cwielenb/CNCF-Dataset huggingface dataset:
Project: Traefik (Orchestration & Management / API Gateway)
File: errorpages.md

title: "Traefik Errors Documentation" description: "In Traefik Proxy, the Errors middleware returns custom pages according to configured ranges of HTTP Status codes. Read the technical documentation." It Has Never Been Easier to Say That Something Went Wrong {: .subtitle } The Errors middleware returns a custom page in lieu of the default, according to configured ranges of HTTP Status codes. !!! important The error page itself is not hosted by Traefik. ```yaml tab="Docker & Swarm" labels: "traefik.http.middlewares.test-errors.errors.status=500,501,503,505-599" "traefik.http.middlewares.test-errors.errors.service=serviceError" "traefik.http.middlewares.test-errors.errors.query=/{status}.html" ``` ```yaml tab="Kubernetes" apiVersion: traefik.io/v1alpha1 kind: Middleware metadata: name: test-errors spec: errors: status: "500" "501" "503" "505-599" query: /{status}.html service: name: whoami port: 80 ``` ```yaml tab="Consul Catalog" "traefik.http.middlewares.test-errors.errors.status=500,501,503,505-599" "traefik.http.middlewares.test-errors.errors.service=serviceError" "traefik.http.middlewares.test-errors.errors.query=/{status}.html" ``` ```yaml tab="File (YAML)" http: middlewares: test-errors: errors: status: "500" "501" "503" "505-599" service: serviceError query: "/{status}.html" services: ``` ```toml tab="File (TOML)" [http.middlewares] [http.middlewares.test-errors.errors] status = ["500","501","503","505-599"] service = "serviceError" query = "/{status}.html" [http.services] ``` !!! note "" In this example, the error page URL is based on the status code (`query=/{status}.html`). The `status` option defines which status or range of statuses should result in an error page. The status code ranges are inclusive (`505-599` will trigger with every code between `505` and `599`, `505` and `599` included). !!! note "" You can define either a status code as a number (`500`), as multiple comma-separated numbers (`500,502`), as ranges by separating two codes with a dash (`505-599`), or a combination of the two (`404,418,505-599`). The comma-separated syntax is only available for label-based providers. The examples above demonstrate which syntax is appropriate for each provider. The service that will serve the new requested error page. !!! note "" In Kubernetes, you need to reference a Kubernetes Service instead of a Traefik service. !!! info "Host Header" By default, the client `Host` header value is forwarded to the configured error . To forward the `Host` value corresponding to the configured error service URL, the option must be set to `false`. The URL for the error page (hosted by )). There are multiple variables that can be placed in the `query` option to insert values in the URL. The table below lists all the available variables and their associated values. | Variable | Value | ||--| | `{status}` | The response status code. | | `{url}` | The request URL. |
Project: MetalLB (Orchestration & Management / Service Proxy)
File: maturity.md

title: Project Maturity weight: 4 MetalLB is currently in beta. MetalLB is being used in several production and non-production clusters, by several people and companies. It is bundled together with the major Kubernetes distributions for on premise deployments. Based on the infrequency of bug reports, MetalLB appears to be robust in those deployments. In any case, no one is perfect and issues might happen. Please file bugs! We want to hear from you and address pain points. The codebase has reasonable test coverage, and a good amount of end-to-end tests which covers against most part of regressions. Despite that, edge cases may have bugs, so if you find unexpected behaviours, please consider . The configuration format may change in backwards-incompatible ways as the project is refactored to support additional routing protocols and features. Backward-incompatible changes to configuration will be rolled out in a "make before break" fashion: first there will be a release that understands the new and the old configuration format, so that you can upgrade your configuration separately from the code. The next release after that removes support for the old configuration format. Release notes during beta will highlight any required changes to configuration when upgrading between versions, and give advance warning of removals planned for the following version. The MetalLB maintainers aim to keep compatibility with the supported versions of Kubernetes. If a kubernetes version is not supported anymore, the compatibility is provided on best effort basis. Documentation exists, but hasn't been battle-tested by many readers unfamiliar with the project. As such, it may be incomplete or confusing in parts. If you find shortcomings in the documentation, please file bugs! Your perspective is very valuable, and we want to hear about what works and what doesn't. The MetalLB copyright was owned by Google, until March 2019. However, it was never an official Google project. The project doesn't have any form of corporate sponsorship. MetalLB was created by , working on MetalLB in their spare time as motivation allows. The original author has now been empowering a [team of maintainers]({{% relref "community/_index.md" %}}#contributing) to assist with moving the project forward. Most support and new feature development is at the mercy of the availability of this small group, so you should set your expectations accordingly. If you would like to help improve this balance, [contributions]({{% relref "community/_index.md" %}}#contributing) are very welcome! In addition to code contributions, donation of resources (hardware, cloud environments...) are also very welcome: the more different conditions we can test MetalLB in, the fewer bugs and regressions will be introduced!
Project: Volcano (Orchestration & Management / Scheduling & Orchestration)
File: version-release.md

Version plan is usually put into practice half month before the latest version released. According to the feedback of community, we will collect requirements which are from classical scenes or common demands in the last three months. All collected requirements will be listed in the requirements list, reviewed initially, and prioritized. Requirement list will be submitted to the community weekly meeting for discussion. Community members will evaluate the scenarios, rationality, feature design points, development workload and other dimensions of the requirements. After the discussion, part of requirements will be settled as version features and published in the roadmap. Generally, we will release an official version such as 1.X every three months. Bug fix versions such as 1.X.X are released any time we consider it necessary after some important bug fixed. In order to ensure the quality of master branch, repository will be frozen two weeks before official version released, during which only bug fix PRs are admitted to be merged. Alpha and Beta version also will be released in the period. During the code frozen, a new branch whose name like `release-X.X.X` will be checkout to merge bug fix and published release. We will publish every release and related docker images. Users can find release in the release list and docker images in the DockerHub. After every release published, some users and community members will be invited to join the Beta test. Any contributor is welcome to take part in the test. We will collect bug feedback and fix them immediately. Usually, this work will be going one week before official release published. After all the work above finished, official release will be published with note about feature introduction.
Project: KrakenD (Orchestration & Management / API Gateway)
File: SECURITY.md

Lura only fixes the latest version of the software, and does not patch prior versions. Please email security@krakend.io with your discovery. As soon as we read and understand your finding we will provide an answer with next steps and possible timelines. We want to thank you in advance for the time you have spent to follow this issue, as it helps all open source users. We develop our software in the open with the help of a global community of developers and contributors with whom we share a common understanding and trust in the free exchange of knowledge. The Lura Project DOES NOT provide cash awards for discovered vulnerabilities at this time. Thank you
Project: Clusternet (Orchestration & Management / Scheduling & Orchestration)
File: READEME.md

If you want to use to interact with Clusternet, you only need to insert below `wrapperFunc` in your codes, while the rest remains the same. ```go // This is the ONLY place you need to wrap for Clusternet config.Wrap(func(rt http.RoundTripper) http.RoundTripper { return clientgo.NewClusternetTransport(config.Host, rt) }) ``` You can follow for a quick start.
Project: Avro (Orchestration & Management / Remote Procedure Call)
File: new-committer-zoltan-csizmadia.md

title: "New committer: Zoltan Csizmadia" linkTitle: "New committer: Zoltan Csizmadia" date: 2022-03-29 <!-- Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> The Project Management Committee (PMC) for Apache Avro has invited Zoltan Csizmadia to become a committer and we are pleased to announce that he has accepted. Zoltan has been present in the C# SDK for over two years and has really increased his activity in maintaining this language in the last few months. He knows the technology, but more importantly, he is patient and works well with those of us who rely on the expertise of others. Recently, he has been engaging with other contributors to increase the maintainability and quality of the dotnet code, and we have confidence in his decisions to balance stability of the established code and the expectations of modern C# developers. Being a committer enables easier contribution to the project since there is no need to go via the patch submission process. This should enable better productivity. Please join me in congratulating Zoltan on his recognition of great work thus far in our community.
Project: k8gb (Orchestration & Management / Coordination & Service Discovery)
File: strategy.md

Returns both cluster endpoints in round-robin manner. While roundRobin is fair for all regions, with WeightRoundRobin we can set explicitly how the regions should be loaded with traffic. For example, we can set one region to handle 80% of the traffic, another 20% and a third 0%, so that the last region is practically disabled. Pinned to a specified primary cluster until workload on that cluster has no available Pods, upon which the next available cluster's Ingress node IPs will be resolved. When Pods are again available on the primary cluster, the primary cluster will once again be the only eligible cluster for which cluster Ingress node IPs will be resolved Similar to `failover` mode, but returns "closest" cluster to the client initiating request. This requires a specially crafted GeoIP database (see for example) and DNS resolver to support EDNS0 extension (CLIENT-SUBNET in particular). If the client subnet is not in GeoIP Database, all available endpoints are returned
Project: DolphinScheduler (Orchestration & Management / Scheduling & Orchestration)
File: map-reduce.md

MapReduce(MR) task type used for executing MapReduce programs. For MapReduce nodes, the worker submits the task by using the Hadoop command `hadoop jar`. See for more details. Click `Project Management -> Project Name -> Workflow Definition`, and click the `Create Workflow` button to enter the DAG editing page. Drag from the toolbar <img src="../../../../img/tasks/icons/mr.png" width="15"/> to the canvas. Please refer to `Default Task Parameters` section for default parameters. | Parameter | Description | |-|--| | Custom parameters | It is a local user-defined parameter for MapReduce, and will replace the content with `${variable}` in the script. | | Parameter | Description | |--|--| | Program type | Select JAVA or SCALA program. | | The class of the main function | The full path of Main Class, the entry point of the MapReduce program. | | Main jar package | The jar package of the MapReduce program. | | Task name | MapReduce task name. | | Yarn queue | Used to set the yarn queue, use `default` queue by default. | | Command line parameters | Set the input parameters of the MapReduce program and support the substitution of custom parameter variables. | | Other parameters | Support `-D`, `-files`, `-libjars`, `-archives` format. | | User-defined parameter | It is a local user-defined parameter for MapReduce, and will replace the content with `${variable}` in the script. | | Parameter | Description | ||--| | Program type | Select Python language. | | Main jar package | The Python jar package for running MapReduce. | | Other parameters | Support `-D`, `-mapper`, `-reducer,` `-input` `-output` format, and you can set the input of user-defined parameters, such as:<ul><li>`-mapper "mapper.py 1"` `-file mapper.py` `-reducer reducer.py` `-file reducer.py` `input /journey/words.txt` `-output /journey/out/mr/${currentTimeMillis}`</li><li>The `mapper.py 1` after `-mapper` is two parameters, the first parameter is `mapper.py`, and the second parameter is `1`. </li></ul> | | User-defined parameter | It is a local user-defined parameter for MapReduce, and will replace the content with `${variable}` in the script. | This example is a common introductory type of MapReduce application, which used to count the number of identical words in the input text. If you are using the MapReduce task type in a production environment, it is necessary to configure the required environment first. The following is the configuration file: `bin/env/dolphinscheduler_env.sh`. When using the MapReduce task node, you need to use the Resource Centre to upload the jar package for the execution. Refer to the . After finish the Resource Centre configuration, upload the required target files directly by dragging and dropping. Configure the required content according to the parameter descriptions above.
Project: APISIX (Orchestration & Management / API Gateway)
File: client-control.md

title: client-control keywords: Apache APISIX API Gateway Client Control description: This document describes the Apache APISIX client-control Plugin, you can use it to control NGINX behavior to handle a client request dynamically. <!-- --> The `client-control` Plugin can be used to dynamically control the behavior of NGINX to handle a client request, by setting the max size of the request body. :::info IMPORTANT This Plugin requires APISIX to run on APISIX-Runtime. See for more info. ::: | Name | Type | Required | Valid values | Description | | - | - | -- | | | | maxbodysize | integer | False | , measured in bytes. If you set the `maxbodysize` to 0, then the size of the client's request body will not be checked. | The example below enables the Plugin on a specific Route: :::note You can fetch the `admin_key` from `config.yaml` and save to an environment variable with the following command: ```bash adminkey=$(yq '.deployment.admin.adminkey[0].key' conf/config.yaml | sed 's/"//g') ``` ::: ```shell curl -i http://127.0.0.1:9180/apisix/admin/routes/1 \ -H "X-API-KEY: $admin_key" -X PUT -d ' { "uri": "/index.html", "plugins": { "client-control": { "maxbodysize" : 1 } }, "upstream": { "type": "roundrobin", "nodes": { "127.0.0.1:1980": 1 } } }' ``` Now since you have configured the `maxbodysize` to `1` above, you will get the following message when you make a request: ```shell curl -i http://127.0.0.1:9080/index.html -d '123' ``` ```shell HTTP/1.1 413 Request Entity Too Large ... <html> <head><title>413 Request Entity Too Large</title></head> <body> <center><h1>413 Request Entity Too Large</h1></center> <hr><center>openresty</center> </body> </html> ``` To remove the `client-control` Plugin, you can delete the corresponding JSON configuration from the Plugin configuration. APISIX will automatically reload, and you do not have to restart for this to take effect. ```shell curl http://127.0.0.1:9180/apisix/admin/routes/1 \ -H "X-API-KEY: $admin_key" -X PUT -d ' { "uri": "/index.html", "upstream": { "type": "roundrobin", "nodes": { "127.0.0.1:1980": 1 } } }' ```
Project: DolphinScheduler (Orchestration & Management / Scheduling & Orchestration)
File: switch.md

The switch is a conditional judgment node, decide the branch executes according to the value of and the expression result written by the user. Note: Execute expressions using javax.script.ScriptEngine.eval. Click `Project Management -> Project Name -> Workflow Definition`, and click the `Create Workflow` button to enter the DAG editing page. Drag from the toolbar <img src="../../../../img/switch.png" width="20"/> task node to canvas to create a task. Note: After created a switch task, you must first configure the upstream and downstream, then configure the parameter of task branches. Please refer to `Default Task Parameters` section for default parameters. | Parameter | Description | ||| | Condition | You can configure multiple conditions for the switch task. When the conditions are satisfied, execute the configured branch. You can configure multiple different conditions to satisfy different businesses. | | Branch flow | The default branch flow, when all the conditions are not satisfied, execute this branch flow. | This is demonstrated using one switch task and three shell tasks. Create a new switch task, and three shell tasks downstream. The shell task is not required. The switch task needs to be connected with the downstream task to configure the relationship before the downstream task can be selected. Configure the conditions and default branches. If the conditions are met, the specified branch will be taken. If the conditions are not met, the default branch will be taken. In the figure, if the value of the variable is "A", the branch taskA is executed, if the value of the variable is "B", the branch taskB is executed, and default is executed if both are not satisfied. Conditions use global variables, please refer to . The value of the global variable configured here is A. If executed correctly, then taskA will be executed correctly. Execute and see if it works as expected. It can be seen that the specified downstream tasksA are executed as expected.
Project: Kusk Gateway (Orchestration & Management / API Gateway)
File: kusk_completion_powershell.md

Generate the autocompletion script for powershell Generate the autocompletion script for powershell. To load completions in your current shell session: kusk completion powershell | Out-String | Invoke-Expression To load completions for every new session, add the output of the above command to your powershell profile. ``` kusk completion powershell [flags] ``` ``` -h, --help help for powershell --no-descriptions disable completion descriptions ``` ``` --config string config file (default is $HOME/.kusk.yaml) ``` - Generate the autocompletion script for the specified shell
Project: DolphinScheduler (Orchestration & Management / Scheduling & Orchestration)
File: workflow-instance.md

Click `Project Management -> Workflow -> Workflow Instance`, enter the Workflow Instance page, as shown in the following figure: Click the workflow name to enter the DAG view page, and check the task execution status, as shown in the following figure: Enter the workflow instance page, click the workflow name, enter the DAG view page, double-click the task node, as shown in the following figure: Click "View Log", a log window pops up, as shown in the figure below, you can also view the task log on the task instance page, refer to Click `Project Management -> Workflow -> Workflow Instance` to enter the workflow instance page, click the workflow name to enter the workflow DAG page; Double-click the task node, click `View History` to jump to the task instance page, and display the list of task instances run by the task definition. Click `Project Management -> Workflow -> Workflow Instance` to enter the workflow instance page, click the workflow name to enter the workflow DAG page; Click the icon in the upper left corner <img src="../../../../img/runparamsbutton.png" width="35"/> to view the startup parameters of the workflow instance; click the icon <img src="../../../../img/global_param.png" width="35"/> to view the global parameters and local parameters of the workflow instance, as shown in the following figure: Click `Project Management -> Workflow -> Workflow Instance`, enter the workflow instance page, as shown in the following figure: Edit: Only processes with success/failed/stop status can be edited. Click the "Edit" button or the workflow instance name to enter the DAG edit page. After the edit, click the "Save" button to confirm, as shown in the figure below. In the pop-up box, check "Whether to update the workflow definition", after saving, the information modified by the instance will be updated to the workflow definition; if not checked, the workflow definition would not be updated. <p align="center"> <img src="../../../../img/editDag-en.png" width="80%" /> </p> Rerun Re-execute the terminated process Recovery Failed: For failed processes, you can perform failure recovery operations, starting from the failed node Stop: Stop the running process, the background code will first `kill` the worker process, and then execute `kill -9` operation Pause: Pause the running process, the system status will change to waiting for execution, it will wait for the task to finish, and pause the next sequence task. Resume pause: Resume the paused process, start running directly from the paused node Delete: Delete the workflow instance and the task instance under the workflow instance Gantt Chart: The vertical axis of the Gantt chart is the topological sorting of task instances of the workflow instance, and the horizontal axis is the running time of the task instances, as shown in the figure: