access needed by a specific program or container, such as Linux capabilities, network access, and file permissions. Each profile can be run in either enforcing mode, which blocks access to disallowed resources, or complain mode, which only reports violations. AppArmor can help you to run a more secure deployment by restricting what containers are allowed to do, and/or provide better auditing through system logs. The container runtime that you use might ship with a default AppArmor profile, or you can use a custom profile. To learn how to use AppArmor in Kubernetes, refer to [Restrict a Container's Access to Resources with AppArmor](/docs/tutorials/security/apparmor/). #### SELinux SELinux is a Linux kernel security module that lets you restrict the access that a specific \*subject\*, such as a process, has to the files on your system. You define security policies that apply to subjects that have specific SELinux labels. When a process that has an SELinux label attempts to access a file, the SELinux server checks whether that process' security policy allows the access and makes an authorization decision. In Kubernetes, you can set an SELinux label in the `securityContext` field of your manifest. The specified labels are assigned to those processes. If you have configured security policies that affect those labels, the host OS kernel enforces these policies. To learn how to use SELinux in Kubernetes, refer to [Assign SELinux labels to a container](/docs/tasks/configure-pod-container/security-context/#assign-selinux-labels-to-a-container). #### Differences between AppArmor and SELinux {#apparmor-selinux-diff} The operating system on your Linux nodes usually includes one of either AppArmor or SELinux. Both mechanisms provide similar types of protection, but have differences such as the following: \* \*\*Configuration\*\*: AppArmor uses profiles to define access to resources. SELinux uses policies that apply to specific labels. \* \*\*Policy application\*\*: In AppArmor, you define resources using
| null |
./vendor/kubernetes/content/en/docs/concepts/security/linux-kernel-security-constraints.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/linux-kernel-security-constraints.md
|
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] | 0.205356
|
nodes usually includes one of either AppArmor or SELinux. Both mechanisms provide similar types of protection, but have differences such as the following: \* \*\*Configuration\*\*: AppArmor uses profiles to define access to resources. SELinux uses policies that apply to specific labels. \* \*\*Policy application\*\*: In AppArmor, you define resources using file paths. SELinux uses the index node (inode) of a resource to identify the resource. ### Summary of features {#summary} The following table describes the use cases and scope of each security control. You can use all of these controls together to build a more hardened system. Summary of Linux kernel security features | Security feature | Description | How to use | Example | | --- | --- | --- | --- | | seccomp | Restrict individual kernel calls in the userspace. Reduces the likelihood that a vulnerability that uses a restricted syscall would compromise the system. | Specify a loaded seccomp profile in the Pod or container specification to apply its constraints to the processes in the Pod. | Reject the `unshare` syscall, which was used in [CVE-2022-0185](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-0185). | | AppArmor | Restrict program access to specific resources. Reduces the attack surface of the program. Improves audit logging. | Specify a loaded AppArmor profile in the container specification. | Restrict a read-only program from writing to any file path in the system. | | SELinux | Restrict access to resources such as files, applications, ports, and processes using labels and security policies. | Specify access restrictions for specific labels. Tag processes with those labels to enforce the access restrictions related to the label. | Restrict a container from accessing files outside its own filesystem. | {{< note >}} Mechanisms like AppArmor and SELinux can provide protection that extends beyond the container. For example, you can use SELinux to help mitigate [CVE-2019-5736](https://access.redhat.com/security/cve/cve-2019-5736). {{< /note >}} ### Considerations for managing custom configurations {#considerations-custom-configurations} seccomp, AppArmor, and SELinux usually have a default configuration that offers basic protections. You can also create custom profiles and policies that meet the requirements of your workloads. Managing and distributing these custom configurations at scale might be challenging, especially if you use all three features together. To help you to manage these configurations at scale, use a tool like the [Kubernetes Security Profiles Operator](https://github.com/kubernetes-sigs/security-profiles-operator). ## Kernel-level security features and privileged containers {#kernel-security-features-privileged-containers} Kubernetes lets you specify that some trusted containers can run in \*privileged\* mode. Any container in a Pod can run in privileged mode to use operating system administrative capabilities that would otherwise be inaccessible. This is available for both Windows and Linux. Privileged containers explicitly override some of the Linux kernel constraints that you might use in your workloads, as follows: \* \*\*seccomp\*\*: Privileged containers run as the `Unconfined` seccomp profile, overriding any seccomp profile that you specified in your manifest. \* \*\*AppArmor\*\*: Privileged containers ignore any applied AppArmor profiles. \* \*\*SELinux\*\*: Privileged containers run as the `unconfined\_t` domain. ### Privileged containers {#privileged-containers} Any container in a Pod can enable \*Privileged mode\* if you set the `privileged: true` field in the [`securityContext`](/docs/tasks/configure-pod-container/security-context/) field for the container. Privileged containers override or undo many other hardening settings such as the applied seccomp profile, AppArmor profile, or SELinux constraints. Privileged containers are given all Linux capabilities, including capabilities that they don't require. For example, a root user in a privileged container might be able to use the `CAP\_SYS\_ADMIN` and `CAP\_NET\_ADMIN` capabilities on the node, bypassing the runtime seccomp configuration and other restrictions. In most cases, you should avoid using privileged containers, and instead grant the specific capabilities required by your container using the `capabilities` field in
| null |
./vendor/kubernetes/content/en/docs/concepts/security/linux-kernel-security-constraints.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/linux-kernel-security-constraints.md
|
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] | 0.249519
|
user in a privileged container might be able to use the `CAP\_SYS\_ADMIN` and `CAP\_NET\_ADMIN` capabilities on the node, bypassing the runtime seccomp configuration and other restrictions. In most cases, you should avoid using privileged containers, and instead grant the specific capabilities required by your container using the `capabilities` field in the `securityContext` field. Only use privileged mode if you have a capability that you can't grant with the securityContext. This is useful for containers that want to use operating system administrative capabilities such as manipulating the network stack or accessing hardware devices. In Kubernetes version 1.26 and later, you can also run Windows containers in a similarly privileged mode by setting the `windowsOptions.hostProcess` flag on the security context of the Pod spec. For details and instructions, see [Create a Windows HostProcess Pod](/docs/tasks/configure-pod-container/create-hostprocess-pod/). ## Recommendations and best practices {#recommendations-best-practices} \* Before configuring kernel-level security capabilities, you should consider implementing network-level isolation. For more information, read the [Security Checklist](/docs/concepts/security/security-checklist/#network-security). \* Unless necessary, run Linux workloads as non-root by setting specific user and group IDs in your Pod manifest and by specifying `runAsNonRoot: true`. Additionally, you can run workloads in user namespaces by setting `hostUsers: false` in your Pod manifest. This lets you run containers as root users in the user namespace, but as non-root users in the host namespace on the node. This is still in early stages of development and might not have the level of support that you need. For instructions, refer to [Use a User Namespace With a Pod](/docs/tasks/configure-pod-container/user-namespaces/). ## {{% heading "whatsnext" %}} \* [Learn how to use AppArmor](/docs/tutorials/security/apparmor/) \* [Learn how to use seccomp](/docs/tutorials/security/seccomp/) \* [Learn how to use SELinux](/docs/tasks/configure-pod-container/security-context/#assign-selinux-labels-to-a-container) \* [Seccomp Node Reference](/docs/reference/node/seccomp/)
| null |
./vendor/kubernetes/content/en/docs/concepts/security/linux-kernel-security-constraints.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/linux-kernel-security-constraints.md
|
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|
Kubernetes {{< glossary\_tooltip text="RBAC" term\_id="rbac" >}} is a key security control to ensure that cluster users and workloads have only the access to resources required to execute their roles. It is important to ensure that, when designing permissions for cluster users, the cluster administrator understands the areas where privilege escalation could occur, to reduce the risk of excessive access leading to security incidents. The good practices laid out here should be read in conjunction with the general [RBAC documentation](/docs/reference/access-authn-authz/rbac/#restrictions-on-role-creation-or-update). ## General good practice ### Least privilege Ideally, minimal RBAC rights should be assigned to users and service accounts. Only permissions explicitly required for their operation should be used. While each cluster will be different, some general rules that can be applied are : - Assign permissions at the namespace level where possible. Use RoleBindings as opposed to ClusterRoleBindings to give users rights only within a specific namespace. - Avoid providing wildcard permissions when possible, especially to all resources. As Kubernetes is an extensible system, providing wildcard access gives rights not just to all object types that currently exist in the cluster, but also to all object types which are created in the future. - Administrators should not use `cluster-admin` accounts except where specifically needed. Providing a low privileged account with [impersonation rights](/docs/reference/access-authn-authz/authentication/#user-impersonation) can avoid accidental modification of cluster resources. - Avoid adding users to the `system:masters` group. Any user who is a member of this group bypasses all RBAC rights checks and will always have unrestricted superuser access, which cannot be revoked by removing RoleBindings or ClusterRoleBindings. As an aside, if a cluster is using an authorization webhook, membership of this group also bypasses that webhook (requests from users who are members of that group are never sent to the webhook) ### Minimize distribution of privileged tokens Ideally, pods shouldn't be assigned service accounts that have been granted powerful permissions (for example, any of the rights listed under [privilege escalation risks](#privilege-escalation-risks)). In cases where a workload requires powerful permissions, consider the following practices: - Limit the number of nodes running powerful pods. Ensure that any DaemonSets you run are necessary and are run with least privilege to limit the blast radius of container escapes. - Avoid running powerful pods alongside untrusted or publicly-exposed ones. Consider using [Taints and Toleration](/docs/concepts/scheduling-eviction/taint-and-toleration/), [NodeAffinity](/docs/concepts/scheduling-eviction/assign-pod-node/#node-affinity), or [PodAntiAffinity](/docs/concepts/scheduling-eviction/assign-pod-node/#inter-pod-affinity-and-anti-affinity) to ensure pods don't run alongside untrusted or less-trusted Pods. Pay special attention to situations where less-trustworthy Pods are not meeting the \*\*Restricted\*\* Pod Security Standard. ### Hardening Kubernetes defaults to providing access which may not be required in every cluster. Reviewing the RBAC rights provided by default can provide opportunities for security hardening. In general, changes should not be made to rights provided to `system:` accounts some options to harden cluster rights exist: - Review bindings for the `system:unauthenticated` group and remove them where possible, as this gives access to anyone who can contact the API server at a network level. - Avoid the default auto-mounting of service account tokens by setting `automountServiceAccountToken: false`. For more details, see [using default service account token](/docs/tasks/configure-pod-container/configure-service-account/#use-the-default-service-account-to-access-the-api-server). Setting this value for a Pod will overwrite the service account setting, workloads which require service account tokens can still mount them. ### Periodic review It is vital to periodically review the Kubernetes RBAC settings for redundant entries and possible privilege escalations. If an attacker is able to create a user account with the same name as a deleted user, they can automatically inherit all the rights of the deleted user, especially the rights assigned to that user. ## Kubernetes RBAC - privilege escalation risks {#privilege-escalation-risks} Within Kubernetes RBAC there are a number of
| null |
./vendor/kubernetes/content/en/docs/concepts/security/rbac-good-practices.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/rbac-good-practices.md
|
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] | 0.153939
|
attacker is able to create a user account with the same name as a deleted user, they can automatically inherit all the rights of the deleted user, especially the rights assigned to that user. ## Kubernetes RBAC - privilege escalation risks {#privilege-escalation-risks} Within Kubernetes RBAC there are a number of privileges which, if granted, can allow a user or a service account to escalate their privileges in the cluster or affect systems outside the cluster. This section is intended to provide visibility of the areas where cluster operators should take care, to ensure that they do not inadvertently allow for more access to clusters than intended. ### Listing secrets It is generally clear that allowing `get` access on Secrets will allow a user to read their contents. It is also important to note that `list` and `watch` access also effectively allow for users to reveal the Secret contents. For example, when a List response is returned (for example, via `kubectl get secrets -A -o yaml`), the response includes the contents of all Secrets. ### Workload creation Permission to create workloads (either Pods, or [workload resources](/docs/concepts/workloads/controllers/) that manage Pods) in a namespace implicitly grants access to many other resources in that namespace, such as Secrets, ConfigMaps, and PersistentVolumes that can be mounted in Pods. Additionally, since Pods can run as any [ServiceAccount](/docs/reference/access-authn-authz/service-accounts-admin/), granting permission to create workloads also implicitly grants the API access levels of any service account in that namespace. Users who can run privileged Pods can use that access to gain node access and potentially to further elevate their privileges. Where you do not fully trust a user or other principal with the ability to create suitably secure and isolated Pods, you should enforce either the \*\*Baseline\*\* or \*\*Restricted\*\* Pod Security Standard. You can use [Pod Security admission](/docs/concepts/security/pod-security-admission/) or other (third party) mechanisms to implement that enforcement. For these reasons, namespaces should be used to separate resources requiring different levels of trust or tenancy. It is still considered best practice to follow [least privilege](#least-privilege) principles and assign the minimum set of permissions, but boundaries within a namespace should be considered weak. ### Persistent volume creation If someone - or some application - is allowed to create arbitrary PersistentVolumes, that access includes the creation of `hostPath` volumes, which then means that a Pod would get access to the underlying host filesystem(s) on the associated node. Granting that ability is a security risk. There are many ways a container with unrestricted access to the host filesystem can escalate privileges, including reading data from other containers, and abusing the credentials of system services, such as Kubelet. You should only allow access to create PersistentVolume objects for: - Users (cluster operators) that need this access for their work, and who you trust. - The Kubernetes control plane components which creates PersistentVolumes based on PersistentVolumeClaims that are configured for automatic provisioning. This is usually setup by the Kubernetes provider or by the operator when installing a CSI driver. Where access to persistent storage is required trusted administrators should create PersistentVolumes, and constrained users should use PersistentVolumeClaims to access that storage. ### Access to `proxy` subresource of Nodes Users with access to the proxy sub-resource of node objects have rights to the Kubelet API, which allows for command execution on every pod on the node(s) to which they have rights. This access bypasses audit logging and admission control, so care should be taken before granting rights to this resource. ### Escalate verb Generally, the RBAC system prevents users from creating clusterroles with more rights than the user possesses. The exception to this is the `escalate`
| null |
./vendor/kubernetes/content/en/docs/concepts/security/rbac-good-practices.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/rbac-good-practices.md
|
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0.038628045469522476,
-0.020595882087945938
] | 0.188832
|
to which they have rights. This access bypasses audit logging and admission control, so care should be taken before granting rights to this resource. ### Escalate verb Generally, the RBAC system prevents users from creating clusterroles with more rights than the user possesses. The exception to this is the `escalate` verb. As noted in the [RBAC documentation](/docs/reference/access-authn-authz/rbac/#restrictions-on-role-creation-or-update), users with this right can effectively escalate their privileges. ### Bind verb Similar to the `escalate` verb, granting users this right allows for the bypass of Kubernetes in-built protections against privilege escalation, allowing users to create bindings to roles with rights they do not already have. ### Impersonate verb This verb allows users to impersonate and gain the rights of other users in the cluster. Care should be taken when granting it, to ensure that excessive permissions cannot be gained via one of the impersonated accounts. ### CSRs and certificate issuing The CSR API allows for users with `create` rights to CSRs and `update` rights on `certificatesigningrequests/approval` where the signer is `kubernetes.io/kube-apiserver-client` to create new client certificates which allow users to authenticate to the cluster. Those client certificates can have arbitrary names including duplicates of Kubernetes system components. This will effectively allow for privilege escalation. ### Token request Users with `create` rights on `serviceaccounts/token` can create TokenRequests to issue tokens for existing service accounts. ### Control admission webhooks Users with control over `validatingwebhookconfigurations` or `mutatingwebhookconfigurations` can control webhooks that can read any object admitted to the cluster, and in the case of mutating webhooks, also mutate admitted objects. ### Namespace modification Users who can perform \*\*patch\*\* operations on Namespace objects (through a namespaced RoleBinding to a Role with that access) can modify labels on that namespace. In clusters where Pod Security Admission is used, this may allow a user to configure the namespace for a more permissive policy than intended by the administrators. For clusters where NetworkPolicy is used, users may be set labels that indirectly allow access to services that an administrator did not intend to allow. ## Kubernetes RBAC - denial of service risks {#denial-of-service-risks} ### Object creation denial-of-service {#object-creation-dos} Users who have rights to create objects in a cluster may be able to create sufficient large objects to create a denial of service condition either based on the size or number of objects, as discussed in [etcd used by Kubernetes is vulnerable to OOM attack](https://github.com/kubernetes/kubernetes/issues/107325). This may be specifically relevant in multi-tenant clusters if semi-trusted or untrusted users are allowed limited access to a system. One option for mitigation of this issue would be to use [resource quotas](/docs/concepts/policy/resource-quotas/#object-count-quota) to limit the quantity of objects which can be created. ## {{% heading "whatsnext" %}} \* To learn more about RBAC, see the [RBAC documentation](/docs/reference/access-authn-authz/rbac/).
| null |
./vendor/kubernetes/content/en/docs/concepts/security/rbac-good-practices.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/rbac-good-practices.md
|
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|
Kubernetes is based on a cloud native architecture and draws on advice from the {{< glossary\_tooltip text="CNCF" term\_id="cncf" >}} about good practices for cloud native information security. Read on for an overview of how Kubernetes is designed to help you deploy a secure cloud native platform. ## Cloud native information security {{< comment >}} There are localized versions available of this whitepaper; if you can link to one of those when localizing, that's even better. {{< /comment >}} The CNCF [white paper](https://github.com/cncf/tag-security/blob/main/community/resources/security-whitepaper/v2/CNCF\_cloud-native-security-whitepaper-May2022-v2.pdf) on cloud native security defines security controls and practices that are appropriate to different \_lifecycle phases\_. ## \_Develop\_ lifecycle phase {#lifecycle-phase-develop} - Ensure the integrity of development environments. - Design applications following good practices for information security, appropriate for your context. - Consider end user security as part of solution design. To achieve this, you can: 1. Adopt an architecture, such as [zero trust](https://glossary.cncf.io/zero-trust-architecture/), that minimizes attack surfaces, even for internal threats. 1. Define a code review process that considers security concerns. 1. Build a \_threat model\_ of your system or application that identifies trust boundaries. Use that threat model to identify risks and determine how to treat them. 1. Incorporate advanced security automation, such as \_fuzzing\_ and [security chaos engineering](https://glossary.cncf.io/security-chaos-engineering/), where it's justified. ## \_Distribute\_ lifecycle phase {#lifecycle-phase-distribute} - Ensure the security of the supply chain for container images you execute. - Ensure the security of the supply chain for the cluster and other components that execute your application. For example, this might include an external database that your cloud native application uses for persistence. To achieve this, you can: 1. Scan container images and other artifacts for known vulnerabilities. 1. Ensure that software distribution uses encryption in transit, with a chain of trust for the software source. 1. Adopt and follow processes to update dependencies when updates are available, especially in response to security announcements. 1. Use validation mechanisms such as digital certificates for supply chain assurance. 1. Subscribe to feeds and other mechanisms to alert you to security risks. 1. Restrict access to artifacts. Place container images in a [private registry](/docs/concepts/containers/images/#using-a-private-registry) that only allows authorized clients to pull images. ## \_Deploy\_ lifecycle phase {#lifecycle-phase-deploy} Ensure appropriate restrictions on what can be deployed, who can deploy it, and where it can be deployed. You can enforce measures from the \_distribute\_ phase, such as verifying the cryptographic identity of container image artifacts. You can deploy different applications and cluster components into different {{< glossary\_tooltip text="namespaces" term\_id="namespace" >}}. Containers and namespaces both provide isolation mechanisms that are relevant to information security. When you deploy Kubernetes, you also set the foundation for your applications' runtime environment: a Kubernetes cluster (or multiple clusters). That infrastructure must provide the security guarantees that higher layers expect. ## \_Runtime\_ lifecycle phase {#lifecycle-phase-runtime} The Runtime phase comprises three critical areas: [access](#protection-runtime-access), [compute](#protection-runtime-compute), and [storage](#protection-runtime-storage). ### Runtime protection: access {#protection-runtime-access} The Kubernetes API is what makes your cluster work. Protecting this API is key to providing effective cluster security. Other pages in the Kubernetes documentation have more detail about how to set up specific aspects of access control. The [security checklist](/docs/concepts/security/security-checklist/) provides suggested basic checks for your cluster. Beyond that, securing your cluster means implementing effective [authentication](/docs/concepts/security/controlling-access/#authentication) and [authorization](/docs/concepts/security/controlling-access/#authorization) for API access. Use [ServiceAccounts](/docs/concepts/security/service-accounts/) to provide and manage security identities for workloads and cluster components. Kubernetes uses TLS to protect API traffic; make sure to deploy the cluster using TLS (including for traffic between nodes and the control plane) and protect the encryption keys. If you use Kubernetes' own API for [CertificateSigningRequests](/docs/reference/access-authn-authz/certificate-signing-requests/#certificate-signing-requests), pay special attention to restricting misuse there. ### Runtime protection: compute {#protection-runtime-compute} {{<
| null |
./vendor/kubernetes/content/en/docs/concepts/security/cloud-native-security.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/cloud-native-security.md
|
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] | 0.14623
|
Kubernetes uses TLS to protect API traffic; make sure to deploy the cluster using TLS (including for traffic between nodes and the control plane) and protect the encryption keys. If you use Kubernetes' own API for [CertificateSigningRequests](/docs/reference/access-authn-authz/certificate-signing-requests/#certificate-signing-requests), pay special attention to restricting misuse there. ### Runtime protection: compute {#protection-runtime-compute} {{< glossary\_tooltip text="Containers" term\_id="container" >}} provide two things: isolation between applications and a mechanism to combine those isolated applications to run on the same host computer. Those two aspects—isolation and aggregation—mean that runtime security involves identifying trade-offs and finding an appropriate balance. Kubernetes relies on a {{< glossary\_tooltip text="container runtime" term\_id="container-runtime" >}} to set up and run containers. The Kubernetes project does not recommend a specific container runtime, and you should make sure that the runtime(s) you choose meet your information security needs. To protect your compute at runtime, you can: 1. Enforce [Pod Security Standards](/docs/concepts/security/pod-security-standards/) for applications to help ensure they run with only the necessary privileges. 1. Run a specialized operating system on your nodes that is designed specifically for running containerized workloads. This is typically based on a read-only operating system (\_immutable image\_) that provides only the services essential for running containers. Container-specific operating systems help isolate system components and present a reduced attack surface in case of a container escape. 1. Define [ResourceQuotas](/docs/concepts/policy/resource-quotas/) to fairly allocate shared resources, and use mechanisms such as [LimitRanges](/docs/concepts/policy/limit-range/) to ensure that Pods specify their resource requirements. 1. Partition workloads across different nodes to improve isolation. Use [node isolation](/docs/concepts/scheduling-eviction/assign-pod-node/#node-isolation-restriction) mechanisms, either from Kubernetes itself or from the ecosystem, to ensure that Pods with different trust contexts run on separate sets of nodes. 1. Use a {{< glossary\_tooltip text="container runtime" term\_id="container-runtime" >}} that provides security restrictions. 1. On Linux nodes, use a Linux security module such as [AppArmor](/docs/tutorials/security/apparmor/) or [seccomp](/docs/tutorials/security/seccomp/). ### Runtime protection: storage {#protection-runtime-storage} To protect storage for your cluster and the applications that run there, you can: 1. Integrate your cluster with an external storage plugin that provides encryption at rest for volumes. 1. Enable [encryption at rest](/docs/tasks/administer-cluster/encrypt-data/) for API objects. 1. Protect data durability using backups, and verify that you can restore them whenever needed. 1. Authenticate connections between cluster nodes and any network storage they rely upon. 1. Implement data encryption within your own application. For encryption keys, generating these within specialized hardware provides the best protection against disclosure risks. A \_hardware security module\_ can let you perform cryptographic operations without allowing the security key to be copied elsewhere. ### Networking and security You should also consider network security measures, such as [NetworkPolicy](/docs/concepts/services-networking/network-policies/) or a [service mesh](https://glossary.cncf.io/service-mesh/). Some network plugins for Kubernetes provide encryption for your cluster network using technologies such as a virtual private network (VPN) overlay. By design, Kubernetes lets you use your own networking plugin for your cluster. If you use managed Kubernetes, the provider may have already selected a network plugin for you. The network plugin you choose and the way you integrate it can have a strong impact on the security of information in transit. ### Observability and runtime security Kubernetes lets you extend your cluster with extra tooling. You can set up third party solutions to help you monitor or troubleshoot your applications and the clusters they are running. You also get some basic observability features built in to Kubernetes itself. Your code running in containers can generate logs, publish metrics, or provide other observability data; at deploy time, you need to make sure your cluster provides an appropriate level of protection there. If you set up a metrics dashboard or something similar, review the chain of components that populate data into that
| null |
./vendor/kubernetes/content/en/docs/concepts/security/cloud-native-security.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/cloud-native-security.md
|
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] | 0.0796
|
running in containers can generate logs, publish metrics, or provide other observability data; at deploy time, you need to make sure your cluster provides an appropriate level of protection there. If you set up a metrics dashboard or something similar, review the chain of components that populate data into that dashboard, as well as the dashboard itself. Make sure that the whole chain is designed with enough resilience and integrity protection that you can rely on it even during an incident where your cluster might be degraded. Where appropriate, deploy security measures below the Kubernetes layer, such as cryptographically measured boot or authenticated distribution of time (which helps ensure the fidelity of logs and audit records). For a high-assurance environment, deploy cryptographic protections to ensure that logs are both tamper-proof and confidential. ## {{% heading "whatsnext" %}} ### Cloud native security {#further-reading-cloud-native} \* CNCF [white paper](https://github.com/cncf/tag-security/blob/main/community/resources/security-whitepaper/v2/CNCF\_cloud-native-security-whitepaper-May2022-v2.pdf) on cloud native security. \* CNCF [white paper](https://github.com/cncf/tag-security/blob/f80844baaea22a358f5b20dca52cd6f72a32b066/supply-chain-security/supply-chain-security-paper/CNCF\_SSCP\_v1.pdf) on good practices for securing a software supply chain. \* [Fixing the Kubernetes clusterf\\*\\*k: Understanding security from the kernel up](https://archive.fosdem.org/2020/schedule/event/kubernetes/) (FOSDEM 2020) \* [Kubernetes Security Best Practices](https://www.youtube.com/watch?v=wqsUfvRyYpw) (Kubernetes Forum Seoul 2019) \* [Towards Measured Boot Out of the Box](https://www.youtube.com/watch?v=EzSkU3Oecuw) (Linux Security Summit 2016) ### Kubernetes and information security {#further-reading-k8s} \* [Kubernetes security](/docs/concepts/security/) \* [Securing your cluster](/docs/tasks/administer-cluster/securing-a-cluster/) \* [Data encryption in transit](/docs/tasks/tls/managing-tls-in-a-cluster/) for the control plane \* [Data encryption at rest](/docs/tasks/administer-cluster/encrypt-data/) \* [Secrets in Kubernetes](/docs/concepts/configuration/secret/) \* [Controlling Access to the Kubernetes API](/docs/concepts/security/controlling-access) \* [Network policies](/docs/concepts/services-networking/network-policies/) for Pods \* [Pod security standards](/docs/concepts/security/pod-security-standards/) \* [RuntimeClasses](/docs/concepts/containers/runtime-class)
| null |
./vendor/kubernetes/content/en/docs/concepts/security/cloud-native-security.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/cloud-native-security.md
|
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|
This page introduces the ServiceAccount object in Kubernetes, providing information about how service accounts work, use cases, limitations, alternatives, and links to resources for additional guidance. ## What are service accounts? {#what-are-service-accounts} A service account is a type of non-human account that, in Kubernetes, provides a distinct identity in a Kubernetes cluster. Application Pods, system components, and entities inside and outside the cluster can use a specific ServiceAccount's credentials to identify as that ServiceAccount. This identity is useful in various situations, including authenticating to the API server or implementing identity-based security policies. Service accounts exist as ServiceAccount objects in the API server. Service accounts have the following properties: \* \*\*Namespaced:\*\* Each service account is bound to a Kubernetes {{}}. Every namespace gets a [`default` ServiceAccount](#default-service-accounts) upon creation. \* \*\*Lightweight:\*\* Service accounts exist in the cluster and are defined in the Kubernetes API. You can quickly create service accounts to enable specific tasks. \* \*\*Portable:\*\* A configuration bundle for a complex containerized workload might include service account definitions for the system's components. The lightweight nature of service accounts and the namespaced identities make the configurations portable. Service accounts are different from user accounts, which are authenticated human users in the cluster. By default, user accounts don't exist in the Kubernetes API server; instead, the API server treats user identities as opaque data. You can authenticate as a user account using multiple methods. Some Kubernetes distributions might add custom extension APIs to represent user accounts in the API server. {{< table caption="Comparison between service accounts and users" >}} | Description | ServiceAccount | User or group | | --- | --- | --- | | Location | Kubernetes API (ServiceAccount object) | External | | Access control | Kubernetes RBAC or other [authorization mechanisms](/docs/reference/access-authn-authz/authorization/#authorization-modules) | Kubernetes RBAC or other identity and access management mechanisms | | Intended use | Workloads, automation | People | {{< /table >}} ### Default service accounts {#default-service-accounts} When you create a cluster, Kubernetes automatically creates a ServiceAccount object named `default` for every namespace in your cluster. The `default` service accounts in each namespace get no permissions by default other than the [default API discovery permissions](/docs/reference/access-authn-authz/rbac/#default-roles-and-role-bindings) that Kubernetes grants to all authenticated principals if role-based access control (RBAC) is enabled. If you delete the `default` ServiceAccount object in a namespace, the {{< glossary\_tooltip text="control plane" term\_id="control-plane" >}} replaces it with a new one. If you deploy a Pod in a namespace, and you don't [manually assign a ServiceAccount to the Pod](#assign-to-pod), Kubernetes assigns the `default` ServiceAccount for that namespace to the Pod. ## Use cases for Kubernetes service accounts {#use-cases} As a general guideline, you can use service accounts to provide identities in the following scenarios: \* Your Pods need to communicate with the Kubernetes API server, for example in situations such as the following: \* Providing read-only access to sensitive information stored in Secrets. \* Granting [cross-namespace access](#cross-namespace), such as allowing a Pod in namespace `example` to read, list, and watch for Lease objects in the `kube-node-lease` namespace. \* Your Pods need to communicate with an external service. For example, a workload Pod requires an identity for a commercially available cloud API, and the commercial provider allows configuring a suitable trust relationship. \* [Authenticating to a private image registry using an `imagePullSecret`](/docs/tasks/configure-pod-container/configure-service-account/#add-imagepullsecrets-to-a-service-account). \* An external service needs to communicate with the Kubernetes API server. For example, authenticating to the cluster as part of a CI/CD pipeline. \* You use third-party security software in your cluster that relies on the ServiceAccount identity of different Pods to group those Pods into different contexts. ## How to use service accounts
| null |
./vendor/kubernetes/content/en/docs/concepts/security/service-accounts.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/service-accounts.md
|
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] | 0.202876
|
to communicate with the Kubernetes API server. For example, authenticating to the cluster as part of a CI/CD pipeline. \* You use third-party security software in your cluster that relies on the ServiceAccount identity of different Pods to group those Pods into different contexts. ## How to use service accounts {#how-to-use} To use a Kubernetes service account, you do the following: 1. Create a ServiceAccount object using a Kubernetes client like `kubectl` or a manifest that defines the object. 1. Grant permissions to the ServiceAccount object using an authorization mechanism such as [RBAC](/docs/reference/access-authn-authz/rbac/). 1. Assign the ServiceAccount object to Pods during Pod creation. If you're using the identity from an external service, [retrieve the ServiceAccount token](#get-a-token) and use it from that service instead. For instructions, refer to [Configure Service Accounts for Pods](/docs/tasks/configure-pod-container/configure-service-account/). ### Grant permissions to a ServiceAccount {#grant-permissions} You can use the built-in Kubernetes [role-based access control (RBAC)](/docs/reference/access-authn-authz/rbac/) mechanism to grant the minimum permissions required by each service account. You create a \*role\*, which grants access, and then \*bind\* the role to your ServiceAccount. RBAC lets you define a minimum set of permissions so that the service account permissions follow the principle of least privilege. Pods that use that service account don't get more permissions than are required to function correctly. For instructions, refer to [ServiceAccount permissions](/docs/reference/access-authn-authz/rbac/#service-account-permissions). #### Cross-namespace access using a ServiceAccount {#cross-namespace} You can use RBAC to allow service accounts in one namespace to perform actions on resources in a different namespace in the cluster. For example, consider a scenario where you have a service account and Pod in the `dev` namespace and you want your Pod to see Jobs running in the `maintenance` namespace. You could create a Role object that grants permissions to list Job objects. Then, you'd create a RoleBinding object in the `maintenance` namespace to bind the Role to the ServiceAccount object. Now, Pods in the `dev` namespace can list Job objects in the `maintenance` namespace using that service account. ### Assign a ServiceAccount to a Pod {#assign-to-pod} To assign a ServiceAccount to a Pod, you set the `spec.serviceAccountName` field in the Pod specification. Kubernetes then automatically provides the credentials for that ServiceAccount to the Pod. In v1.22 and later, Kubernetes gets a short-lived, \*\*automatically rotating\*\* token using the `TokenRequest` API and mounts the token as a [projected volume](/docs/concepts/storage/projected-volumes/#serviceaccounttoken). By default, Kubernetes provides the Pod with the credentials for an assigned ServiceAccount, whether that is the `default` ServiceAccount or a custom ServiceAccount that you specify. To prevent Kubernetes from automatically injecting credentials for a specified ServiceAccount or the `default` ServiceAccount, set the `automountServiceAccountToken` field in your Pod specification to `false`. In versions earlier than 1.22, Kubernetes provides a long-lived, static token to the Pod as a Secret. #### Manually retrieve ServiceAccount credentials {#get-a-token} If you need the credentials for a ServiceAccount to mount in a non-standard location, or for an audience that isn't the API server, use one of the following methods: \* [TokenRequest API](/docs/reference/kubernetes-api/authentication-resources/token-request-v1/) (recommended): Request a short-lived service account token from within your own \*application code\*. The token expires automatically and can rotate upon expiration. If you have a legacy application that is not aware of Kubernetes, you could use a sidecar container within the same pod to fetch these tokens and make them available to the application workload. \* [Token Volume Projection](/docs/tasks/configure-pod-container/configure-service-account/#serviceaccount-token-volume-projection) (also recommended): In Kubernetes v1.20 and later, use the Pod specification to tell the kubelet to add the service account token to the Pod as a \*projected volume\*. Projected tokens expire automatically, and the kubelet rotates the token before it expires. \* [Service Account Token Secrets](/docs/tasks/configure-pod-container/configure-service-account/#manually-create-an-api-token-for-a-serviceaccount) (not recommended):
| null |
./vendor/kubernetes/content/en/docs/concepts/security/service-accounts.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/service-accounts.md
|
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] | 0.203425
|
Volume Projection](/docs/tasks/configure-pod-container/configure-service-account/#serviceaccount-token-volume-projection) (also recommended): In Kubernetes v1.20 and later, use the Pod specification to tell the kubelet to add the service account token to the Pod as a \*projected volume\*. Projected tokens expire automatically, and the kubelet rotates the token before it expires. \* [Service Account Token Secrets](/docs/tasks/configure-pod-container/configure-service-account/#manually-create-an-api-token-for-a-serviceaccount) (not recommended): You can mount service account tokens as Kubernetes Secrets in Pods. These tokens don't expire and don't rotate. In versions prior to v1.24, a permanent token was automatically created for each service account. This method is not recommended anymore, especially at scale, because of the risks associated with static, long-lived credentials. The [LegacyServiceAccountTokenNoAutoGeneration feature gate](/docs/reference/command-line-tools-reference/feature-gates-removed) (which was enabled by default from Kubernetes v1.24 to v1.26), prevented Kubernetes from automatically creating these tokens for ServiceAccounts. The feature gate is removed in v1.27, because it was elevated to GA status; you can still create indefinite service account tokens manually, but should take into account the security implications. {{< note >}} For applications running outside your Kubernetes cluster, you might be considering creating a long-lived ServiceAccount token that is stored in a Secret. This allows authentication, but the Kubernetes project recommends you avoid this approach. Long-lived bearer tokens represent a security risk as, once disclosed, the token can be misused. Instead, consider using an alternative. For example, your external application can authenticate using a well-protected private key `and` a certificate, or using a custom mechanism such as an [authentication webhook](/docs/reference/access-authn-authz/authentication/#webhook-token-authentication) that you implement yourself. You can also use TokenRequest to obtain short-lived tokens for your external application. {{< /note >}} ### Restricting access to Secrets (deprecated) {#enforce-mountable-secrets} {{< feature-state for\_k8s\_version="v1.32" state="deprecated" >}} {{< note >}} `kubernetes.io/enforce-mountable-secrets` is deprecated since Kubernetes v1.32. Use separate namespaces to isolate access to mounted secrets. {{< /note >}} Kubernetes provides an annotation called `kubernetes.io/enforce-mountable-secrets` that you can add to your ServiceAccounts. When this annotation is applied, the ServiceAccount's secrets can only be mounted on specified types of resources, enhancing the security posture of your cluster. You can add the annotation to a ServiceAccount using a manifest: ```yaml apiVersion: v1 kind: ServiceAccount metadata: annotations: kubernetes.io/enforce-mountable-secrets: "true" name: my-serviceaccount namespace: my-namespace ``` When this annotation is set to "true", the Kubernetes control plane ensures that the Secrets from this ServiceAccount are subject to certain mounting restrictions. 1. The name of each Secret that is mounted as a volume in a Pod must appear in the `secrets` field of the Pod's ServiceAccount. 1. The name of each Secret referenced using `envFrom` in a Pod must also appear in the `secrets` field of the Pod's ServiceAccount. 1. The name of each Secret referenced using `imagePullSecrets` in a Pod must also appear in the `secrets` field of the Pod's ServiceAccount. By understanding and enforcing these restrictions, cluster administrators can maintain a tighter security profile and ensure that secrets are accessed only by the appropriate resources. ## Authenticating service account credentials {#authenticating-credentials} ServiceAccounts use signed {{}} (JWTs) to authenticate to the Kubernetes API server, and to any other system where a trust relationship exists. Depending on how the token was issued (either time-limited using a `TokenRequest` or using a legacy mechanism with a Secret), a ServiceAccount token might also have an expiry time, an audience, and a time after which the token \*starts\* being valid. When a client that is acting as a ServiceAccount tries to communicate with the Kubernetes API server, the client includes an `Authorization: Bearer ` header with the HTTP request. The API server checks the validity of that bearer token as follows: 1. Checks the token signature. 1. Checks whether the token has expired. 1. Checks whether object references in
| null |
./vendor/kubernetes/content/en/docs/concepts/security/service-accounts.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/service-accounts.md
|
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] | 0.138375
|
tries to communicate with the Kubernetes API server, the client includes an `Authorization: Bearer ` header with the HTTP request. The API server checks the validity of that bearer token as follows: 1. Checks the token signature. 1. Checks whether the token has expired. 1. Checks whether object references in the token claims are currently valid. 1. Checks whether the token is currently valid. 1. Checks the audience claims. The TokenRequest API produces \_bound tokens\_ for a ServiceAccount. This binding is linked to the lifetime of the client, such as a Pod, that is acting as that ServiceAccount. See [Token Volume Projection](/docs/tasks/configure-pod-container/configure-service-account/#serviceaccount-token-volume-projection) for an example of a bound pod service account token's JWT schema and payload. For tokens issued using the `TokenRequest` API, the API server also checks that the specific object reference that is using the ServiceAccount still exists, matching by the {{< glossary\_tooltip term\_id="uid" text="unique ID" >}} of that object. For legacy tokens that are mounted as Secrets in Pods, the API server checks the token against the Secret. For more information about the authentication process, refer to [Authentication](/docs/reference/access-authn-authz/authentication/#service-account-tokens). ### Authenticating service account credentials in your own code {#authenticating-in-code} If you have services of your own that need to validate Kubernetes service account credentials, you can use the following methods: \* [TokenReview API](/docs/reference/kubernetes-api/authentication-resources/token-review-v1/) (recommended) \* OIDC discovery The Kubernetes project recommends that you use the TokenReview API, because this method invalidates tokens that are bound to API objects such as Secrets, ServiceAccounts, Pods or Nodes when those objects are deleted. For example, if you delete the Pod that contains a projected ServiceAccount token, the cluster invalidates that token immediately and a TokenReview immediately fails. If you use OIDC validation instead, your clients continue to treat the token as valid until the token reaches its expiration timestamp. Your application should always define the audience that it accepts, and should check that the token's audiences match the audiences that the application expects. This helps to minimize the scope of the token so that it can only be used in your application and nowhere else. ## Alternatives \* Issue your own tokens using another mechanism, and then use [Webhook Token Authentication](/docs/reference/access-authn-authz/authentication/#webhook-token-authentication) to validate bearer tokens using your own validation service. \* Provide your own identities to Pods. \* [Use the SPIFFE CSI driver plugin to provide SPIFFE SVIDs as X.509 certificate pairs to Pods](https://cert-manager.io/docs/projects/csi-driver-spiffe/). {{% thirdparty-content single="true" %}} \* [Use a service mesh such as Istio to provide certificates to Pods](https://istio.io/latest/docs/tasks/security/cert-management/plugin-ca-cert/). \* Authenticate from outside the cluster to the API server without using service account tokens: \* [Configure the API server to accept OpenID Connect (OIDC) tokens from your identity provider](/docs/reference/access-authn-authz/authentication/#openid-connect-tokens). \* Use service accounts or user accounts created using an external Identity and Access Management (IAM) service, such as from a cloud provider, to authenticate to your cluster. \* [Use the CertificateSigningRequest API with client certificates](/docs/tasks/tls/managing-tls-in-a-cluster/). \* [Configure the kubelet to retrieve credentials from an image registry](/docs/tasks/administer-cluster/kubelet-credential-provider/). \* Use a Device Plugin to access a virtual Trusted Platform Module (TPM), which then allows authentication using a private key. ## {{% heading "whatsnext" %}} \* Learn how to [manage your ServiceAccounts as a cluster administrator](/docs/reference/access-authn-authz/service-accounts-admin/). \* Learn how to [assign a ServiceAccount to a Pod](/docs/tasks/configure-pod-container/configure-service-account/). \* Read the [ServiceAccount API reference](/docs/reference/kubernetes-api/authentication-resources/service-account-v1/).
| null |
./vendor/kubernetes/content/en/docs/concepts/security/service-accounts.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/service-accounts.md
|
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] | 0.164566
|
{{}} The following good practices are intended for both cluster administrators and application developers. Use these guidelines to improve the security of your sensitive information in Secret objects, as well as to more effectively manage your Secrets. ## Cluster administrators This section provides good practices that cluster administrators can use to improve the security of confidential information in the cluster. ### Configure encryption at rest By default, Secret objects are stored unencrypted in {{}}. You should configure encryption of your Secret data in `etcd`. For instructions, refer to [Encrypt Secret Data at Rest](/docs/tasks/administer-cluster/encrypt-data/). ### Configure least-privilege access to Secrets {#least-privilege-secrets} When planning your access control mechanism, such as Kubernetes {{}} [(RBAC)](/docs/reference/access-authn-authz/rbac/), consider the following guidelines for access to `Secret` objects. You should also follow the other guidelines in [RBAC good practices](/docs/concepts/security/rbac-good-practices). - \*\*Components\*\*: Restrict `watch` or `list` access to only the most privileged, system-level components. Only grant `get` access for Secrets if the component's normal behavior requires it. - \*\*Humans\*\*: Restrict `get`, `watch`, or `list` access to Secrets. Only allow cluster administrators to access `etcd`. This includes read-only access. For more complex access control, such as restricting access to Secrets with specific annotations, consider using third-party authorization mechanisms. {{< caution >}} Granting `list` access to Secrets implicitly lets the subject fetch the contents of the Secrets. {{< /caution >}} A user who can create a Pod that uses a Secret can also see the value of that Secret. Even if cluster policies do not allow a user to read the Secret directly, the same user could have access to run a Pod that then exposes the Secret. You can detect or limit the impact caused by Secret data being exposed, either intentionally or unintentionally, by a user with this access. Some recommendations include: \* Use short-lived Secrets \* Implement audit rules that alert on specific events, such as concurrent reading of multiple Secrets by a single user #### Restrict Access for Secrets Use separate namespaces to isolate access to mounted secrets. ### Improve etcd management policies Consider wiping or shredding the durable storage used by `etcd` once it is no longer in use. If there are multiple `etcd` instances, configure encrypted SSL/TLS communication between the instances to protect the Secret data in transit. ### Configure access to external Secrets {{% thirdparty-content %}} You can use third-party Secrets store providers to keep your confidential data outside your cluster and then configure Pods to access that information. The [Kubernetes Secrets Store CSI Driver](https://secrets-store-csi-driver.sigs.k8s.io/) is a DaemonSet that lets the kubelet retrieve Secrets from external stores, and mount the Secrets as a volume into specific Pods that you authorize to access the data. For a list of supported providers, refer to [Providers for the Secret Store CSI Driver](https://secrets-store-csi-driver.sigs.k8s.io/concepts.html#provider-for-the-secrets-store-csi-driver). ## Good practices for using swap memory For best practices for setting swap memory for Linux nodes, please refer to [swap memory management](/docs/concepts/cluster-administration/swap-memory-management/#good-practice-for-using-swap-in-a-kubernetes-cluster). ## Developers This section provides good practices for developers to use to improve the security of confidential data when building and deploying Kubernetes resources. ### Restrict Secret access to specific containers If you are defining multiple containers in a Pod, and only one of those containers needs access to a Secret, define the volume mount or environment variable configuration so that the other containers do not have access to that Secret. ### Protect Secret data after reading Applications still need to protect the value of confidential information after reading it from an environment variable or volume. For example, your application must avoid logging the secret data in the clear or transmitting it to an untrusted party. ### Avoid sharing Secret manifests If
| null |
./vendor/kubernetes/content/en/docs/concepts/security/secrets-good-practices.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/secrets-good-practices.md
|
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] | 0.08546
|
Protect Secret data after reading Applications still need to protect the value of confidential information after reading it from an environment variable or volume. For example, your application must avoid logging the secret data in the clear or transmitting it to an untrusted party. ### Avoid sharing Secret manifests If you configure a Secret through a {{< glossary\_tooltip text="manifest" term\_id="manifest" >}}, with the secret data encoded as base64, sharing this file or checking it in to a source repository means the secret is available to everyone who can read the manifest. {{< caution >}} Base64 encoding is \_not\_ an encryption method, it provides no additional confidentiality over plain text. {{< /caution >}}
| null |
./vendor/kubernetes/content/en/docs/concepts/security/secrets-good-practices.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/secrets-good-practices.md
|
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|
The Kubernetes API server is the main point of entry to a cluster for external parties (users and services) interacting with it. As part of this role, the API server has several key built-in security controls, such as audit logging and {{< glossary\_tooltip text="admission controllers" term\_id="admission-controller" >}}. However, there are ways to modify the configuration or content of the cluster that bypass these controls. This page describes the ways in which the security controls built into the Kubernetes API server can be bypassed, so that cluster operators and security architects can ensure that these bypasses are appropriately restricted. ## Static Pods {#static-pods} The {{< glossary\_tooltip text="kubelet" term\_id="kubelet" >}} on each node loads and directly manages any manifests that are stored in a named directory or fetched from a specific URL as [\*static Pods\*](/docs/tasks/configure-pod-container/static-pod) in your cluster. The API server doesn't manage these static Pods. An attacker with write access to this location could modify the configuration of static pods loaded from that source, or could introduce new static Pods. Static Pods are restricted from accessing other objects in the Kubernetes API. For example, you can't configure a static Pod to mount a Secret from the cluster. However, these Pods can take other security sensitive actions, such as using `hostPath` mounts from the underlying node. By default, the kubelet creates a {{< glossary\_tooltip text="mirror pod" term\_id="mirror-pod">}} so that the static Pods are visible in the Kubernetes API. However, if the attacker uses an invalid namespace name when creating the Pod, it will not be visible in the Kubernetes API and can only be discovered by tooling that has access to the affected host(s). If a static Pod fails admission control, the kubelet won't register the Pod with the API server. However, the Pod still runs on the node. For more information, refer to [kubeadm issue #1541](https://github.com/kubernetes/kubeadm/issues/1541#issuecomment-487331701). ### Mitigations {#static-pods-mitigations} - Only [enable the kubelet static Pod manifest functionality](/docs/tasks/configure-pod-container/static-pod/#static-pod-creation) if required by the node. - If a node uses the static Pod functionality, restrict filesystem access to the static Pod manifest directory or URL to users who need the access. - Restrict access to kubelet configuration parameters and files to prevent an attacker setting a static Pod path or URL. - Regularly audit and centrally report all access to directories or web storage locations that host static Pod manifests and kubelet configuration files. ## The kubelet API {#kubelet-api} The kubelet provides an HTTP API that is typically exposed on TCP port 10250 on cluster worker nodes. The API might also be exposed on control plane nodes depending on the Kubernetes distribution in use. Direct access to the API allows for disclosure of information about the pods running on a node, the logs from those pods, and execution of commands in every container running on the node. When Kubernetes cluster users have RBAC access to `Node` object sub-resources, that access serves as authorization to interact with the kubelet API. The exact access depends on which sub-resource access has been granted, as detailed in [kubelet authorization](/docs/reference/access-authn-authz/kubelet-authn-authz/#kubelet-authorization). Direct access to the kubelet API is not subject to admission control and is not logged by Kubernetes audit logging. An attacker with direct access to this API may be able to bypass controls that detect or prevent certain actions. The kubelet API can be configured to authenticate requests in a number of ways. By default, the kubelet configuration allows anonymous access. Most Kubernetes providers change the default to use webhook and certificate authentication. This lets the control plane ensure that the caller is authorized to access the `nodes` API resource or sub-resources. The default anonymous access doesn't
| null |
./vendor/kubernetes/content/en/docs/concepts/security/api-server-bypass-risks.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/api-server-bypass-risks.md
|
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] | 0.202146
|
requests in a number of ways. By default, the kubelet configuration allows anonymous access. Most Kubernetes providers change the default to use webhook and certificate authentication. This lets the control plane ensure that the caller is authorized to access the `nodes` API resource or sub-resources. The default anonymous access doesn't make this assertion with the control plane. ### Mitigations - Restrict access to sub-resources of the `nodes` API object using mechanisms such as [RBAC](/docs/reference/access-authn-authz/rbac/). Only grant this access when required, such as by monitoring services. - Restrict access to the kubelet port. Only allow specified and trusted IP address ranges to access the port. - Ensure that [kubelet authentication](/docs/reference/access-authn-authz/kubelet-authn-authz/#kubelet-authentication). is set to webhook or certificate mode. - Ensure that the unauthenticated "read-only" Kubelet port is not enabled on the cluster. ## The etcd API Kubernetes clusters use etcd as a datastore. The `etcd` service listens on TCP port 2379. The only clients that need access are the Kubernetes API server and any backup tooling that you use. Direct access to this API allows for disclosure or modification of any data held in the cluster. Access to the etcd API is typically managed by client certificate authentication. Any certificate issued by a certificate authority that etcd trusts allows full access to the data stored inside etcd. Direct access to etcd is not subject to Kubernetes admission control and is not logged by Kubernetes audit logging. An attacker who has read access to the API server's etcd client certificate private key (or can create a new trusted client certificate) can gain cluster admin rights by accessing cluster secrets or modifying access rules. Even without elevating their Kubernetes RBAC privileges, an attacker who can modify etcd can retrieve any API object or create new workloads inside the cluster. Many Kubernetes providers configure etcd to use mutual TLS (both client and server verify each other's certificate for authentication). There is no widely accepted implementation of authorization for the etcd API, although the feature exists. Since there is no authorization model, any certificate with client access to etcd can be used to gain full access to etcd. Typically, etcd client certificates that are only used for health checking can also grant full read and write access. ### Mitigations {#etcd-api-mitigations} - Ensure that the certificate authority trusted by etcd is used only for the purposes of authentication to that service. - Control access to the private key for the etcd server certificate, and to the API server's client certificate and key. - Consider restricting access to the etcd port at a network level, to only allow access from specified and trusted IP address ranges. ## Container runtime socket {#runtime-socket} On each node in a Kubernetes cluster, access to interact with containers is controlled by the container runtime (or runtimes, if you have configured more than one). Typically, the container runtime exposes a Unix socket that the kubelet can access. An attacker with access to this socket can launch new containers or interact with running containers. At the cluster level, the impact of this access depends on whether the containers that run on the compromised node have access to Secrets or other confidential data that an attacker could use to escalate privileges to other worker nodes or to control plane components. ### Mitigations {#runtime-socket-mitigations} - Ensure that you tightly control filesystem access to container runtime sockets. When possible, restrict this access to the `root` user. - Isolate the kubelet from other components running on the node, using mechanisms such as Linux kernel namespaces. - Ensure that you restrict or forbid the use of [`hostPath` mounts](/docs/concepts/storage/volumes/#hostpath) that include
| null |
./vendor/kubernetes/content/en/docs/concepts/security/api-server-bypass-risks.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/api-server-bypass-risks.md
|
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] | 0.123323
|
you tightly control filesystem access to container runtime sockets. When possible, restrict this access to the `root` user. - Isolate the kubelet from other components running on the node, using mechanisms such as Linux kernel namespaces. - Ensure that you restrict or forbid the use of [`hostPath` mounts](/docs/concepts/storage/volumes/#hostpath) that include the container runtime socket, either directly or by mounting a parent directory. Also `hostPath` mounts must be set as read-only to mitigate risks of attackers bypassing directory restrictions. - Restrict user access to nodes, and especially restrict superuser access to nodes.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/api-server-bypass-risks.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/api-server-bypass-risks.md
|
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|
This page provides an overview of available configuration options and best practices for cluster multi-tenancy. Sharing clusters saves costs and simplifies administration. However, sharing clusters also presents challenges such as security, fairness, and managing \_noisy neighbors\_. Clusters can be shared in many ways. In some cases, different applications may run in the same cluster. In other cases, multiple instances of the same application may run in the same cluster, one for each end user. All these types of sharing are frequently described using the umbrella term \_multi-tenancy\_. While Kubernetes does not have first-class concepts of end users or tenants, it provides several features to help manage different tenancy requirements. These are discussed below. ## Use cases The first step to determining how to share your cluster is understanding your use case, so you can evaluate the patterns and tools available. In general, multi-tenancy in Kubernetes clusters falls into two broad categories, though many variations and hybrids are also possible. ### Multiple teams A common form of multi-tenancy is to share a cluster between multiple teams within an organization, each of whom may operate one or more workloads. These workloads frequently need to communicate with each other, and with other workloads located on the same or different clusters. In this scenario, members of the teams often have direct access to Kubernetes resources via tools such as `kubectl`, or indirect access through GitOps controllers or other types of release automation tools. There is often some level of trust between members of different teams, but Kubernetes policies such as RBAC, quotas, and network policies are essential to safely and fairly share clusters. ### Multiple customers The other major form of multi-tenancy frequently involves a Software-as-a-Service (SaaS) vendor running multiple instances of a workload for customers. This business model is so strongly associated with this deployment style that many people call it "SaaS tenancy." However, a better term might be "multi-customer tenancy," since SaaS vendors may also use other deployment models, and this deployment model can also be used outside of SaaS. In this scenario, the customers do not have access to the cluster; Kubernetes is invisible from their perspective and is only used by the vendor to manage the workloads. Cost optimization is frequently a critical concern, and Kubernetes policies are used to ensure that the workloads are strongly isolated from each other. ## Terminology ### Tenants When discussing multi-tenancy in Kubernetes, there is no single definition for a "tenant". Rather, the definition of a tenant will vary depending on whether multi-team or multi-customer tenancy is being discussed. In multi-team usage, a tenant is typically a team, where each team typically deploys a small number of workloads that scales with the complexity of the service. However, the definition of "team" may itself be fuzzy, as teams may be organized into higher-level divisions or subdivided into smaller teams. By contrast, if each team deploys dedicated workloads for each new client, they are using a multi-customer model of tenancy. In this case, a "tenant" is simply a group of users who share a single workload. This may be as large as an entire company, or as small as a single team at that company. In many cases, the same organization may use both definitions of "tenants" in different contexts. For example, a platform team may offer shared services such as security tools and databases to multiple internal “customers” and a SaaS vendor may also have multiple teams sharing a development cluster. Finally, hybrid architectures are also possible, such as a SaaS provider using a combination of per-customer workloads for sensitive data, combined with multi-tenant shared
| null |
./vendor/kubernetes/content/en/docs/concepts/security/multi-tenancy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/multi-tenancy.md
|
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offer shared services such as security tools and databases to multiple internal “customers” and a SaaS vendor may also have multiple teams sharing a development cluster. Finally, hybrid architectures are also possible, such as a SaaS provider using a combination of per-customer workloads for sensitive data, combined with multi-tenant shared services. {{< figure src="/images/docs/multi-tenancy.png" title="A cluster showing coexisting tenancy models" class="diagram-large" >}} ### Isolation There are several ways to design and build multi-tenant solutions with Kubernetes. Each of these methods comes with its own set of tradeoffs that impact the isolation level, implementation effort, operational complexity, and cost of service. A Kubernetes cluster consists of a control plane which runs Kubernetes software, and a data plane consisting of worker nodes where tenant workloads are executed as pods. Tenant isolation can be applied in both the control plane and the data plane based on organizational requirements. The level of isolation offered is sometimes described using terms like “hard” multi-tenancy, which implies strong isolation, and “soft” multi-tenancy, which implies weaker isolation. In particular, "hard" multi-tenancy is often used to describe cases where the tenants do not trust each other, often from security and resource sharing perspectives (e.g. guarding against attacks such as data exfiltration or DoS). Since data planes typically have much larger attack surfaces, "hard" multi-tenancy often requires extra attention to isolating the data-plane, though control plane isolation also remains critical. However, the terms "hard" and "soft" can often be confusing, as there is no single definition that will apply to all users. Rather, "hardness" or "softness" is better understood as a broad spectrum, with many different techniques that can be used to maintain different types of isolation in your clusters, based on your requirements. In more extreme cases, it may be easier or necessary to forgo any cluster-level sharing at all and assign each tenant their dedicated cluster, possibly even running on dedicated hardware if VMs are not considered an adequate security boundary. This may be easier with managed Kubernetes clusters, where the overhead of creating and operating clusters is at least somewhat taken on by a cloud provider. The benefit of stronger tenant isolation must be evaluated against the cost and complexity of managing multiple clusters. The [Multi-cluster SIG](https://git.k8s.io/community/sig-multicluster/README.md) is responsible for addressing these types of use cases. The remainder of this page focuses on isolation techniques used for shared Kubernetes clusters. However, even if you are considering dedicated clusters, it may be valuable to review these recommendations, as it will give you the flexibility to shift to shared clusters in the future if your needs or capabilities change. ## Control plane isolation Control plane isolation ensures that different tenants cannot access or affect each others' Kubernetes API resources. ### Namespaces In Kubernetes, a {{< glossary\_tooltip text="Namespace" term\_id="namespace" >}} provides a mechanism for isolating groups of API resources within a single cluster. This isolation has two key dimensions: 1. Object names within a namespace can overlap with names in other namespaces, similar to files in folders. This allows tenants to name their resources without having to consider what other tenants are doing. 2. Many Kubernetes security policies are scoped to namespaces. For example, RBAC Roles and Network Policies are namespace-scoped resources. Using RBAC, Users and Service Accounts can be restricted to a namespace. In a multi-tenant environment, a Namespace helps segment a tenant's workload into a logical and distinct management unit. In fact, a common practice is to isolate every workload in its own namespace, even if multiple workloads are operated by the same tenant. This ensures that each workload has its own identity and can be configured with
| null |
./vendor/kubernetes/content/en/docs/concepts/security/multi-tenancy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/multi-tenancy.md
|
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helps segment a tenant's workload into a logical and distinct management unit. In fact, a common practice is to isolate every workload in its own namespace, even if multiple workloads are operated by the same tenant. This ensures that each workload has its own identity and can be configured with an appropriate security policy. The namespace isolation model requires configuration of several other Kubernetes resources, networking plugins, and adherence to security best practices to properly isolate tenant workloads. These considerations are discussed below. ### Access controls The most important type of isolation for the control plane is authorization. If teams or their workloads can access or modify each others' API resources, they can change or disable all other types of policies thereby negating any protection those policies may offer. As a result, it is critical to ensure that each tenant has the appropriate access to only the namespaces they need, and no more. This is known as the "Principle of Least Privilege." Role-based access control (RBAC) is commonly used to enforce authorization in the Kubernetes control plane, for both users and workloads (service accounts). [Roles](/docs/reference/access-authn-authz/rbac/#role-and-clusterrole) and [RoleBindings](/docs/reference/access-authn-authz/rbac/#rolebinding-and-clusterrolebinding) are Kubernetes objects that are used at a namespace level to enforce access control in your application; similar objects exist for authorizing access to cluster-level objects, though these are less useful for multi-tenant clusters. In a multi-team environment, RBAC must be used to restrict tenants' access to the appropriate namespaces, and ensure that cluster-wide resources can only be accessed or modified by privileged users such as cluster administrators. If a policy ends up granting a user more permissions than they need, this is likely a signal that the namespace containing the affected resources should be refactored into finer-grained namespaces. Namespace management tools may simplify the management of these finer-grained namespaces by applying common RBAC policies to different namespaces, while still allowing fine-grained policies where necessary. ### Quotas Kubernetes workloads consume node resources, like CPU and memory. In a multi-tenant environment, you can use [Resource Quotas](/docs/concepts/policy/resource-quotas/) to manage resource usage of tenant workloads. For the multiple teams use case, where tenants have access to the Kubernetes API, you can use resource quotas to limit the number of API resources (for example: the number of Pods, or the number of ConfigMaps) that a tenant can create. Limits on object count ensure fairness and aim to avoid \_noisy neighbor\_ issues from affecting other tenants that share a control plane. Resource quotas are namespaced objects. By mapping tenants to namespaces, cluster admins can use quotas to ensure that a tenant cannot monopolize a cluster's resources or overwhelm its control plane. Namespace management tools simplify the administration of quotas. In addition, while Kubernetes quotas only apply within a single namespace, some namespace management tools allow groups of namespaces to share quotas, giving administrators far more flexibility with less effort than built-in quotas. Quotas prevent a single tenant from consuming greater than their allocated share of resources hence minimizing the “noisy neighbor” issue, where one tenant negatively impacts the performance of other tenants' workloads. When you apply a quota to namespace, Kubernetes requires you to also specify resource requests and limits for each container. Limits are the upper bound for the amount of resources that a container can consume. Containers that attempt to consume resources that exceed the configured limits will either be throttled or killed, based on the resource type. When resource requests are set lower than limits, each container is guaranteed the requested amount but there may still be some potential for impact across workloads. Quotas cannot protect against all kinds of resource sharing, such as network
| null |
./vendor/kubernetes/content/en/docs/concepts/security/multi-tenancy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/multi-tenancy.md
|
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|
limits will either be throttled or killed, based on the resource type. When resource requests are set lower than limits, each container is guaranteed the requested amount but there may still be some potential for impact across workloads. Quotas cannot protect against all kinds of resource sharing, such as network traffic. Node isolation (described below) may be a better solution for this problem. ## Data Plane Isolation Data plane isolation ensures that pods and workloads for different tenants are sufficiently isolated. ### Network isolation By default, all pods in a Kubernetes cluster are allowed to communicate with each other, and all network traffic is unencrypted. This can lead to security vulnerabilities where traffic is accidentally or maliciously sent to an unintended destination, or is intercepted by a workload on a compromised node. Pod-to-pod communication can be controlled using [Network Policies](/docs/concepts/services-networking/network-policies/), which restrict communication between pods using namespace labels or IP address ranges. In a multi-tenant environment where strict network isolation between tenants is required, starting with a default policy that denies communication between pods is recommended with another rule that allows all pods to query the DNS server for name resolution. With such a default policy in place, you can begin adding more permissive rules that allow for communication within a namespace. It is also recommended not to use empty label selector '{}' for namespaceSelector field in network policy definition, in case traffic need to be allowed between namespaces. This scheme can be further refined as required. Note that this only applies to pods within a single control plane; pods that belong to different virtual control planes cannot talk to each other via Kubernetes networking. Namespace management tools may simplify the creation of default or common network policies. In addition, some of these tools allow you to enforce a consistent set of namespace labels across your cluster, ensuring that they are a trusted basis for your policies. {{< warning >}} Network policies require a [CNI plugin](/docs/concepts/extend-kubernetes/compute-storage-net/network-plugins/#cni) that supports the implementation of network policies. Otherwise, NetworkPolicy resources will be ignored. {{< /warning >}} More advanced network isolation may be provided by service meshes, which provide OSI Layer 7 policies based on workload identity, in addition to namespaces. These higher-level policies can make it easier to manage namespace-based multi-tenancy, especially when multiple namespaces are dedicated to a single tenant. They frequently also offer encryption using mutual TLS, protecting your data even in the presence of a compromised node, and work across dedicated or virtual clusters. However, they can be significantly more complex to manage and may not be appropriate for all users. ### Storage isolation Kubernetes offers several types of volumes that can be used as persistent storage for workloads. For security and data-isolation, [dynamic volume provisioning](/docs/concepts/storage/dynamic-provisioning/) is recommended and volume types that use node resources should be avoided. [StorageClasses](/docs/concepts/storage/storage-classes/) allow you to describe custom "classes" of storage offered by your cluster, based on quality-of-service levels, backup policies, or custom policies determined by the cluster administrators. Pods can request storage using a [PersistentVolumeClaim](/docs/concepts/storage/persistent-volumes/). A PersistentVolumeClaim is a namespaced resource, which enables isolating portions of the storage system and dedicating it to tenants within the shared Kubernetes cluster. However, it is important to note that a PersistentVolume is a cluster-wide resource and has a lifecycle independent of workloads and namespaces. For example, you can configure a separate StorageClass for each tenant and use this to strengthen isolation. If a StorageClass is shared, you should set a [reclaim policy of `Delete`](/docs/concepts/storage/storage-classes/#reclaim-policy) to ensure that a PersistentVolume cannot be reused across different namespaces. ### Sandboxing containers Kubernetes pods are composed of one or more containers
| null |
./vendor/kubernetes/content/en/docs/concepts/security/multi-tenancy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/multi-tenancy.md
|
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] | 0.141111
|
can configure a separate StorageClass for each tenant and use this to strengthen isolation. If a StorageClass is shared, you should set a [reclaim policy of `Delete`](/docs/concepts/storage/storage-classes/#reclaim-policy) to ensure that a PersistentVolume cannot be reused across different namespaces. ### Sandboxing containers Kubernetes pods are composed of one or more containers that execute on worker nodes. Containers utilize OS-level virtualization and hence offer a weaker isolation boundary than virtual machines that utilize hardware-based virtualization. In a shared environment, unpatched vulnerabilities in the application and system layers can be exploited by attackers for container breakouts and remote code execution that allow access to host resources. In some applications, like a Content Management System (CMS), customers may be allowed the ability to upload and execute untrusted scripts or code. In either case, mechanisms to further isolate and protect workloads using strong isolation are desirable. Sandboxing provides a way to isolate workloads running in a shared cluster. It typically involves running each pod in a separate execution environment such as a virtual machine or a userspace kernel. Sandboxing is often recommended when you are running untrusted code, where workloads are assumed to be malicious. Part of the reason this type of isolation is necessary is because containers are processes running on a shared kernel; they mount file systems like `/sys` and `/proc` from the underlying host, making them less secure than an application that runs on a virtual machine which has its own kernel. While controls such as seccomp, AppArmor, and SELinux can be used to strengthen the security of containers, it is hard to apply a universal set of rules to all workloads running in a shared cluster. Running workloads in a sandbox environment helps to insulate the host from container escapes, where an attacker exploits a vulnerability to gain access to the host system and all the processes/files running on that host. Virtual machines and userspace kernels are two popular approaches to sandboxing. ### Node Isolation Node isolation is another technique that you can use to isolate tenant workloads from each other. With node isolation, a set of nodes is dedicated to running pods from a particular tenant and co-mingling of tenant pods is prohibited. This configuration reduces the noisy tenant issue, as all pods running on a node will belong to a single tenant. The risk of information disclosure is slightly lower with node isolation because an attacker that manages to escape from a container will only have access to the containers and volumes mounted to that node. Although workloads from different tenants are running on different nodes, it is important to be aware that the kubelet and (unless using virtual control planes) the API service are still shared services. A skilled attacker could use the permissions assigned to the kubelet or other pods running on the node to move laterally within the cluster and gain access to tenant workloads running on other nodes. If this is a major concern, consider implementing compensating controls such as seccomp, AppArmor or SELinux or explore using sandboxed containers or creating separate clusters for each tenant. Node isolation is a little easier to reason about from a billing standpoint than sandboxing containers since you can charge back per node rather than per pod. It also has fewer compatibility and performance issues and may be easier to implement than sandboxing containers. For example, nodes for each tenant can be configured with taints so that only pods with the corresponding toleration can run on them. A mutating webhook could then be used to automatically add tolerations and node affinities to pods deployed into tenant namespaces so that
| null |
./vendor/kubernetes/content/en/docs/concepts/security/multi-tenancy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/multi-tenancy.md
|
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] | 0.137959
|
to implement than sandboxing containers. For example, nodes for each tenant can be configured with taints so that only pods with the corresponding toleration can run on them. A mutating webhook could then be used to automatically add tolerations and node affinities to pods deployed into tenant namespaces so that they run on a specific set of nodes designated for that tenant. Node isolation can be implemented using [pod node selectors](/docs/concepts/scheduling-eviction/assign-pod-node/). ## Additional Considerations This section discusses other Kubernetes constructs and patterns that are relevant for multi-tenancy. ### API Priority and Fairness [API priority and fairness](/docs/concepts/cluster-administration/flow-control/) is a Kubernetes feature that allows you to assign a priority to certain pods running within the cluster. When an application calls the Kubernetes API, the API server evaluates the priority assigned to pod. Calls from pods with higher priority are fulfilled before those with a lower priority. When contention is high, lower priority calls can be queued until the server is less busy or you can reject the requests. Using API priority and fairness will not be very common in SaaS environments unless you are allowing customers to run applications that interface with the Kubernetes API, for example, a controller. ### Quality-of-Service (QoS) {#qos} When you’re running a SaaS application, you may want the ability to offer different Quality-of-Service (QoS) tiers of service to different tenants. For example, you may have freemium service that comes with fewer performance guarantees and features and a for-fee service tier with specific performance guarantees. Fortunately, there are several Kubernetes constructs that can help you accomplish this within a shared cluster, including network QoS, storage classes, and pod priority and preemption. The idea with each of these is to provide tenants with the quality of service that they paid for. Let’s start by looking at networking QoS. Typically, all pods on a node share a network interface. Without network QoS, some pods may consume an unfair share of the available bandwidth at the expense of other pods. The Kubernetes [bandwidth plugin](https://www.cni.dev/plugins/current/meta/bandwidth/) creates an [extended resource](/docs/concepts/configuration/manage-resources-containers/#extended-resources) for networking that allows you to use Kubernetes resources constructs, i.e. requests/limits, to apply rate limits to pods by using Linux tc queues. Be aware that the plugin is considered experimental as per the [Network Plugins](/docs/concepts/extend-kubernetes/compute-storage-net/network-plugins/#support-traffic-shaping) documentation and should be thoroughly tested before use in production environments. For storage QoS, you will likely want to create different storage classes or profiles with different performance characteristics. Each storage profile can be associated with a different tier of service that is optimized for different workloads such IO, redundancy, or throughput. Additional logic might be necessary to allow the tenant to associate the appropriate storage profile with their workload. Finally, there’s [pod priority and preemption](/docs/concepts/scheduling-eviction/pod-priority-preemption/) where you can assign priority values to pods. When scheduling pods, the scheduler will try evicting pods with lower priority when there are insufficient resources to schedule pods that are assigned a higher priority. If you have a use case where tenants have different service tiers in a shared cluster e.g. free and paid, you may want to give higher priority to certain tiers using this feature. ### DNS Kubernetes clusters include a Domain Name System (DNS) service to provide translations from names to IP addresses, for all Services and Pods. By default, the Kubernetes DNS service allows lookups across all namespaces in the cluster. In multi-tenant environments where tenants can access pods and other Kubernetes resources, or where stronger isolation is required, it may be necessary to prevent pods from looking up services in other Namespaces. You can restrict cross-namespace DNS lookups by configuring security rules for the DNS service.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/multi-tenancy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/multi-tenancy.md
|
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|
namespaces in the cluster. In multi-tenant environments where tenants can access pods and other Kubernetes resources, or where stronger isolation is required, it may be necessary to prevent pods from looking up services in other Namespaces. You can restrict cross-namespace DNS lookups by configuring security rules for the DNS service. For example, CoreDNS (the default DNS service for Kubernetes) can leverage Kubernetes metadata to restrict queries to Pods and Services within a namespace. For more information, read an [example](https://github.com/coredns/policy#kubernetes-metadata-multi-tenancy-policy) of configuring this within the CoreDNS documentation. When a [Virtual Control Plane per tenant](#virtual-control-plane-per-tenant) model is used, a DNS service must be configured per tenant or a multi-tenant DNS service must be used. Here is an example of a [customized version of CoreDNS](https://github.com/kubernetes-sigs/cluster-api-provider-nested/blob/main/virtualcluster/doc/tenant-dns.md) that supports multiple tenants. ### Operators [Operators](/docs/concepts/extend-kubernetes/operator/) are Kubernetes controllers that manage applications. Operators can simplify the management of multiple instances of an application, like a database service, which makes them a common building block in the multi-consumer (SaaS) multi-tenancy use case. Operators used in a multi-tenant environment should follow a stricter set of guidelines. Specifically, the Operator should: \* Support creating resources within different tenant namespaces, rather than just in the namespace in which the Operator is deployed. \* Ensure that the Pods are configured with resource requests and limits, to ensure scheduling and fairness. \* Support configuration of Pods for data-plane isolation techniques such as node isolation and sandboxed containers. ## Implementations There are two primary ways to share a Kubernetes cluster for multi-tenancy: using Namespaces (that is, a Namespace per tenant) or by virtualizing the control plane (that is, virtual control plane per tenant). In both cases, data plane isolation, and management of additional considerations such as API Priority and Fairness, is also recommended. Namespace isolation is well-supported by Kubernetes, has a negligible resource cost, and provides mechanisms to allow tenants to interact appropriately, such as by allowing service-to-service communication. However, it can be difficult to configure, and doesn't apply to Kubernetes resources that can't be namespaced, such as Custom Resource Definitions, Storage Classes, and Webhooks. Control plane virtualization allows for isolation of non-namespaced resources at the cost of somewhat higher resource usage and more difficult cross-tenant sharing. It is a good option when namespace isolation is insufficient but dedicated clusters are undesirable, due to the high cost of maintaining them (especially on-prem) or due to their higher overhead and lack of resource sharing. However, even within a virtualized control plane, you will likely see benefits by using namespaces as well. The two options are discussed in more detail in the following sections. ### Namespace per tenant As previously mentioned, you should consider isolating each workload in its own namespace, even if you are using dedicated clusters or virtualized control planes. This ensures that each workload only has access to its own resources, such as ConfigMaps and Secrets, and allows you to tailor dedicated security policies for each workload. In addition, it is a best practice to give each namespace names that are unique across your entire fleet (that is, even if they are in separate clusters), as this gives you the flexibility to switch between dedicated and shared clusters in the future, or to use multi-cluster tooling such as service meshes. Conversely, there are also advantages to assigning namespaces at the tenant level, not just the workload level, since there are often policies that apply to all workloads owned by a single tenant. However, this raises its own problems. Firstly, this makes it difficult or impossible to customize policies to individual workloads, and secondly, it may be challenging to come up with a single
| null |
./vendor/kubernetes/content/en/docs/concepts/security/multi-tenancy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/multi-tenancy.md
|
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] | 0.126031
|
just the workload level, since there are often policies that apply to all workloads owned by a single tenant. However, this raises its own problems. Firstly, this makes it difficult or impossible to customize policies to individual workloads, and secondly, it may be challenging to come up with a single level of "tenancy" that should be given a namespace. For example, an organization may have divisions, teams, and subteams - which should be assigned a namespace? One possible approach is to organize your namespaces into hierarchies, and share certain policies and resources between them. This could include managing namespace labels, namespace lifecycles, delegated access, and shared resource quotas across related namespaces. These capabilities can be useful in both multi-team and multi-customer scenarios. ### Virtual control plane per tenant Another form of control-plane isolation is to use Kubernetes extensions to provide each tenant a virtual control-plane that enables segmentation of cluster-wide API resources. [Data plane isolation](#data-plane-isolation) techniques can be used with this model to securely manage worker nodes across tenants. The virtual control plane based multi-tenancy model extends namespace-based multi-tenancy by providing each tenant with dedicated control plane components, and hence complete control over cluster-wide resources and add-on services. Worker nodes are shared across all tenants, and are managed by a Kubernetes cluster that is normally inaccessible to tenants. This cluster is often referred to as a \_super-cluster\_ (or sometimes as a \_host-cluster\_). Since a tenant’s control-plane is not directly associated with underlying compute resources it is referred to as a \_virtual control plane\_. A virtual control plane typically consists of the Kubernetes API server, the controller manager, and the etcd data store. It interacts with the super cluster via a metadata synchronization controller which coordinates changes across tenant control planes and the control plane of the super-cluster. By using per-tenant dedicated control planes, most of the isolation problems due to sharing one API server among all tenants are solved. Examples include noisy neighbors in the control plane, uncontrollable blast radius of policy misconfigurations, and conflicts between cluster scope objects such as webhooks and CRDs. Hence, the virtual control plane model is particularly suitable for cases where each tenant requires access to a Kubernetes API server and expects the full cluster manageability. The improved isolation comes at the cost of running and maintaining an individual virtual control plane per tenant. In addition, per-tenant control planes do not solve isolation problems in the data plane, such as node-level noisy neighbors or security threats. These must still be addressed separately.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/multi-tenancy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/multi-tenancy.md
|
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|
{{< feature-state for\_k8s\_version="v1.25" state="stable" >}} The Kubernetes [Pod Security Standards](/docs/concepts/security/pod-security-standards/) define different isolation levels for Pods. These standards let you define how you want to restrict the behavior of pods in a clear, consistent fashion. Kubernetes offers a built-in \_Pod Security\_ {{< glossary\_tooltip text="admission controller" term\_id="admission-controller" >}} to enforce the Pod Security Standards. Pod security restrictions are applied at the {{< glossary\_tooltip text="namespace" term\_id="namespace" >}} level when pods are created. ### Built-in Pod Security admission enforcement This page is part of the documentation for Kubernetes v{{< skew currentVersion >}}. If you are running a different version of Kubernetes, consult the documentation for that release. ## Pod Security levels Pod Security admission places requirements on a Pod's [Security Context](/docs/tasks/configure-pod-container/security-context/) and other related fields according to the three levels defined by the [Pod Security Standards](/docs/concepts/security/pod-security-standards): `privileged`, `baseline`, and `restricted`. Refer to the [Pod Security Standards](/docs/concepts/security/pod-security-standards) page for an in-depth look at those requirements. ## Pod Security Admission labels for namespaces Once the feature is enabled or the webhook is installed, you can configure namespaces to define the admission control mode you want to use for pod security in each namespace. Kubernetes defines a set of {{< glossary\_tooltip term\_id="label" text="labels" >}} that you can set to define which of the predefined Pod Security Standard levels you want to use for a namespace. The label you select defines what action the {{< glossary\_tooltip text="control plane" term\_id="control-plane" >}} takes if a potential violation is detected: {{< table caption="Pod Security Admission modes" >}} Mode | Description :---------|:------------ \*\*enforce\*\* | Policy violations will cause the pod to be rejected. \*\*audit\*\* | Policy violations will trigger the addition of an audit annotation to the event recorded in the [audit log](/docs/tasks/debug/debug-cluster/audit/), but are otherwise allowed. \*\*warn\*\* | Policy violations will trigger a user-facing warning, but are otherwise allowed. {{< /table >}} A namespace can configure any or all modes, or even set a different level for different modes. For each mode, there are two labels that determine the policy used: ```yaml # The per-mode level label indicates which policy level to apply for the mode. # # MODE must be one of `enforce`, `audit`, or `warn`. # LEVEL must be one of `privileged`, `baseline`, or `restricted`. pod-security.kubernetes.io/: # Optional: per-mode version label that can be used to pin the policy to the # version that shipped with a given Kubernetes minor version (for example v{{< skew currentVersion >}}). # # MODE must be one of `enforce`, `audit`, or `warn`. # VERSION must be a valid Kubernetes minor version, or `latest`. pod-security.kubernetes.io/-version: ``` Check out [Enforce Pod Security Standards with Namespace Labels](/docs/tasks/configure-pod-container/enforce-standards-namespace-labels) to see example usage. ## Workload resources and Pod templates Pods are often created indirectly, by creating a [workload object](/docs/concepts/workloads/controllers/) such as a {{< glossary\_tooltip term\_id="deployment" >}} or {{< glossary\_tooltip term\_id="job">}}. The workload object defines a \_Pod template\_ and a {{< glossary\_tooltip term\_id="controller" text="controller" >}} for the workload resource creates Pods based on that template. To help catch violations early, both the audit and warning modes are applied to the workload resources. However, enforce mode is \*\*not\*\* applied to workload resources, only to the resulting pod objects. ## Exemptions You can define \_exemptions\_ from pod security enforcement in order to allow the creation of pods that would have otherwise been prohibited due to the policy associated with a given namespace. Exemptions can be statically configured in the [Admission Controller configuration](/docs/tasks/configure-pod-container/enforce-standards-admission-controller/#configure-the-admission-controller). Exemptions must be explicitly enumerated. Requests meeting exemption criteria are \_ignored\_ by the Admission Controller (all `enforce`, `audit` and `warn` behaviors are skipped). Exemption dimensions include: - \*\*Usernames:\*\* requests from users with an exempt authenticated (or impersonated) username
| null |
./vendor/kubernetes/content/en/docs/concepts/security/pod-security-admission.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/pod-security-admission.md
|
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|
given namespace. Exemptions can be statically configured in the [Admission Controller configuration](/docs/tasks/configure-pod-container/enforce-standards-admission-controller/#configure-the-admission-controller). Exemptions must be explicitly enumerated. Requests meeting exemption criteria are \_ignored\_ by the Admission Controller (all `enforce`, `audit` and `warn` behaviors are skipped). Exemption dimensions include: - \*\*Usernames:\*\* requests from users with an exempt authenticated (or impersonated) username are ignored. - \*\*RuntimeClassNames:\*\* pods and [workload resources](#workload-resources-and-pod-templates) specifying an exempt runtime class name are ignored. - \*\*Namespaces:\*\* pods and [workload resources](#workload-resources-and-pod-templates) in an exempt namespace are ignored. {{< caution >}} Most pods are created by a controller in response to a [workload resource](#workload-resources-and-pod-templates), meaning that exempting an end user will only exempt them from enforcement when creating pods directly, but not when creating a workload resource. Controller service accounts (such as `system:serviceaccount:kube-system:replicaset-controller`) should generally not be exempted, as doing so would implicitly exempt any user that can create the corresponding workload resource. {{< /caution >}} Updates to the following pod fields are exempt from policy checks, meaning that if a pod update request only changes these fields, it will not be denied even if the pod is in violation of the current policy level: - Any metadata updates \*\*except\*\* changes to the seccomp or AppArmor annotations: - `seccomp.security.alpha.kubernetes.io/pod` (deprecated) - `container.seccomp.security.alpha.kubernetes.io/\*` (deprecated) - `container.apparmor.security.beta.kubernetes.io/\*` (deprecated) - Valid updates to `.spec.activeDeadlineSeconds` - Valid updates to `.spec.tolerations` ## Metrics Here are the Prometheus metrics exposed by kube-apiserver: - `pod\_security\_errors\_total`: This metric indicates the number of errors preventing normal evaluation. Non-fatal errors may result in the latest restricted profile being used for enforcement. - `pod\_security\_evaluations\_total`: This metric indicates the number of policy evaluations that have occurred, not counting ignored or exempt requests during exporting. - `pod\_security\_exemptions\_total`: This metric indicates the number of exempt requests, not counting ignored or out of scope requests. ## {{% heading "whatsnext" %}} - [Pod Security Standards](/docs/concepts/security/pod-security-standards) - [Enforcing Pod Security Standards](/docs/setup/best-practices/enforcing-pod-security-standards) - [Enforce Pod Security Standards by Configuring the Built-in Admission Controller](/docs/tasks/configure-pod-container/enforce-standards-admission-controller) - [Enforce Pod Security Standards with Namespace Labels](/docs/tasks/configure-pod-container/enforce-standards-namespace-labels) If you are running an older version of Kubernetes and want to upgrade to a version of Kubernetes that does not include PodSecurityPolicies, read [migrate from PodSecurityPolicy to the Built-In PodSecurity Admission Controller](/docs/tasks/configure-pod-container/migrate-from-psp).
| null |
./vendor/kubernetes/content/en/docs/concepts/security/pod-security-admission.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/pod-security-admission.md
|
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] | 0.14476
|
This page provides an overview of controlling access to the Kubernetes API. Users access the [Kubernetes API](/docs/concepts/overview/kubernetes-api/) using `kubectl`, client libraries, or by making REST requests. Both human users and [Kubernetes service accounts](/docs/tasks/configure-pod-container/configure-service-account/) can be authorized for API access. When a request reaches the API, it goes through several stages, illustrated in the following diagram:  ## Transport security By default, the Kubernetes API server listens on port 6443 on the first non-localhost network interface, protected by TLS. In a typical production Kubernetes cluster, the API serves on port 443. The port can be changed with the `--secure-port`, and the listening IP address with the `--bind-address` flag. The API server presents a certificate. This certificate may be signed using a private certificate authority (CA), or based on a public key infrastructure linked to a generally recognized CA. The certificate and corresponding private key can be set by using the `--tls-cert-file` and `--tls-private-key-file` flags. If your cluster uses a private certificate authority, you need a copy of that CA certificate configured into your `~/.kube/config` on the client, so that you can trust the connection and be confident it was not intercepted. Your client can present a TLS client certificate at this stage. ## Authentication Once TLS is established, the HTTP request moves to the Authentication step. This is shown as step \*\*1\*\* in the diagram. The cluster creation script or cluster admin configures the API server to run one or more Authenticator modules. Authenticators are described in more detail in [Authentication](/docs/reference/access-authn-authz/authentication/). The input to the authentication step is the entire HTTP request; however, it typically examines the headers and/or client certificate. Authentication modules include client certificates, password, and plain tokens, bootstrap tokens, and JSON Web Tokens (used for service accounts). Multiple authentication modules can be specified, in which case each one is tried in sequence, until one of them succeeds. If the request cannot be authenticated, it is rejected with HTTP status code 401. Otherwise, the user is authenticated as a specific `username`, and the user name is available to subsequent steps to use in their decisions. Some authenticators also provide the group memberships of the user, while other authenticators do not. While Kubernetes uses usernames for access control decisions and in request logging, it does not have a `User` object nor does it store usernames or other information about users in its API. ## Authorization After the request is authenticated as coming from a specific user, the request must be authorized. This is shown as step \*\*2\*\* in the diagram. A request must include the username of the requester, the requested action, and the object affected by the action. The request is authorized if an existing policy declares that the user has permissions to complete the requested action. For example, if Bob has the policy below, then he can read pods only in the namespace `projectCaribou`: ```json { "apiVersion": "abac.authorization.kubernetes.io/v1beta1", "kind": "Policy", "spec": { "user": "bob", "namespace": "projectCaribou", "resource": "pods", "readonly": true } } ``` If Bob makes the following request, the request is authorized because he is allowed to read objects in the `projectCaribou` namespace: ```json { "apiVersion": "authorization.k8s.io/v1beta1", "kind": "SubjectAccessReview", "spec": { "resourceAttributes": { "namespace": "projectCaribou", "verb": "get", "group": "unicorn.example.org", "resource": "pods" } } } ``` If Bob makes a request to write (`create` or `update`) to the objects in the `projectCaribou` namespace, his authorization is denied. If Bob makes a request to read (`get`) objects in a different namespace such as `projectFish`, then his authorization is denied. Kubernetes authorization requires that you use common REST attributes to interact with
| null |
./vendor/kubernetes/content/en/docs/concepts/security/controlling-access.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/controlling-access.md
|
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] | 0.134612
|
request to write (`create` or `update`) to the objects in the `projectCaribou` namespace, his authorization is denied. If Bob makes a request to read (`get`) objects in a different namespace such as `projectFish`, then his authorization is denied. Kubernetes authorization requires that you use common REST attributes to interact with existing organization-wide or cloud-provider-wide access control systems. It is important to use REST formatting because these control systems might interact with other APIs besides the Kubernetes API. Kubernetes supports multiple authorization modules, such as ABAC mode, RBAC Mode, and Webhook mode. When an administrator creates a cluster, they configure the authorization modules that should be used in the API server. If more than one authorization modules are configured, Kubernetes checks each module, and if any module authorizes the request, then the request can proceed. If all of the modules deny the request, then the request is denied (HTTP status code 403). To learn more about Kubernetes authorization, including details about creating policies using the supported authorization modules, see [Authorization](/docs/reference/access-authn-authz/authorization/). ## Admission control Admission Control modules are software modules that can modify or reject requests. In addition to the attributes available to Authorization modules, Admission Control modules can access the contents of the object that is being created or modified. Admission controllers act on requests that create, modify, delete, or connect to (proxy) an object. Admission controllers do not act on requests that merely read objects. When multiple admission controllers are configured, they are called in order. This is shown as step \*\*3\*\* in the diagram. Unlike Authentication and Authorization modules, if any admission controller module rejects, then the request is immediately rejected. In addition to rejecting objects, admission controllers can also set complex defaults for fields. The available Admission Control modules are described in [Admission Controllers](/docs/reference/access-authn-authz/admission-controllers/). Once a request passes all admission controllers, it is validated using the validation routines for the corresponding API object, and then written to the object store (shown as step \*\*4\*\*). ## Auditing Kubernetes auditing provides a security-relevant, chronological set of records documenting the sequence of actions in a cluster. The cluster audits the activities generated by users, by applications that use the Kubernetes API, and by the control plane itself. For more information, see [Auditing](/docs/tasks/debug/debug-cluster/audit/). ## {{% heading "whatsnext" %}} Read more documentation on authentication, authorization and API access control: - [Authenticating](/docs/reference/access-authn-authz/authentication/) - [Authenticating with Bootstrap Tokens](/docs/reference/access-authn-authz/bootstrap-tokens/) - [Admission Controllers](/docs/reference/access-authn-authz/admission-controllers/) - [Dynamic Admission Control](/docs/reference/access-authn-authz/extensible-admission-controllers/) - [Authorization](/docs/reference/access-authn-authz/authorization/) - [Role Based Access Control](/docs/reference/access-authn-authz/rbac/) - [Attribute Based Access Control](/docs/reference/access-authn-authz/abac/) - [Node Authorization](/docs/reference/access-authn-authz/node/) - [Webhook Authorization](/docs/reference/access-authn-authz/webhook/) - [Certificate Signing Requests](/docs/reference/access-authn-authz/certificate-signing-requests/) - including [CSR approval](/docs/reference/access-authn-authz/certificate-signing-requests/#approval-rejection) and [certificate signing](/docs/reference/access-authn-authz/certificate-signing-requests/#signing) - Service accounts - [Developer guide](/docs/tasks/configure-pod-container/configure-service-account/) - [Administration](/docs/reference/access-authn-authz/service-accounts-admin/) You can learn about: - how Pods can use [Secrets](/docs/concepts/configuration/secret/#service-accounts-automatically-create-and-attach-secrets-with-api-credentials) to obtain API credentials.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/controlling-access.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/controlling-access.md
|
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0.017690032720565796,
-0.03623028099536896,
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] | 0.1296
|
This checklist aims at providing a basic list of guidance with links to more comprehensive documentation on each topic. It does not claim to be exhaustive and is meant to evolve. On how to read and use this document: - The order of topics does not reflect an order of priority. - Some checklist items are detailed in the paragraph below the list of each section. {{< caution >}} Checklists are \*\*not\*\* sufficient for attaining a good security posture on their own. A good security posture requires constant attention and improvement, but a checklist can be the first step on the never-ending journey towards security preparedness. Some of the recommendations in this checklist may be too restrictive or too lax for your specific security needs. Since Kubernetes security is not "one size fits all", each category of checklist items should be evaluated on its merits. {{< /caution >}} ## Authentication & Authorization - [ ] `system:masters` group is not used for user or component authentication after bootstrapping. - [ ] The kube-controller-manager is running with `--use-service-account-credentials` enabled. - [ ] The root certificate is protected (either an offline CA, or a managed online CA with effective access controls). - [ ] Intermediate and leaf certificates have an expiry date no more than 3 years in the future. - [ ] A process exists for periodic access review, and reviews occur no more than 24 months apart. - [ ] The [Role Based Access Control Good Practices](/docs/concepts/security/rbac-good-practices/) are followed for guidance related to authentication and authorization. After bootstrapping, neither users nor components should authenticate to the Kubernetes API as `system:masters`. Similarly, running all of kube-controller-manager as `system:masters` should be avoided. In fact, `system:masters` should only be used as a break-glass mechanism, as opposed to an admin user. ## Network security - [ ] CNI plugins in use support network policies. - [ ] Ingress and egress network policies are applied to all workloads in the cluster. - [ ] Default network policies within each namespace, selecting all pods, denying everything, are in place. - [ ] If appropriate, a service mesh is used to encrypt all communications inside of the cluster. - [ ] The Kubernetes API, kubelet API and etcd are not exposed publicly on Internet. - [ ] Access from the workloads to the cloud metadata API is filtered. - [ ] Use of LoadBalancer and ExternalIPs is restricted. A number of [Container Network Interface (CNI) plugins](/docs/concepts/extend-kubernetes/compute-storage-net/network-plugins/) plugins provide the functionality to restrict network resources that pods may communicate with. This is most commonly done through [Network Policies](/docs/concepts/services-networking/network-policies/) which provide a namespaced resource to define rules. Default network policies that block all egress and ingress, in each namespace, selecting all pods, can be useful to adopt an allow list approach to ensure that no workloads are missed. Not all CNI plugins provide encryption in transit. If the chosen plugin lacks this feature, an alternative solution could be to use a service mesh to provide that functionality. The etcd datastore of the control plane should have controls to limit access and not be publicly exposed on the Internet. Furthermore, mutual TLS (mTLS) should be used to communicate securely with it. The certificate authority for this should be unique to etcd. External Internet access to the Kubernetes API server should be restricted to not expose the API publicly. Be careful, as many managed Kubernetes distributions are publicly exposing the API server by default. You can then use a bastion host to access the server. The [kubelet](/docs/reference/command-line-tools-reference/kubelet/) API access should be restricted and not exposed publicly, the default authentication and authorization settings,
| null |
./vendor/kubernetes/content/en/docs/concepts/security/security-checklist.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/security-checklist.md
|
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] | 0.083652
|
restricted to not expose the API publicly. Be careful, as many managed Kubernetes distributions are publicly exposing the API server by default. You can then use a bastion host to access the server. The [kubelet](/docs/reference/command-line-tools-reference/kubelet/) API access should be restricted and not exposed publicly, the default authentication and authorization settings, when no configuration file specified with the `--config` flag, are overly permissive. If a cloud provider is used for hosting Kubernetes, the access from pods to the cloud metadata API `169.254.169.254` should also be restricted or blocked if not needed because it may leak information. For restricted LoadBalancer and ExternalIPs use, see [CVE-2020-8554: Man in the middle using LoadBalancer or ExternalIPs](https://github.com/kubernetes/kubernetes/issues/97076) and the [DenyServiceExternalIPs admission controller](/docs/reference/access-authn-authz/admission-controllers/#denyserviceexternalips) for further information. ## Pod security - [ ] RBAC rights to `create`, `update`, `patch`, `delete` workloads is only granted if necessary. - [ ] Appropriate Pod Security Standards policy is applied for all namespaces and enforced. - [ ] Memory limit is set for the workloads with a limit equal or inferior to the request. - [ ] CPU limit might be set on sensitive workloads. - [ ] For nodes that support it, Seccomp is enabled with appropriate syscalls profile for programs. - [ ] For nodes that support it, AppArmor or SELinux is enabled with appropriate profile for programs. RBAC authorization is crucial but [cannot be granular enough to have authorization on the Pods' resources](/docs/concepts/security/rbac-good-practices/#workload-creation) (or on any resource that manages Pods). The only granularity is the API verbs on the resource itself, for example, `create` on Pods. Without additional admission, the authorization to create these resources allows direct unrestricted access to the schedulable nodes of a cluster. The [Pod Security Standards](/docs/concepts/security/pod-security-standards/) define three different policies, privileged, baseline and restricted that limit how fields can be set in the `PodSpec` regarding security. These standards can be enforced at the namespace level with the new [Pod Security](/docs/concepts/security/pod-security-admission/) admission, enabled by default, or by third-party admission webhook. Please note that, contrary to the removed PodSecurityPolicy admission it replaces, [Pod Security](/docs/concepts/security/pod-security-admission/) admission can be easily combined with admission webhooks and external services. Pod Security admission `restricted` policy, the most restrictive policy of the [Pod Security Standards](/docs/concepts/security/pod-security-standards/) set, [can operate in several modes](/docs/concepts/security/pod-security-admission/#pod-security-admission-labels-for-namespaces), `warn`, `audit` or `enforce` to gradually apply the most appropriate [security context](/docs/tasks/configure-pod-container/security-context/) according to security best practices. Nevertheless, pods' [security context](/docs/tasks/configure-pod-container/security-context/) should be separately investigated to limit the privileges and access pods may have on top of the predefined security standards, for specific use cases. For a hands-on tutorial on [Pod Security](/docs/concepts/security/pod-security-admission/), see the blog post [Kubernetes 1.23: Pod Security Graduates to Beta](/blog/2021/12/09/pod-security-admission-beta/). [Memory and CPU limits](/docs/concepts/configuration/manage-resources-containers/) should be set in order to restrict the memory and CPU resources a pod can consume on a node, and therefore prevent potential DoS attacks from malicious or breached workloads. Such policy can be enforced by an admission controller. Please note that CPU limits will throttle usage and thus can have unintended effects on auto-scaling features or efficiency i.e. running the process in best effort with the CPU resource available. {{< caution >}} Memory limit superior to request can expose the whole node to OOM issues. {{< /caution >}} ### Enabling Seccomp Seccomp stands for secure computing mode and has been a feature of the Linux kernel since version 2.6.12. It can be used to sandbox the privileges of a process, restricting the calls it is able to make from userspace into the kernel. Kubernetes lets you automatically apply seccomp profiles loaded onto a node to your Pods and containers. Seccomp can improve the security of your workloads by reducing the Linux kernel syscall attack
| null |
./vendor/kubernetes/content/en/docs/concepts/security/security-checklist.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/security-checklist.md
|
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] | 0.099213
|
sandbox the privileges of a process, restricting the calls it is able to make from userspace into the kernel. Kubernetes lets you automatically apply seccomp profiles loaded onto a node to your Pods and containers. Seccomp can improve the security of your workloads by reducing the Linux kernel syscall attack surface available inside containers. The seccomp filter mode leverages BPF to create an allow or deny list of specific syscalls, named profiles. Since Kubernetes 1.27, you can enable the use of `RuntimeDefault` as the default seccomp profile for all workloads. A [security tutorial](/docs/tutorials/security/seccomp/) is available on this topic. In addition, the [Kubernetes Security Profiles Operator](https://github.com/kubernetes-sigs/security-profiles-operator) is a project that facilitates the management and use of seccomp in clusters. {{< note >}} Seccomp is only available on Linux nodes. {{< /note >}} ### Enabling AppArmor or SELinux #### AppArmor [AppArmor](/docs/tutorials/security/apparmor/) is a Linux kernel security module that can provide an easy way to implement Mandatory Access Control (MAC) and better auditing through system logs. A default AppArmor profile is enforced on nodes that support it, or a custom profile can be configured. Like seccomp, AppArmor is also configured through profiles, where each profile is either running in enforcing mode, which blocks access to disallowed resources or complain mode, which only reports violations. AppArmor profiles are enforced on a per-container basis, with an annotation, allowing for processes to gain just the right privileges. {{< note >}} AppArmor is only available on Linux nodes, and enabled in [some Linux distributions](https://gitlab.com/apparmor/apparmor/-/wikis/home#distributions-and-ports). {{< /note >}} #### SELinux [SELinux](https://github.com/SELinuxProject/selinux-notebook/blob/main/src/selinux\_overview.md) is also a Linux kernel security module that can provide a mechanism for supporting access control security policies, including Mandatory Access Controls (MAC). SELinux labels can be assigned to containers or pods [via their `securityContext` section](/docs/tasks/configure-pod-container/security-context/#assign-selinux-labels-to-a-container). {{< note >}} SELinux is only available on Linux nodes, and enabled in [some Linux distributions](https://en.wikipedia.org/wiki/Security-Enhanced\_Linux#Implementations). {{< /note >}} ## Logs and auditing - [ ] Audit logs, if enabled, are protected from general access. ## Pod placement - [ ] Pod placement is done in accordance with the tiers of sensitivity of the application. - [ ] Sensitive applications are running isolated on nodes or with specific sandboxed runtimes. Pods that are on different tiers of sensitivity, for example, an application pod and the Kubernetes API server, should be deployed onto separate nodes. The purpose of node isolation is to prevent an application container breakout to directly providing access to applications with higher level of sensitivity to easily pivot within the cluster. This separation should be enforced to prevent pods accidentally being deployed onto the same node. This could be enforced with the following features: [Node Selectors](/docs/concepts/scheduling-eviction/assign-pod-node/) : Key-value pairs, as part of the pod specification, that specify which nodes to deploy onto. These can be enforced at the namespace and cluster level with the [PodNodeSelector](/docs/reference/access-authn-authz/admission-controllers/#podnodeselector) admission controller. [PodTolerationRestriction](/docs/reference/access-authn-authz/admission-controllers/#podtolerationrestriction) : An admission controller that allows administrators to restrict permitted [tolerations](/docs/concepts/scheduling-eviction/taint-and-toleration/) within a namespace. Pods within a namespace may only utilize the tolerations specified on the namespace object annotation keys that provide a set of default and allowed tolerations. [RuntimeClass](/docs/concepts/containers/runtime-class/) : RuntimeClass is a feature for selecting the container runtime configuration. The container runtime configuration is used to run a Pod's containers and can provide more or less isolation from the host at the cost of performance overhead. ## Secrets - [ ] ConfigMaps are not used to hold confidential data. - [ ] Encryption at rest is configured for the Secret API. - [ ] If appropriate, a mechanism to inject secrets stored in third-party storage is deployed and available. - [ ] Service account tokens are not mounted in
| null |
./vendor/kubernetes/content/en/docs/concepts/security/security-checklist.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/security-checklist.md
|
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] | 0.248595
|
[ ] ConfigMaps are not used to hold confidential data. - [ ] Encryption at rest is configured for the Secret API. - [ ] If appropriate, a mechanism to inject secrets stored in third-party storage is deployed and available. - [ ] Service account tokens are not mounted in pods that don't require them. - [ ] [Bound service account token volume](/docs/reference/access-authn-authz/service-accounts-admin/#bound-service-account-token-volume) is in-use instead of non-expiring tokens. Secrets required for pods should be stored within Kubernetes Secrets as opposed to alternatives such as ConfigMap. Secret resources stored within etcd should be [encrypted at rest](/docs/tasks/administer-cluster/encrypt-data/). Pods needing secrets should have these automatically mounted through volumes, preferably stored in memory like with the [`emptyDir.medium` option](/docs/concepts/storage/volumes/#emptydir). Mechanism can be used to also inject secrets from third-party storages as volume, like the [Secrets Store CSI Driver](https://secrets-store-csi-driver.sigs.k8s.io/). This should be done preferentially as compared to providing the pods service account RBAC access to secrets. This would allow adding secrets into the pod as environment variables or files. Please note that the environment variable method might be more prone to leakage due to crash dumps in logs and the non-confidential nature of environment variable in Linux, as opposed to the permission mechanism on files. Service account tokens should not be mounted into pods that do not require them. This can be configured by setting [`automountServiceAccountToken`](/docs/tasks/configure-pod-container/configure-service-account/#use-the-default-service-account-to-access-the-api-server) to `false` either within the service account to apply throughout the namespace or specifically for a pod. For Kubernetes v1.22 and above, use [Bound Service Accounts](/docs/reference/access-authn-authz/service-accounts-admin/#bound-service-account-token-volume) for time-bound service account credentials. ## Images - [ ] Minimize unnecessary content in container images. - [ ] Container images are configured to be run as unprivileged user. - [ ] References to container images are made by sha256 digests (rather than tags) or the provenance of the image is validated by verifying the image's digital signature at deploy time [via admission control](/docs/tasks/administer-cluster/verify-signed-artifacts/#verifying-image-signatures-with-admission-controller). - [ ] Container images are regularly scanned during creation and in deployment, and known vulnerable software is patched. Container image should contain the bare minimum to run the program they package. Preferably, only the program and its dependencies, building the image from the minimal possible base. In particular, image used in production should not contain shells or debugging utilities, as an [ephemeral debug container](/docs/tasks/debug/debug-application/debug-running-pod/#ephemeral-container) can be used for troubleshooting. Build images to directly start with an unprivileged user by using the [`USER` instruction in Dockerfile](https://docs.docker.com/develop/develop-images/dockerfile\_best-practices/#user). The [Security Context](/docs/tasks/configure-pod-container/security-context/#set-the-security-context-for-a-pod) allows a container image to be started with a specific user and group with `runAsUser` and `runAsGroup`, even if not specified in the image manifest. However, the file permissions in the image layers might make it impossible to just start the process with a new unprivileged user without image modification. Avoid using image tags to reference an image, especially the `latest` tag, the image behind a tag can be easily modified in a registry. Prefer using the complete `sha256` digest which is unique to the image manifest. This policy can be enforced via an [ImagePolicyWebhook](/docs/reference/access-authn-authz/admission-controllers/#imagepolicywebhook). Image signatures can also be automatically [verified with an admission controller](/docs/tasks/administer-cluster/verify-signed-artifacts/#verifying-image-signatures-with-admission-controller) at deploy time to validate their authenticity and integrity. Scanning a container image can prevent critical vulnerabilities from being deployed to the cluster alongside the container image. Image scanning should be completed before deploying a container image to a cluster and is usually done as part of the deployment process in a CI/CD pipeline. The purpose of an image scan is to obtain information about possible vulnerabilities and their prevention in the container image, such as a [Common Vulnerability Scoring System (CVSS)](https://www.first.org/cvss/) score. If the result of the image scans is combined with the
| null |
./vendor/kubernetes/content/en/docs/concepts/security/security-checklist.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/security-checklist.md
|
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] | 0.166971
|
as part of the deployment process in a CI/CD pipeline. The purpose of an image scan is to obtain information about possible vulnerabilities and their prevention in the container image, such as a [Common Vulnerability Scoring System (CVSS)](https://www.first.org/cvss/) score. If the result of the image scans is combined with the pipeline compliance rules, only properly patched container images will end up in Production. ## Admission controllers - [ ] An appropriate selection of admission controllers is enabled. - [ ] A pod security policy is enforced by the Pod Security Admission or/and a webhook admission controller. - [ ] The admission chain plugins and webhooks are securely configured. Admission controllers can help improve the security of the cluster. However, they can present risks themselves as they extend the API server and [should be properly secured](/blog/2022/01/19/secure-your-admission-controllers-and-webhooks/). The following lists present a number of admission controllers that could be considered to enhance the security posture of your cluster and application. It includes controllers that may be referenced in other parts of this document. This first group of admission controllers includes plugins [enabled by default](/docs/reference/access-authn-authz/admission-controllers/#which-plugins-are-enabled-by-default), consider to leave them enabled unless you know what you are doing: [`CertificateApproval`](/docs/reference/access-authn-authz/admission-controllers/#certificateapproval) : Performs additional authorization checks to ensure the approving user has permission to approve certificate request. [`CertificateSigning`](/docs/reference/access-authn-authz/admission-controllers/#certificatesigning) : Performs additional authorization checks to ensure the signing user has permission to sign certificate requests. [`CertificateSubjectRestriction`](/docs/reference/access-authn-authz/admission-controllers/#certificatesubjectrestriction) : Rejects any certificate request that specifies a 'group' (or 'organization attribute') of `system:masters`. [`LimitRanger`](/docs/reference/access-authn-authz/admission-controllers/#limitranger) : Enforces the LimitRange API constraints. [`MutatingAdmissionWebhook`](/docs/reference/access-authn-authz/admission-controllers/#mutatingadmissionwebhook) : Allows the use of custom controllers through webhooks, these controllers may mutate requests that they review. [`PodSecurity`](/docs/reference/access-authn-authz/admission-controllers/#podsecurity) : Replacement for Pod Security Policy, restricts security contexts of deployed Pods. [`ResourceQuota`](/docs/reference/access-authn-authz/admission-controllers/#resourcequota) : Enforces resource quotas to prevent over-usage of resources. [`ValidatingAdmissionWebhook`](/docs/reference/access-authn-authz/admission-controllers/#validatingadmissionwebhook) : Allows the use of custom controllers through webhooks, these controllers do not mutate requests that it reviews. The second group includes plugins that are not enabled by default but are in general availability state and are recommended to improve your security posture: [`DenyServiceExternalIPs`](/docs/reference/access-authn-authz/admission-controllers/#denyserviceexternalips) : Rejects all net-new usage of the `Service.spec.externalIPs` field. This is a mitigation for [CVE-2020-8554: Man in the middle using LoadBalancer or ExternalIPs](https://github.com/kubernetes/kubernetes/issues/97076). [`NodeRestriction`](/docs/reference/access-authn-authz/admission-controllers/#noderestriction) : Restricts kubelet's permissions to only modify the pods API resources they own or the node API resource that represent themselves. It also prevents kubelet from using the `node-restriction.kubernetes.io/` annotation, which can be used by an attacker with access to the kubelet's credentials to influence pod placement to the controlled node. The third group includes plugins that are not enabled by default but could be considered for certain use cases: [`AlwaysPullImages`](/docs/reference/access-authn-authz/admission-controllers/#alwayspullimages) : Enforces the usage of the latest version of a tagged image and ensures that the deployer has permissions to use the image. [`ImagePolicyWebhook`](/docs/reference/access-authn-authz/admission-controllers/#imagepolicywebhook) : Allows enforcing additional controls for images through webhooks. ## What's next - [Privilege escalation via Pod creation](/docs/reference/access-authn-authz/authorization/#privilege-escalation-via-pod-creation) warns you about a specific access control risk; check how you're managing that threat. - If you use Kubernetes RBAC, read [RBAC Good Practices](/docs/concepts/security/rbac-good-practices/) for further information on authorization. - [Securing a Cluster](/docs/tasks/administer-cluster/securing-a-cluster/) for information on protecting a cluster from accidental or malicious access. - [Cluster Multi-tenancy guide](/docs/concepts/security/multi-tenancy/) for configuration options recommendations and best practices on multi-tenancy. - [Blog post "A Closer Look at NSA/CISA Kubernetes Hardening Guidance"](/blog/2021/10/05/nsa-cisa-kubernetes-hardening-guidance/#building-secure-container-images) for complementary resource on hardening Kubernetes clusters.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/security-checklist.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/security-checklist.md
|
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] | 0.192332
|
The Pod Security Standards define three different \_policies\_ to broadly cover the security spectrum. These policies are \_cumulative\_ and range from highly-permissive to highly-restrictive. This guide outlines the requirements of each policy. | Profile | Description | | ------ | ----------- | | **Privileged** | Unrestricted policy, providing the widest possible level of permissions. This policy allows for known privilege escalations. | | **Baseline** | Minimally restrictive policy which prevents known privilege escalations. Allows the default (minimally specified) Pod configuration. | | **Restricted** | Heavily restricted policy, following current Pod hardening best practices. | ## Profile Details ### Privileged \*\*The \_Privileged\_ policy is purposely-open, and entirely unrestricted.\*\* This type of policy is typically aimed at system- and infrastructure-level workloads managed by privileged, trusted users. The Privileged policy is defined by an absence of restrictions. If you define a Pod where the Privileged security policy applies, the Pod you define is able to bypass typical container isolation mechanisms. For example, you can define a Pod that has access to the node's host network. ### Baseline \*\*The \_Baseline\_ policy is aimed at ease of adoption for common containerized workloads while preventing known privilege escalations.\*\* This policy is targeted at application operators and developers of non-critical applications. The following listed controls should be enforced/disallowed: {{< note >}} In this table, wildcards (`\*`) indicate all elements in a list. For example, `spec.containers[\*].securityContext` refers to the Security Context object for \_all defined containers\_. If any of the listed containers fails to meet the requirements, the entire pod will fail validation. {{< /note >}} Baseline policy specification | Control | Policy | | --- | --- | | HostProcess | Windows Pods offer the ability to run [HostProcess containers](/docs/tasks/configure-pod-container/create-hostprocess-pod) which enables privileged access to the Windows host machine. Privileged access to the host is disallowed in the Baseline policy. {{< feature-state for\_k8s\_version="v1.26" state="stable" >}} **Restricted Fields** * `spec.securityContext.windowsOptions.hostProcess` * `spec.containers[*].securityContext.windowsOptions.hostProcess` * `spec.initContainers[*].securityContext.windowsOptions.hostProcess` * `spec.ephemeralContainers[*].securityContext.windowsOptions.hostProcess` **Allowed Values** * Undefined/nil * `false` | | Host Namespaces | Sharing the host namespaces must be disallowed. **Restricted Fields** * `spec.hostNetwork` * `spec.hostPID` * `spec.hostIPC` **Allowed Values** * Undefined/nil * `false` | | Privileged Containers | Privileged Pods disable most security mechanisms and must be disallowed. **Restricted Fields** * `spec.containers[*].securityContext.privileged` * `spec.initContainers[*].securityContext.privileged` * `spec.ephemeralContainers[*].securityContext.privileged` **Allowed Values** * Undefined/nil * `false` | | Capabilities | Adding additional capabilities beyond those listed below must be disallowed. **Restricted Fields** * `spec.containers[*].securityContext.capabilities.add` * `spec.initContainers[*].securityContext.capabilities.add` * `spec.ephemeralContainers[*].securityContext.capabilities.add` **Allowed Values** * Undefined/nil * `AUDIT_WRITE` * `CHOWN` * `DAC_OVERRIDE` * `FOWNER` * `FSETID` * `KILL` * `MKNOD` * `NET_BIND_SERVICE` * `SETFCAP` * `SETGID` * `SETPCAP` * `SETUID` * `SYS_CHROOT` | | HostPath Volumes | HostPath volumes must be forbidden. **Restricted Fields** * `spec.volumes[*].hostPath` **Allowed Values** * Undefined/nil | | Host Ports | HostPorts should be disallowed entirely (recommended) or restricted to a known list **Restricted Fields** * `spec.containers[*].ports[*].hostPort` * `spec.initContainers[*].ports[*].hostPort` * `spec.ephemeralContainers[*].ports[*].hostPort` **Allowed Values** * Undefined/nil * Known list (not supported by the built-in [Pod Security Admission controller](/docs/concepts/security/pod-security-admission/)) * `0` | | Host Probes / Lifecycle Hooks (v1.34+) | The Host field in probes and lifecycle hooks must be disallowed. **Restricted Fields** * `spec.containers[*].livenessProbe.httpGet.host` * `spec.containers[*].readinessProbe.httpGet.host` * `spec.containers[*].startupProbe.httpGet.host` * `spec.containers[*].livenessProbe.tcpSocket.host` * `spec.containers[*].readinessProbe.tcpSocket.host` * `spec.containers[*].startupProbe.tcpSocket.host` * `spec.containers[*].lifecycle.postStart.tcpSocket.host`* `spec.containers[*].lifecycle.preStop.tcpSocket.host`* `spec.containers[*].lifecycle.postStart.httpGet.host` * `spec.containers[*].lifecycle.preStop.httpGet.host` * `spec.initContainers[*].livenessProbe.httpGet.host` * `spec.initContainers[*].readinessProbe.httpGet.host` * `spec.initContainers[*].startupProbe.httpGet.host` * `spec.initContainers[*].livenessProbe.tcpSocket.host` * `spec.initContainers[*].readinessProbe.tcpSocket.host` * `spec.initContainers[*].startupProbe.tcpSocket.host` * `spec.initContainers[*].lifecycle.postStart.tcpSocket.host`* `spec.initContainers[*].lifecycle.preStop.tcpSocket.host`* `spec.initContainers[*].lifecycle.postStart.httpGet.host` * `spec.initContainers[*].lifecycle.preStop.httpGet.host` **Allowed Values** * Undefined/nil * "" | | AppArmor | On supported hosts, the `RuntimeDefault` AppArmor profile is applied by default. The baseline policy should prevent overriding or disabling the default AppArmor profile, or restrict overrides to an allowed set of profiles. **Restricted Fields** * `spec.securityContext.appArmorProfile.type` * `spec.containers[*].securityContext.appArmorProfile.type` * `spec.initContainers[*].securityContext.appArmorProfile.type`
| null |
./vendor/kubernetes/content/en/docs/concepts/security/pod-security-standards.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/pod-security-standards.md
|
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] | 0.156247
|
**Allowed Values** * Undefined/nil * "" | | AppArmor | On supported hosts, the `RuntimeDefault` AppArmor profile is applied by default. The baseline policy should prevent overriding or disabling the default AppArmor profile, or restrict overrides to an allowed set of profiles. **Restricted Fields** * `spec.securityContext.appArmorProfile.type` * `spec.containers[*].securityContext.appArmorProfile.type` * `spec.initContainers[*].securityContext.appArmorProfile.type` * `spec.ephemeralContainers[*].securityContext.appArmorProfile.type` **Allowed Values** * Undefined/nil * `RuntimeDefault` * `Localhost` --- * `metadata.annotations["container.apparmor.security.beta.kubernetes.io/*"]` **Allowed Values** * Undefined/nil * `runtime/default` * `localhost/*` | | SELinux | Setting the SELinux type is restricted, and setting a custom SELinux user or role option is forbidden. **Restricted Fields** * `spec.securityContext.seLinuxOptions.type` * `spec.containers[*].securityContext.seLinuxOptions.type` * `spec.initContainers[*].securityContext.seLinuxOptions.type` * `spec.ephemeralContainers[*].securityContext.seLinuxOptions.type` **Allowed Values** * Undefined/"" * `container_t` * `container_init_t` * `container_kvm_t` * `container_engine_t` (since Kubernetes 1.31) --- **Restricted Fields** * `spec.securityContext.seLinuxOptions.user` * `spec.containers[*].securityContext.seLinuxOptions.user` * `spec.initContainers[*].securityContext.seLinuxOptions.user` * `spec.ephemeralContainers[*].securityContext.seLinuxOptions.user` * `spec.securityContext.seLinuxOptions.role` * `spec.containers[*].securityContext.seLinuxOptions.role` * `spec.initContainers[*].securityContext.seLinuxOptions.role` * `spec.ephemeralContainers[*].securityContext.seLinuxOptions.role` **Allowed Values** * Undefined/"" | | `/proc` Mount Type | The default `/proc` masks are set up to reduce attack surface, and should be required. **Restricted Fields** * `spec.containers[*].securityContext.procMount` * `spec.initContainers[*].securityContext.procMount` * `spec.ephemeralContainers[*].securityContext.procMount` **Allowed Values** * Undefined/nil * `Default` | | Seccomp | Seccomp profile must not be explicitly set to `Unconfined`. **Restricted Fields** * `spec.securityContext.seccompProfile.type` * `spec.containers[*].securityContext.seccompProfile.type` * `spec.initContainers[*].securityContext.seccompProfile.type` * `spec.ephemeralContainers[*].securityContext.seccompProfile.type` **Allowed Values** * Undefined/nil * `RuntimeDefault` * `Localhost` | | Sysctls | Sysctls can disable security mechanisms or affect all containers on a host, and should be disallowed except for an allowed "safe" subset. A sysctl is considered safe if it is namespaced in the container or the Pod, and it is isolated from other Pods or processes on the same Node. **Restricted Fields** * `spec.securityContext.sysctls[*].name` **Allowed Values** * Undefined/nil * `kernel.shm_rmid_forced` * `net.ipv4.ip_local_port_range` * `net.ipv4.ip_unprivileged_port_start` * `net.ipv4.tcp_syncookies` * `net.ipv4.ping_group_range` * `net.ipv4.ip_local_reserved_ports` (since Kubernetes 1.27) * `net.ipv4.tcp_keepalive_time` (since Kubernetes 1.29) * `net.ipv4.tcp_fin_timeout` (since Kubernetes 1.29) * `net.ipv4.tcp_keepalive_intvl` (since Kubernetes 1.29) * `net.ipv4.tcp_keepalive_probes` (since Kubernetes 1.29) | ### Restricted \*\*The \_Restricted\_ policy is aimed at enforcing current Pod hardening best practices, at the expense of some compatibility.\*\* It is targeted at operators and developers of security-critical applications, as well as lower-trust users. The following listed controls should be enforced/disallowed: {{< note >}} In this table, wildcards (`\*`) indicate all elements in a list. For example, `spec.containers[\*].securityContext` refers to the Security Context object for \_all defined containers\_. If any of the listed containers fails to meet the requirements, the entire pod will fail validation. {{< /note >}} Restricted policy specification | **Control** | **Policy** | | --- | --- | | *Everything from the Baseline policy* | | | Volume Types | The Restricted policy only permits the following volume types. **Restricted Fields** * `spec.volumes[*]` **Allowed Values** Every item in the `spec.volumes[*]` list must set one of the following fields to a non-null value: * `spec.volumes[*].configMap` * `spec.volumes[*].csi` * `spec.volumes[*].downwardAPI` * `spec.volumes[*].emptyDir` * `spec.volumes[*].ephemeral` * `spec.volumes[*].persistentVolumeClaim` * `spec.volumes[*].projected` * `spec.volumes[*].secret` | | Privilege Escalation (v1.8+) | Privilege escalation (such as via set-user-ID or set-group-ID file mode) should not be allowed. *[This is Linux only policy](#os-specific-policy-controls) in v1.25+ `(spec.os.name != windows)`* **Restricted Fields** * `spec.containers[*].securityContext.allowPrivilegeEscalation` * `spec.initContainers[*].securityContext.allowPrivilegeEscalation` * `spec.ephemeralContainers[*].securityContext.allowPrivilegeEscalation` **Allowed Values** * `false` | | Running as Non-root | Containers must be required to run as non-root users. **Restricted Fields** * `spec.securityContext.runAsNonRoot` * `spec.containers[*].securityContext.runAsNonRoot` * `spec.initContainers[*].securityContext.runAsNonRoot` * `spec.ephemeralContainers[*].securityContext.runAsNonRoot` **Allowed Values** * `true` The container fields may be undefined/`nil` if the pod-level `spec.securityContext.runAsNonRoot` is set to `true`. | | Running as Non-root user (v1.23+) | Containers must not set runAsUser to 0 **Restricted Fields** * `spec.securityContext.runAsUser` * `spec.containers[*].securityContext.runAsUser` * `spec.initContainers[*].securityContext.runAsUser` * `spec.ephemeralContainers[*].securityContext.runAsUser` **Allowed Values** * any non-zero value * `undefined/null` | | Seccomp (v1.19+) | Seccomp profile must be explicitly set to one of the allowed
| null |
./vendor/kubernetes/content/en/docs/concepts/security/pod-security-standards.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/pod-security-standards.md
|
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|
`true`. | | Running as Non-root user (v1.23+) | Containers must not set runAsUser to 0 **Restricted Fields** * `spec.securityContext.runAsUser` * `spec.containers[*].securityContext.runAsUser` * `spec.initContainers[*].securityContext.runAsUser` * `spec.ephemeralContainers[*].securityContext.runAsUser` **Allowed Values** * any non-zero value * `undefined/null` | | Seccomp (v1.19+) | Seccomp profile must be explicitly set to one of the allowed values. Both the `Unconfined` profile and the *absence* of a profile are prohibited. *[This is Linux only policy](#os-specific-policy-controls) in v1.25+ `(spec.os.name != windows)`* **Restricted Fields** * `spec.securityContext.seccompProfile.type` * `spec.containers[*].securityContext.seccompProfile.type` * `spec.initContainers[*].securityContext.seccompProfile.type` * `spec.ephemeralContainers[*].securityContext.seccompProfile.type` **Allowed Values** * `RuntimeDefault` * `Localhost` The container fields may be undefined/`nil` if the pod-level `spec.securityContext.seccompProfile.type` field is set appropriately. Conversely, the pod-level field may be undefined/`nil` if \_all\_ container- level fields are set. | | Capabilities (v1.22+) | Containers must drop `ALL` capabilities, and are only permitted to add back the `NET_BIND_SERVICE` capability. *[This is Linux only policy](#os-specific-policy-controls) in v1.25+ `(.spec.os.name != "windows")`* **Restricted Fields** * `spec.containers[*].securityContext.capabilities.drop` * `spec.initContainers[*].securityContext.capabilities.drop` * `spec.ephemeralContainers[*].securityContext.capabilities.drop` **Allowed Values** * Any list of capabilities that includes `ALL` --- **Restricted Fields** * `spec.containers[*].securityContext.capabilities.add` * `spec.initContainers[*].securityContext.capabilities.add` * `spec.ephemeralContainers[*].securityContext.capabilities.add` **Allowed Values** * Undefined/nil * `NET_BIND_SERVICE` | ## Policy Instantiation Decoupling policy definition from policy instantiation allows for a common understanding and consistent language of policies across clusters, independent of the underlying enforcement mechanism. As mechanisms mature, they will be defined below on a per-policy basis. The methods of enforcement of individual policies are not defined here. [\*\*Pod Security Admission Controller\*\*](/docs/concepts/security/pod-security-admission/) - {{< example file="security/podsecurity-privileged.yaml" >}}Privileged namespace{{< /example >}} - {{< example file="security/podsecurity-baseline.yaml" >}}Baseline namespace{{< /example >}} - {{< example file="security/podsecurity-restricted.yaml" >}}Restricted namespace{{< /example >}} ### Alternatives {{% thirdparty-content %}} Other alternatives for enforcing policies are being developed in the Kubernetes ecosystem, such as: - [Kubewarden](https://github.com/kubewarden) - [Kyverno](https://kyverno.io/policies/pod-security/) - [OPA Gatekeeper](https://github.com/open-policy-agent/gatekeeper) ## Pod OS field Kubernetes lets you use nodes that run either Linux or Windows. You can mix both kinds of node in one cluster. Windows in Kubernetes has some limitations and differentiators from Linux-based workloads. Specifically, many of the Pod `securityContext` fields [have no effect on Windows](/docs/concepts/windows/intro/#compatibility-v1-pod-spec-containers-securitycontext). {{< note >}} Kubelets prior to v1.24 don't enforce the pod OS field, and if a cluster has nodes on versions earlier than v1.24 the Restricted policies should be pinned to a version prior to v1.25. {{< /note >}} ### Restricted Pod Security Standard changes Another important change, made in Kubernetes v1.25 is that the \_Restricted\_ policy has been updated to use the `pod.spec.os.name` field. Based on the OS name, certain policies that are specific to a particular OS can be relaxed for the other OS. #### OS-specific policy controls Restrictions on the following controls are only required if `.spec.os.name` is not `windows`: - Privilege Escalation - Seccomp - Linux Capabilities ## User namespaces User Namespaces are a Linux-only feature to run workloads with increased isolation. How they work together with Pod Security Standards is described in the [documentation](/docs/concepts/workloads/pods/user-namespaces#integration-with-pod-security-admission-checks) for Pods that use user namespaces. ## FAQ ### Why isn't there a profile between Privileged and Baseline? The three profiles defined here have a clear linear progression from most secure (Restricted) to least secure (Privileged), and cover a broad set of workloads. Privileges required above the Baseline policy are typically very application specific, so we do not offer a standard profile in this niche. This is not to say that the privileged profile should always be used in this case, but that policies in this space need to be defined on a case-by-case basis. SIG Auth may reconsider this position in the future, should a clear need for other profiles arise. ### What's the difference between a security profile and a security context? [Security Contexts](/docs/tasks/configure-pod-container/security-context/) configure Pods
| null |
./vendor/kubernetes/content/en/docs/concepts/security/pod-security-standards.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/pod-security-standards.md
|
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|
in this case, but that policies in this space need to be defined on a case-by-case basis. SIG Auth may reconsider this position in the future, should a clear need for other profiles arise. ### What's the difference between a security profile and a security context? [Security Contexts](/docs/tasks/configure-pod-container/security-context/) configure Pods and Containers at runtime. Security contexts are defined as part of the Pod and container specifications in the Pod manifest, and represent parameters to the container runtime. Security profiles are control plane mechanisms to enforce specific settings in the Security Context, as well as other related parameters outside the Security Context. As of July 2021, [Pod Security Policies](/docs/concepts/security/pod-security-policy/) are deprecated in favor of the built-in [Pod Security Admission Controller](/docs/concepts/security/pod-security-admission/). ### What about sandboxed Pods? There is currently no API standard that controls whether a Pod is considered sandboxed or not. Sandbox Pods may be identified by the use of a sandboxed runtime (such as gVisor or Kata Containers), but there is no standard definition of what a sandboxed runtime is. The protections necessary for sandboxed workloads can differ from others. For example, the need to restrict privileged permissions is lessened when the workload is isolated from the underlying kernel. This allows for workloads requiring heightened permissions to still be isolated. Additionally, the protection of sandboxed workloads is highly dependent on the method of sandboxing. As such, no single recommended profile is recommended for all sandboxed workloads.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/pod-security-standards.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/pod-security-standards.md
|
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] | 0.163215
|
{{% alert title="Removed feature" color="warning" %}} PodSecurityPolicy was [deprecated](/blog/2021/04/08/kubernetes-1-21-release-announcement/#podsecuritypolicy-deprecation) in Kubernetes v1.21, and removed from Kubernetes in v1.25. {{% /alert %}} Instead of using PodSecurityPolicy, you can enforce similar restrictions on Pods using either or both: - [Pod Security Admission](/docs/concepts/security/pod-security-admission/) - a 3rd party admission plugin, that you deploy and configure yourself For a migration guide, see [Migrate from PodSecurityPolicy to the Built-In PodSecurity Admission Controller](/docs/tasks/configure-pod-container/migrate-from-psp/). For more information on the removal of this API, see [PodSecurityPolicy Deprecation: Past, Present, and Future](/blog/2021/04/06/podsecuritypolicy-deprecation-past-present-and-future/). If you are not running Kubernetes v{{< skew currentVersion >}}, check the documentation for your version of Kubernetes.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/pod-security-policy.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/pod-security-policy.md
|
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] | 0.140916
|
This page describes security considerations and best practices specific to the Linux operating system. ## Protection for Secret data on nodes On Linux nodes, memory-backed volumes (such as [`secret`](/docs/concepts/configuration/secret/) volume mounts, or [`emptyDir`](/docs/concepts/storage/volumes/#emptydir) with `medium: Memory`) are implemented with a `tmpfs` filesystem. If you have swap configured and use an older Linux kernel (or a current kernel and an unsupported configuration of Kubernetes), \*\*memory\*\* backed volumes can have data written to persistent storage. The Linux kernel officially supports the `noswap` option from version 6.3, therefore it is recommended the used kernel version is 6.3 or later, or supports the `noswap` option via a backport, if swap is enabled on the node. Read [swap memory management](/docs/concepts/cluster-administration/swap-memory-management/#memory-backed-volumes) for more info.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/linux-security.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/linux-security.md
|
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|
This page describes security considerations and best practices specific to the Windows operating system. ## Protection for Secret data on nodes On Windows, data from Secrets are written out in clear text onto the node's local storage (as compared to using tmpfs / in-memory filesystems on Linux). As a cluster operator, you should take both of the following additional measures: 1. Use file ACLs to secure the Secrets' file location. 1. Apply volume-level encryption using [BitLocker](https://docs.microsoft.com/windows/security/information-protection/bitlocker/bitlocker-how-to-deploy-on-windows-server). ## Container users [RunAsUsername](/docs/tasks/configure-pod-container/configure-runasusername) can be specified for Windows Pods or containers to execute the container processes as specific user. This is roughly equivalent to [RunAsUser](/docs/concepts/security/pod-security-policy/#users-and-groups). Windows containers offer two default user accounts, ContainerUser and ContainerAdministrator. The differences between these two user accounts are covered in [When to use ContainerAdmin and ContainerUser user accounts](https://docs.microsoft.com/virtualization/windowscontainers/manage-containers/container-security#when-to-use-containeradmin-and-containeruser-user-accounts) within Microsoft's \_Secure Windows containers\_ documentation. Local users can be added to container images during the container build process. {{< note >}} \* [Nano Server](https://hub.docker.com/\_/microsoft-windows-nanoserver) based images run as `ContainerUser` by default \* [Server Core](https://hub.docker.com/\_/microsoft-windows-servercore) based images run as `ContainerAdministrator` by default {{< /note >}} Windows containers can also run as Active Directory identities by utilizing [Group Managed Service Accounts](/docs/tasks/configure-pod-container/configure-gmsa/) ## Pod-level security isolation Linux-specific pod security context mechanisms (such as SELinux, AppArmor, Seccomp, or custom POSIX capabilities) are not supported on Windows nodes. Privileged containers are [not supported](/docs/concepts/windows/intro/#compatibility-v1-pod-spec-containers-securitycontext) on Windows. Instead [HostProcess containers](/docs/tasks/configure-pod-container/create-hostprocess-pod) can be used on Windows to perform many of the tasks performed by privileged containers on Linux.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/windows-security.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/windows-security.md
|
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] | 0.0992
|
This section of the Kubernetes documentation aims to help you learn to run workloads more securely, and about the essential aspects of keeping a Kubernetes cluster secure. Kubernetes is based on a cloud-native architecture, and draws on advice from the {{< glossary\_tooltip text="CNCF" term\_id="cncf" >}} about good practice for cloud native information security. Read [Cloud Native Security and Kubernetes](/docs/concepts/security/cloud-native-security/) for the broader context about how to secure your cluster and the applications that you're running on it. ## Kubernetes security mechanisms {#security-mechanisms} Kubernetes includes several APIs and security controls, as well as ways to define [policies](#policies) that can form part of how you manage information security. ### Control plane protection A key security mechanism for any Kubernetes cluster is to [control access to the Kubernetes API](/docs/concepts/security/controlling-access). Kubernetes expects you to configure and use TLS to provide [data encryption in transit](/docs/tasks/tls/managing-tls-in-a-cluster/) within the control plane, and between the control plane and its clients. You can also enable [encryption at rest](/docs/tasks/administer-cluster/encrypt-data/) for the data stored within Kubernetes control plane; this is separate from using encryption at rest for your own workloads' data, which might also be a good idea. ### Secrets The [Secret](/docs/concepts/configuration/secret/) API provides basic protection for configuration values that require confidentiality. ### Workload protection Enforce [Pod security standards](/docs/concepts/security/pod-security-standards/) to ensure that Pods and their containers are isolated appropriately. You can also use [RuntimeClasses](/docs/concepts/containers/runtime-class) to define custom isolation if you need it. [Network policies](/docs/concepts/services-networking/network-policies/) let you control network traffic between Pods, or between Pods and the network outside your cluster. You can deploy security controls from the wider ecosystem to implement preventative or detective controls around Pods, their containers, and the images that run in them. ### Admission control {#admission-control} [Admission controllers](/docs/reference/access-authn-authz/admission-controllers/) are plugins that intercept Kubernetes API requests and can validate or mutate the requests based on specific fields in the request. Thoughtfully designing these controllers helps to avoid unintended disruptions as Kubernetes APIs change across version updates. For design considerations, see [Admission Webhook Good Practices](/docs/concepts/cluster-administration/admission-webhooks-good-practices/). ### Auditing Kubernetes [audit logging](/docs/tasks/debug/debug-cluster/audit/) provides a security-relevant, chronological set of records documenting the sequence of actions in a cluster. The cluster audits the activities generated by users, by applications that use the Kubernetes API, and by the control plane itself. ## Cloud provider security {{% thirdparty-content vendor="true" %}} If you are running a Kubernetes cluster on your own hardware or a different cloud provider, consult your documentation for security best practices. Here are links to some of the popular cloud providers' security documentation: {{< table caption="Cloud provider security" >}} IaaS Provider | Link | -------------------- | ------------ | Alibaba Cloud | https://www.alibabacloud.com/trust-center | Amazon Web Services | https://aws.amazon.com/security | Google Cloud Platform | https://cloud.google.com/security | Huawei Cloud | https://www.huaweicloud.com/intl/en-us/securecenter/overallsafety | IBM Cloud | https://www.ibm.com/cloud/security | Microsoft Azure | https://docs.microsoft.com/en-us/azure/security/azure-security | Oracle Cloud Infrastructure | https://www.oracle.com/security | Tencent Cloud | https://www.tencentcloud.com/solutions/data-security-and-information-protection | VMware vSphere | https://www.vmware.com/solutions/security/hardening-guides | {{< /table >}} ## Policies You can define security policies using Kubernetes-native mechanisms, such as [NetworkPolicy](/docs/concepts/services-networking/network-policies/) (declarative control over network packet filtering) or [ValidatingAdmissionPolicy](/docs/reference/access-authn-authz/validating-admission-policy/) (declarative restrictions on what changes someone can make using the Kubernetes API). However, you can also rely on policy implementations from the wider ecosystem around Kubernetes. Kubernetes provides extension mechanisms to let those ecosystem projects implement their own policy controls on source code review, container image approval, API access controls, networking, and more. For more information about policy mechanisms and Kubernetes, read [Policies](/docs/concepts/policy/). ## {{% heading "whatsnext" %}} Learn about related Kubernetes security topics: \* [Securing your cluster](/docs/tasks/administer-cluster/securing-a-cluster/) \* [Known vulnerabilities](/docs/reference/issues-security/official-cve-feed/) in Kubernetes (and links to further information) \* [Data encryption in transit](/docs/tasks/tls/managing-tls-in-a-cluster/) for the control plane \* [Data encryption at rest](/docs/tasks/administer-cluster/encrypt-data/) \*
| null |
./vendor/kubernetes/content/en/docs/concepts/security/_index.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/_index.md
|
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] | 0.167614
|
For more information about policy mechanisms and Kubernetes, read [Policies](/docs/concepts/policy/). ## {{% heading "whatsnext" %}} Learn about related Kubernetes security topics: \* [Securing your cluster](/docs/tasks/administer-cluster/securing-a-cluster/) \* [Known vulnerabilities](/docs/reference/issues-security/official-cve-feed/) in Kubernetes (and links to further information) \* [Data encryption in transit](/docs/tasks/tls/managing-tls-in-a-cluster/) for the control plane \* [Data encryption at rest](/docs/tasks/administer-cluster/encrypt-data/) \* [Controlling Access to the Kubernetes API](/docs/concepts/security/controlling-access) \* [Network policies](/docs/concepts/services-networking/network-policies/) for Pods \* [Secrets in Kubernetes](/docs/concepts/configuration/secret/) \* [Pod security standards](/docs/concepts/security/pod-security-standards/) \* [RuntimeClasses](/docs/concepts/containers/runtime-class) Learn the context: \* [Cloud Native Security and Kubernetes](/docs/concepts/security/cloud-native-security/) Get certified: \* [Certified Kubernetes Security Specialist](https://training.linuxfoundation.org/certification/certified-kubernetes-security-specialist/) certification and official training course. Read more in this section:
| null |
./vendor/kubernetes/content/en/docs/concepts/security/_index.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/_index.md
|
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|
The Kubernetes {{< glossary\_tooltip text="scheduler" term\_id="kube-scheduler" >}} is one of the critical components of the {{< glossary\_tooltip text="control plane" term\_id="control-plane" >}}. This document covers how to improve the security posture of the Scheduler. A misconfigured scheduler can have security implications. Such a scheduler can target specific nodes and evict the workloads or applications that are sharing the node and its resources. This can aid an attacker with a [Yo-Yo attack](https://arxiv.org/abs/2105.00542): an attack on a vulnerable autoscaler. ## kube-scheduler configuration ### Scheduler authentication & authorization command line options When setting up authentication configuration, it should be made sure that kube-scheduler's authentication remains consistent with kube-api-server's authentication. If any request has missing authentication headers, the [authentication should happen through the kube-api-server allowing all authentication to be consistent in the cluster](/docs/tasks/extend-kubernetes/configure-aggregation-layer/#original-request-username-and-group). - `authentication-kubeconfig`: Make sure to provide a proper kubeconfig so that the scheduler can retrieve authentication configuration options from the API Server. This kubeconfig file should be protected with strict file permissions. - `authentication-tolerate-lookup-failure`: Set this to `false` to make sure the scheduler \_always\_ looks up its authentication configuration from the API server. - `authentication-skip-lookup`: Set this to `false` to make sure the scheduler \_always\_ looks up its authentication configuration from the API server. - `authorization-always-allow-paths`: These paths should respond with data that is appropriate for anonymous authorization. Defaults to `/healthz,/readyz,/livez`. - `profiling`: Set to `false` to disable the profiling endpoints which are provide debugging information but which should not be enabled on production clusters as they present a risk of denial of service or information leakage. The `--profiling` argument is deprecated and can now be provided through the [KubeScheduler DebuggingConfiguration](https://kubernetes.io/docs/reference/config-api/kube-scheduler-config.v1/#DebuggingConfiguration). Profiling can be disabled through the kube-scheduler config by setting `enableProfiling` to `false`. - `requestheader-client-ca-file`: Avoid passing this argument. ### Scheduler networking command line options - `bind-address`: In most cases, the kube-scheduler does not need to be externally accessible. Setting the bind address to `localhost` is a secure practice. - `permit-address-sharing`: Set this to `false` to disable connection sharing through `SO\_REUSEADDR`. `SO\_REUSEADDR` can lead to reuse of terminated connections that are in `TIME\_WAIT` state. - `permit-port-sharing`: Default `false`. Use the default unless you are confident you understand the security implications. ### Scheduler TLS command line options - `tls-cipher-suites`: Always provide a list of preferred cipher suites. This ensures encryption never happens with insecure cipher suites. ## Scheduling configurations for custom schedulers When using custom schedulers based on the Kubernetes scheduling code, cluster administrators need to be careful with plugins that use the `queueSort`, `prefilter`, `filter`, or `permit` [extension points](/docs/reference/scheduling/config/#extension-points). These extension points control various stages of a scheduling process, and the wrong configuration can impact the kube-scheduler's behavior in your cluster. ### Key considerations - Exactly one plugin that uses the `queueSort` extension point can be enabled at a time. Any plugins that use `queueSort` should be scrutinized. - Plugins that implement the `prefilter` or `filter` extension point can potentially mark all nodes as unschedulable. This can bring scheduling of new pods to a halt. - Plugins that implement the `permit` extension point can prevent or delay the binding of a Pod. Such plugins should be thoroughly reviewed by the cluster administrator. When using a plugin that is not one of the [default plugins](/docs/reference/scheduling/config/#scheduling-plugins), consider disabling the `queueSort`, `filter` and `permit` extension points as follows: ```yaml apiVersion: kubescheduler.config.k8s.io/v1 kind: KubeSchedulerConfiguration profiles: - schedulerName: my-scheduler plugins: # Disable specific plugins for different extension points # You can disable all plugins for an extension point using "\*" queueSort: disabled: - name: "\*" # Disable all queueSort plugins # - name: "PrioritySort" # Disable specific queueSort plugin filter: disabled: - name: "\*" # Disable
| null |
./vendor/kubernetes/content/en/docs/concepts/security/hardening-guide/scheduler.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/hardening-guide/scheduler.md
|
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] | 0.122002
|
- schedulerName: my-scheduler plugins: # Disable specific plugins for different extension points # You can disable all plugins for an extension point using "\*" queueSort: disabled: - name: "\*" # Disable all queueSort plugins # - name: "PrioritySort" # Disable specific queueSort plugin filter: disabled: - name: "\*" # Disable all filter plugins # - name: "NodeResourcesFit" # Disable specific filter plugin permit: disabled: - name: "\*" # Disables all permit plugins # - name: "TaintToleration" # Disable specific permit plugin ``` This creates a scheduler profile ` my-scheduler`. Whenever the `.spec` of a Pod does not have a value for `.spec.schedulerName`, the kube-scheduler runs for that Pod, using its main configuration, and default plugins. If you define a Pod with `.spec.schedulerName` set to `my-scheduler`, the kube-scheduler runs but with a custom configuration; in that custom configuration, the `queueSort`, `filter` and `permit` extension points are disabled. If you use this KubeSchedulerConfiguration, and don't run any custom scheduler, and you then define a Pod with `.spec.schedulerName` set to `nonexistent-scheduler` (or any other scheduler name that doesn't exist in your cluster), no events would be generated for a pod. ## Disallow labeling nodes A cluster administrator should ensure that cluster users cannot label the nodes. A malicious actor can use `nodeSelector` to schedule workloads on nodes where those workloads should not be present.
| null |
./vendor/kubernetes/content/en/docs/concepts/security/hardening-guide/scheduler.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/hardening-guide/scheduler.md
|
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] | 0.132727
|
Selecting the appropriate authentication mechanism(s) is a crucial aspect of securing your cluster. Kubernetes provides several built-in mechanisms, each with its own strengths and weaknesses that should be carefully considered when choosing the best authentication mechanism for your cluster. In general, it is recommended to enable as few authentication mechanisms as possible to simplify user management and prevent cases where users retain access to a cluster that is no longer required. It is important to note that Kubernetes does not have an in-built user database within the cluster. Instead, it takes user information from the configured authentication system and uses that to make authorization decisions. Therefore, to audit user access, you need to review credentials from every configured authentication source. For production clusters with multiple users directly accessing the Kubernetes API, it is recommended to use external authentication sources such as OIDC. The internal authentication mechanisms, such as client certificates and service account tokens, described below, are not suitable for this use case. ## X.509 client certificate authentication {#x509-client-certificate-authentication} Kubernetes leverages [X.509 client certificate](/docs/reference/access-authn-authz/authentication/#x509-client-certificates) authentication for system components, such as when the kubelet authenticates to the API Server. While this mechanism can also be used for user authentication, it might not be suitable for production use due to several restrictions: - Client certificates cannot be individually revoked. Once compromised, a certificate can be used by an attacker until it expires. To mitigate this risk, it is recommended to configure short lifetimes for user authentication credentials created using client certificates. - If a certificate needs to be invalidated, the certificate authority must be re-keyed, which can introduce availability risks to the cluster. - There is no permanent record of client certificates created in the cluster. Therefore, all issued certificates must be recorded if you need to keep track of them. - Private keys used for client certificate authentication cannot be password-protected. Anyone who can read the file containing the key will be able to make use of it. - Using client certificate authentication requires a direct connection from the client to the API server without any intervening TLS termination points, which can complicate network architectures. - Group data is embedded in the `O` value of the client certificate, which means the user's group memberships cannot be changed for the lifetime of the certificate. ## Static token file {#static-token-file} Although Kubernetes allows you to load credentials from a [static token file](/docs/reference/access-authn-authz/authentication/#static-token-file) located on the control plane node disks, this approach is not recommended for production servers due to several reasons: - Credentials are stored in clear text on control plane node disks, which can be a security risk. - Changing any credential requires a restart of the API server process to take effect, which can impact availability. - There is no mechanism available to allow users to rotate their credentials. To rotate a credential, a cluster administrator must modify the token on disk and distribute it to the users. - There is no lockout mechanism available to prevent brute-force attacks. ## Bootstrap tokens {#bootstrap-tokens} [Bootstrap tokens](/docs/reference/access-authn-authz/bootstrap-tokens/) are used for joining nodes to clusters and are not recommended for user authentication due to several reasons: - They have hard-coded group memberships that are not suitable for general use, making them unsuitable for authentication purposes. - Manually generating bootstrap tokens can lead to weak tokens that can be guessed by an attacker, which can be a security risk. - There is no lockout mechanism available to prevent brute-force attacks, making it easier for attackers to guess or crack the token. ## ServiceAccount secret tokens {#serviceaccount-secret-tokens} [Service account secrets](/docs/reference/access-authn-authz/service-accounts-admin/#manual-secret-management-for-serviceaccounts) are available as an option to
| null |
./vendor/kubernetes/content/en/docs/concepts/security/hardening-guide/authentication-mechanisms.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/hardening-guide/authentication-mechanisms.md
|
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] | 0.081015
|
tokens that can be guessed by an attacker, which can be a security risk. - There is no lockout mechanism available to prevent brute-force attacks, making it easier for attackers to guess or crack the token. ## ServiceAccount secret tokens {#serviceaccount-secret-tokens} [Service account secrets](/docs/reference/access-authn-authz/service-accounts-admin/#manual-secret-management-for-serviceaccounts) are available as an option to allow workloads running in the cluster to authenticate to the API server. In Kubernetes < 1.23, these were the default option, however, they are being replaced with TokenRequest API tokens. While these secrets could be used for user authentication, they are generally unsuitable for a number of reasons: - They cannot be set with an expiry and will remain valid until the associated service account is deleted. - The authentication tokens are visible to any cluster user who can read secrets in the namespace that they are defined in. - Service accounts cannot be added to arbitrary groups complicating RBAC management where they are used. ## TokenRequest API tokens {#tokenrequest-api-tokens} The TokenRequest API is a useful tool for generating short-lived credentials for service authentication to the API server or third-party systems. However, it is not generally recommended for user authentication as there is no revocation method available, and distributing credentials to users in a secure manner can be challenging. When using TokenRequest tokens for service authentication, it is recommended to implement a short lifespan to reduce the impact of compromised tokens. ## OpenID Connect token authentication {#openid-connect-token-authentication} Kubernetes supports integrating external authentication services with the Kubernetes API using [OpenID Connect (OIDC)](/docs/reference/access-authn-authz/authentication/#openid-connect-tokens). There is a wide variety of software that can be used to integrate Kubernetes with an identity provider. However, when using OIDC authentication in Kubernetes, it is important to consider the following hardening measures: - The software installed in the cluster to support OIDC authentication should be isolated from general workloads as it will run with high privileges. - Some Kubernetes managed services are limited in the OIDC providers that can be used. - As with TokenRequest tokens, OIDC tokens should have a short lifespan to reduce the impact of compromised tokens. ## Webhook token authentication {#webhook-token-authentication} [Webhook token authentication](/docs/reference/access-authn-authz/authentication/#webhook-token-authentication) is another option for integrating external authentication providers into Kubernetes. This mechanism allows for an authentication service, either running inside the cluster or externally, to be contacted for an authentication decision over a webhook. It is important to note that the suitability of this mechanism will likely depend on the software used for the authentication service, and there are some Kubernetes-specific considerations to take into account. To configure Webhook authentication, access to control plane server filesystems is required. This means that it will not be possible with Managed Kubernetes unless the provider specifically makes it available. Additionally, any software installed in the cluster to support this access should be isolated from general workloads, as it will run with high privileges. ## Authenticating proxy {#authenticating-proxy} Another option for integrating external authentication systems into Kubernetes is to use an [authenticating proxy](/docs/reference/access-authn-authz/authentication/#authenticating-proxy). With this mechanism, Kubernetes expects to receive requests from the proxy with specific header values set, indicating the username and group memberships to assign for authorization purposes. It is important to note that there are specific considerations to take into account when using this mechanism. Firstly, securely configured TLS must be used between the proxy and Kubernetes API server to mitigate the risk of traffic interception or sniffing attacks. This ensures that the communication between the proxy and Kubernetes API server is secure. Secondly, it is important to be aware that an attacker who is able to modify the headers of the request may be able to gain unauthorized access
| null |
./vendor/kubernetes/content/en/docs/concepts/security/hardening-guide/authentication-mechanisms.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/hardening-guide/authentication-mechanisms.md
|
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] | 0.185583
|
mitigate the risk of traffic interception or sniffing attacks. This ensures that the communication between the proxy and Kubernetes API server is secure. Secondly, it is important to be aware that an attacker who is able to modify the headers of the request may be able to gain unauthorized access to Kubernetes resources. As such, it is important to ensure that the headers are properly secured and cannot be tampered with. ## {{% heading "whatsnext" %}} - [User Authentication](/docs/reference/access-authn-authz/authentication/) - [Authenticating with Bootstrap Tokens](/docs/reference/access-authn-authz/bootstrap-tokens/) - [kubelet Authentication](/docs/reference/access-authn-authz/kubelet-authn-authz/#kubelet-authentication) - [Authenticating with Service Account Tokens](/docs/reference/access-authn-authz/service-accounts-admin/#bound-service-account-tokens)
| null |
./vendor/kubernetes/content/en/docs/concepts/security/hardening-guide/authentication-mechanisms.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/security/hardening-guide/authentication-mechanisms.md
|
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] | 0.123805
|
{{< feature-state feature\_gate\_name="NodeDeclaredFeatures" >}} Kubernetes nodes use \_declared features\_ to report the availability of specific features that are new or feature-gated. Control plane components utilize this information to make better decisions. The kube-scheduler, via the `NodeDeclaredFeatures` plugin, ensures pods are only placed on nodes that explicitly support the features the pod requires. Additionally, the `NodeDeclaredFeatureValidator` admission controller validates pod updates against a node's declared features. This mechanism helps manage version skew and improve cluster stability, especially during cluster upgrades or in mixed-version environments where nodes might not all have the same features enabled. This is intended for Kubernetes feature developers introducing new node-level features and works in the background; application developers deploying Pods do not need to interact with this framework directly. ## How it Works 1. \*\*Kubelet Feature Reporting:\*\* At startup, the kubelet on each node detects which managed Kubernetes features are currently enabled and reports them in the `.status.declaredFeatures` field of the Node. Only features under active development are included in this field. 2. \*\*Scheduler Filtering:\*\* The default kube-scheduler uses the `NodeDeclaredFeatures` plugin. This plugin: \* In the `PreFilter` stage, checks the `PodSpec` to infer the set of node features required by the pod. \* In the `Filter` stage, checks if the features listed in the node's `.status.declaredFeatures` satisfy the requirements inferred for the Pod. Pods will not be scheduled on nodes lacking the required features. Custom schedulers can also utilize the `.status.declaredFeatures` field to enforce similar constraints. 3. \*\*Admission Control:\*\* The `nodedeclaredfeaturevalidator` admission controller can reject Pods that require features not declared by the node they are bound to, preventing issues during pod updates. ## Enabling node declared features To use Node Declared Features, the `NodeDeclaredFeatures` [feature gate](/docs/reference/command-line-tools-reference/feature-gates/#NodeDeclaredFeatures) must be enabled on the `kube-apiserver`, `kube-scheduler`, and `kubelet` components. ## {{% heading "whatsnext" %}} \* Read the KEP for more details: [KEP-5328: Node Declared Features](https://github.com/kubernetes/enhancements/blob/6d3210f7dd5d547c8f7f6a33af6a09eb45193cd7/keps/sig-node/5328-node-declared-features/README.md) \* Read about the [`NodeDeclaredFeatureValidator` admission controller](/docs/reference/access-authn-authz/admission-controllers/#nodedeclaredfeaturevalidator).
| null |
./vendor/kubernetes/content/en/docs/concepts/scheduling-eviction/node-declared-features.md
|
https://github.com/kubernetes/website/blob/main//content/en/docs/concepts/scheduling-eviction/node-declared-features.md
|
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] | 0.17408
|
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