cwielenb/CNCF-Dataset huggingface dataset:
Project: KICS (Provisioning / Security & Compliance)
File: 099b4411-d11e-4537-a0fc-146b19762a79.md

title: Project-wide SSH Keys Are Enabled In VM Instances hide: toc: true navigation: true <style> .highlight .hll { background-color: #ff171742; } .md-content { max-width: 1100px; margin: 0 auto; } </style> Query id: 099b4411-d11e-4537-a0fc-146b19762a79 Query name: Project-wide SSH Keys Are Enabled In VM Instances Platform: Ansible Severity: <span style="color:#ff7213">Medium</span> Category: Secret Management URL: VM Instance should block project-wide SSH keys<br> ```yaml title="Positive test num. 1 - yaml file" hl_lines="9 4 15" name: sshkeysunblocked google.cloud.gcpcomputeinstance: metadata: block-project-ssh-keys: no zone: us-central1-a auth_kind: serviceaccount name: sshkeysmissing google.cloud.gcpcomputeinstance: metadata: startup-script-url: gs:://graphite-playground/bootstrap.sh cost-center: '12345' zone: us-central1-a auth_kind: serviceaccount name: no_metadata google.cloud.gcpcomputeinstance: zone: us-central1-a auth_kind: serviceaccount ``` ```yaml title="Negative test num. 1 - yaml file" name: sshkeysblocked google.cloud.gcpcomputeinstance: metadata: block-project-ssh-keys: yes zone: us-central1-a auth_kind: serviceaccount ```
Project: KubeDL (Provisioning / Automation & Configuration)
File: metrics.md

This document describes the prometheus metrics supported for the KubeDL operator. The curly brackets `{}`are used to indicate the labels supported for the metrics. `kind` - the target job workload kind, e.g. TFJob, PyTorchJob, XDLJob, XGBoostJob | Metric Names | Description | | | -- | | kubedljobscreated{kind} | Counts number of jobs created | | kubedljobsdeleted{kind} | Counts number of jobs deleted | | kubedljobssuccessful{kind} | Counts number of jobs successfully finished | | kubedljobsfailed{kind} | Counts number of jobs failed | | kubedljobsrestarted{kind} | Counts number of jobs restarted | | kubedljobsrunning{kind} | Counts number of jobs currently running | | kubedljobspending{kind} | Counts number of jobs currently pending | | kubedljobsfirstpodlaunchdelayseconds{kind, name, namespace, uid} | Histogram for recording launch delay duration (from job created to first pod running) | | kubedljobsallpodslaunchdelayseconds{kind, name, namespace, uid} | Histogram for recording launch delay duration (from job created to all pods running) |
Project: RabbitMQ (App Definition and Development / Streaming & Messaging)
File: 3.9.28.md

RabbitMQ `3.9.28` is a maintenance release in the `3.9.x` release series. This series . Please refer to the Upgrading to 3.9 section from if upgrading from a version prior to 3.9.0. This release requires at least Erlang 24.3, and supports Erlang 25. has more details on Erlang version requirements for RabbitMQ. Erlang 23 support has reached its . Starting with this release, RabbitMQ requires Erlang 24.3 or later versions. Nodes will fail to start on older Erlang releases. Release notes can be found on GitHub at . Preserve additional information in the log message when heartbeat frame cannot be sent due to a TCP timeout. GitHub issue: `rabbitmqctl add_vhost` now coerces a single string value of `--tags` into an array. GitHub issue: User filtering combined with pagination in the management UI did not work as expected. GitHub issue: Correctly format JSON field value in channel detail API response. Contributed @Syuparn. GitHub issue: AMQP 1.0 connection churn resulted in a memory leak. GitHub issue: `ERROR` frames delivery is now correctly delivered w.r.t. TCP connection closure for clients that run into certain types of exceptions. Contributed by @csicar. GitHub issue: `ra` was upgraded `prometheus.erl` was upgraded None in this release. To obtain source code of the entire distribution, please download the archive named `rabbitmq-server-3.9.28.tar.xz` instead of the source tarball produced by GitHub.
Project: KubeEdge (Provisioning / Automation & Configuration)
File: CONTRIBUTING.md

Welcome to Kubernetes. We are excited about the prospect of you joining our ! The Kubernetes community abides by the CNCF . Here is an excerpt: As contributors and maintainers of this project, and in the interest of fostering an open and welcoming community, we pledge to respect all people who contribute through reporting issues, posting feature requests, updating documentation, submitting pull requests or patches, and other activities. We have full documentation on how to get started contributing here: <! If your repo has certain guidelines for contribution, put them here ahead of the general k8s resources --> Kubernetes projects require that you sign a Contributor License Agreement (CLA) before we can accept your pull requests - Main contributor documentation, or you can just jump directly to the - Common resources for existing developers - We have a diverse set of mentorship programs available that are always looking for volunteers! <! Custom Information - if you're copying this template for the first time you can add custom content here, for example: - Replace `kubernetes-users` with your slack channel string, this will send users directly to your channel. -->
Project: KubeBlocks by ApeCloud (App Definition and Development / Database)
File: postgresql-connection-pool.md

title: PostgreSQL connection pool description: Connect to PgBouncer to reduce too many PostgreSQL connections and to improve the throughput and stability of the database. keywords: [postgresql, connection pool, pgbouncer] sidebar_position: 1 sidebar_label: Connection pool PostgreSQL adopts a multi-process architecture, which creates a separate backend process for each user connection. When there are too many user connections, it occupies a large amount of memory, which reduces the throughput and stability of the database. To solve these problems, KubeBlocks introduces a connection pool, PgBouncer, for PostgreSQL database clusters. When creating a PostgreSQL cluster with KubeBlocks, PgBouncer is installed by default. View the status of the created PostgreSQL cluster and ensure this cluster is `Running`. ```bash kbcli cluster list mycluster ``` Describe this cluster and there are two connection links in Endpoints. Port `5432` is used to connect to the primary pod of this database and port `6432` is used to connect to PgBouncer. ```bash kbcli cluster describe mycluster > Endpoints: COMPONENT MODE INTERNAL EXTERNAL postgresql ReadWrite mycluster-postgresql.default.svc.cluster.local:5432 <none> mycluster-postgresql.default.svc.cluster.local:6432 ``` Connect the cluster with PgBouncer. This command shows how to connect to a cluster with CLI. The default example uses port `5432` and you can replace it with port `6432`. ```bash kbcli cluster connect --client=cli --show-example mycluster > kubectl port-forward service/mycluster-postgresql 6432:6432 PGPASSWORD=* psql -h127.0.0.1 -p 6432 -U postgres postgres ``` Run `port-forward`. ```bash kubectl port-forward service/mycluster-postgresql 6432:6432 ``` Open a new terminal window and run the `psql` command to connect to PgBouncer. ```bash PGPASSWORD=* psql -h127.0.0.1 -p 6432 -U postgres postgres ``` Run the following command in `psgl` to verify the connection. If you can connect to `pgbouncer` and execute `show help` with the expected results below, this cluster connects to PgBouncer successfully. ```bash postgres=# \c pgbouncer ``` ```bash pgbouncer=# show help; > NOTICE: Console usage DETAIL: SHOW HELP|CONFIG|DATABASES|POOLS|CLIENTS|SERVERS|USERS|VERSION SHOW PEERS|PEER_POOLS SHOW FDS|SOCKETS|ACTIVE_SOCKETS|LISTS|MEM|STATE SHOW DNSHOSTS|DNSZONES SHOW STATS|STATSTOTALS|STATSAVERAGES|TOTALS SET key = arg RELOAD PAUSE [<db>] RESUME [<db>] DISABLE <db> ENABLE <db> RECONNECT [<db>] KILL <db> SUSPEND SHUTDOWN WAIT_CLOSE [<db>] SHOW ```
Project: RBAC Lookup (Provisioning / Security & Compliance)
File: gke.md

If you're connected to a GKE cluster, RBAC is only half the story here. Google Cloud IAM roles can grant cluster access. Cluster access is effectively determined by a union of IAM and RBAC roles. To see the relevant IAM roles along with RBAC roles, use the `--gke` flag. ``` rbac-lookup rob --gke SUBJECT SCOPE ROLE rob@example.com cluster-wide ClusterRole/view rob@example.com nginx-ingress ClusterRole/edit rob@example.com project-wide IAM/gke-developer rob@example.com project-wide IAM/viewer ``` Of course this GKE integration also supports wide output, in this case referencing the specific IAM roles that are assigned to a user. ``` rbac-lookup rob --gke --output wide SUBJECT SCOPE ROLE SOURCE User/rob@example.com cluster-wide ClusterRole/view ClusterRoleBinding/rob-cluster-view User/rob@example.com nginx-ingress ClusterRole/edit RoleBinding/rob-edit User/rob@example.com project-wide IAM/gke-developer IAMRole/container.developer User/rob@example.com project-wide IAM/gcp-viewer IAMRole/viewer ``` At this point this integration only supports standard IAM roles, and is not advanced enough to include any custom roles. For a full list of supported roles and how they are mapped, view .
Project: DevSpace (App Definition and Development / Application Definition & Image Build)
File: devspace_update_dependencies.md

title: "Command - devspace update dependencies" sidebar_label: devspace update dependencies Updates the git repositories of the dependencies defined in the devspace.yaml ``` devspace update dependencies [flags] ``` ``` Updates the git repositories of the dependencies defined in the devspace.yaml ``` ``` -h, --help help for dependencies ``` ``` --config string The devspace config file to use --debug Prints the stack trace if an error occurs --disable-profile-activation If true will ignore all profile activations --inactivity-timeout int Minutes the current user is inactive (no mouse or keyboard interaction) until DevSpace will exit automatically. 0 to disable. Only supported on windows and mac operating systems (default 180) --kube-context string The kubernetes context to use -n, --namespace string The kubernetes namespace to use --no-warn If true does not show any warning when deploying into a different namespace or kube-context than before -p, --profile strings The DevSpace profiles to apply. Multiple profiles are applied in the order they are specified --profile-parent strings One or more profiles that should be applied before the specified profile (e.g. devspace dev --profile-parent=base1 --profile-parent=base2 --profile=my-profile) --profile-refresh If true will pull and re-download profile parent sources --restore-vars If true will restore the variables from kubernetes before loading the config --save-vars If true will save the variables to kubernetes after loading the config --silent Run in silent mode and prevents any devspace log output except panics & fatals -s, --switch-context DEPRECATED: Switches and uses the last kube context and namespace that was used to deploy the DevSpace project --var strings Variables to override during execution (e.g. --var=MYVAR=MYVALUE) --vars-secret string The secret to restore/save the variables from/to, if --restore-vars or --save-vars is enabled (default "devspace-vars") ```
Project: KICS (Provisioning / Security & Compliance)
File: c48e57d3-d642-4e0b-90db-37f807b41b91.md

title: PSP Set To Privileged hide: toc: true navigation: true <style> .highlight .hll { background-color: #ff171742; } .md-content { max-width: 1100px; margin: 0 auto; } </style> Query id: c48e57d3-d642-4e0b-90db-37f807b41b91 Query name: PSP Set To Privileged Platform: Kubernetes Severity: <span style="color:#bb2124">High</span> Category: Insecure Configurations URL: Do not allow pod to request execution as privileged.<br> ```yaml title="Positive test num. 1 - yaml file" hl_lines="6" apiVersion: policy/v1beta1 kind: PodSecurityPolicy metadata: name: example spec: privileged: true seLinux: rule: RunAsAny supplementalGroups: rule: RunAsAny runAsUser: rule: RunAsAny fsGroup: rule: RunAsAny volumes: '*' ``` ```yaml title="Negative test num. 1 - yaml file" apiVersion: policy/v1beta1 kind: PodSecurityPolicy metadata: name: example spec: privileged: false seLinux: rule: RunAsAny supplementalGroups: rule: RunAsAny runAsUser: rule: RunAsAny fsGroup: rule: RunAsAny volumes: '*' ```
Project: Meshery (Provisioning / Automation & Configuration)
File: ADOPTERS.md

- "Our complex, dynamic, and intelligent system demands leverage different tools to efficiently manage service exchange and ecosystem at a global scale; for instance, we need to identify the right fit service mesh to address varying workload scenarios, distributed systems across locations, different security tiers, minimal latency etc. Meshery helps us curate service mesh for tailored need by helping us running simulations and identifying the right fit service mesh that works efficiently across a diverse ecosystem of tools." - "As a security-focused organization, HPE Security Engineering continually evaluates, assesses, and conducts performance analysis over service meshes and other cloud-native technologies. Meshery has been an instrumental piece of our daily work, as having a simple yet powerful management plane facilitates our engineers to deploy, manage, experiment, and quickly iterate. Meshery's features can only be overshadowed by its friendly and welcoming community always willing to help." - : "Working with service mesh technology, I find one of the most useful tools is Meshery! I use Meshery to run POCs for our customers to help them adopt, and then, ongoing to check our mesh configuration. The most fantastic part about Meshery is its performance management features." Sudeep Batra () - : "We find Meshery to be the perfect tool to help us successfully operate our service mesh. And with so many new features coming out, it's only getting better and better." - "As we are a very modern technology company, we always want to use cutting edge, open source technology to excel. All our microservices are modern in nature and so is their infrastructure. We are cloud agnostic and at the same time, we are fascinated by service meshes to empower us with secure, reliable, intelligent infrastructure. When we are in an Istio world, the need for managing the mesh was always been a gap. With Meshery, we believe we can nurture our service mesh to perform better and more efficiently." - "We are a true Boutique Tech Consulting partner who understands the pain points of the all-sized company in terms of embracing cloud. Being obsessed about anything cloud and automation first, we drive our partner to success. We always strive to provide our customers, the cutting-edge technology and the trend is service mesh now. We enable our clients to make their microservices more secure with Mesh. When we talk about service meshes, Meshery comes in handy. We have seen the impact Meshery has done for the mesh deployment and management and reduced the time to market. " - "We are working on the acceleration and security of open source Service Mesh projects. Meshery is the best tool for managing and operating different Service Mesh projects, it greatly helped us compare the functions and performance of them, and demonstrate the results of our efforts. We also love Meshery's community where we can connect with Service Mesh talents and enthusiasts from all over the world!" If you're using Meshery and aren't on this list, please !
Project: ArangoDB (App Definition and Development / Database)
File: try_throw_std_exception_from_error.md

+++ title = "`void trythrowstdexceptionfromerror(std::errorcode ec, const std::string &msg = std::string{})`" description = "Try to throw a standard library exception type matching an error code." +++ This function saves writing boilerplate by throwing a standard library exception type equivalent to the supplied error code, with an optional custom message. If the function returns, there is no standard library exception type equivalent to the supplied error code. The following codes produce the following exception throws: <dl> <dt><code>EINVAL</code> <dd><code>std::invalid_argument</code> <dt><code>EDOM</code> <dd><code>std::domain_error</code> <dt><code>E2BIG</code> <dd><code>std::length_error</code> <dt><code>ERANGE</code> <dd><code>std::outofrange</code> <dt><code>EOVERFLOW</code> <dd><code>std::overflow_error</code> <dt><code>ENOMEM</code> <dd><code>std::bad_alloc</code> </dl> The choice to refer to POSIX `errno` values above reflects the matching algorithm. As {{% api "std::errc" %}} exactly maps POSIX `errno`, on all platforms {{% api "std::generic_category" %}} error codes are matched by this function. Only on POSIX platforms only are {{% api "std::system_category" %}} error codes also matched by this function. Overridable: Not overridable. Requires: C++ exceptions to be globally enabled. Namespace: `BOOSTOUTCOMEV2_NAMESPACE` Header: `<boost/outcome/utils.hpp>`
Project: Flink (App Definition and Development / Streaming & Messaging)
File: conversion_of_data_stream.md

title: "Conversions between Table and DataStream" weight: 42 type: docs <!-- 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 http://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. --> <meta http-equiv="refresh" content="0; url={{< ref "docs/dev/table/datastreamapi" >}} "/>
Project: OceanBase (App Definition and Development / Database)
File: feature_request.md

name: Feature Request about: Suggest an idea for this project title: "[Feature]: " labels: ["type: feature"] Use Case <!-- A clear and concise description of what is the intended usage scenario is. --> Describe the solution you'd like <!-- A clear and concise description of what you want to happen. --> Describe alternatives you've considered <!-- A clear and concise description of any alternative solutions or features you've considered. --> Additional context <!-- Add any other context or screenshots about the feature request here. -->
Project: Beam (App Definition and Development / Streaming & Messaging)
File: beam-2.12.0.md

title: "Apache Beam 2.12.0" date: 2019-04-25 00:00:01 -0800 categories: blog release aliases: /blog/2019/04/25/beam-2.12.0.html authors: apilloud <!-- Licensed 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 http://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. --> We are happy to present the new 2.12.0 release of Beam. This release includes both improvements and new functionality. See the for this release.<!--more--> For more information on changes in 2.12.0, check out the . Add support for a BigQuery custom sink for Python SDK. Add support to specify a query in CassandraIO for Java SDK. Add experimental support for cross-language transforms, please see Add support in the Flink Runner for exactly-once Writes with KafkaIO Enable Bundle Finalization in Python SDK for portable runners. Add support to the Java SDK harness to merge windows. Add Kafka Sink EOS support on Flink runner. Added a dead letter queue to Python streaming BigQuery sink. Add Experimental Python 3.6 and 3.7 workloads enabled. Beam 2.12 supports starting Dataflow pipelines under Python 3.6, 3.7, however 3.5 remains the only recommended minor version for Dataflow runner. In addition to announced 2.11 limitations, Beam typehint annotations are currently not supported on Python >= 3.6. Various bug fixes and performance improvements. According to git shortlog, the following people contributed to the 2.12.0 release. Thank you to all contributors! Ahmed El.Hussaini, Ahmet Altay, Alan Myrvold, Alex Amato, Alexander Savchenko, Alexey Romanenko, Andrew Brampton, Andrew Pilloud, Ankit Jhalaria, Ankur Goenka, Anton Kedin, Boyuan Zhang, Brian Hulette, Chamikara Jayalath, Charles Chen, Colm O hEigeartaigh, Craig Chambers, Dan Duong, Daniel Mescheder, Daniel Oliveira, David Moravek, David Rieber, David Yan, Eric Roshan-Eisner, Etienne Chauchot, Gleb Kanterov, Heejong Lee, Ho Tien Vu, Ismal Meja, Jan Lukavsk, Jean-Baptiste Onofr, Jeff Klukas, Juta, Kasia Kucharczyk, Kengo Seki, Kenneth Jung, Kenneth Knowles, kevin, Kyle Weaver, Kyle Winkelman, ukasz Gajowy, Mark Liu, Mathieu Blanchard, Max Charas, Maximilian Michels, Melissa Pashniak, Michael Luckey, Michal Walenia, Mike Kaplinskiy, Mikhail Gryzykhin, Niel Markwick, Pablo Estrada, Radoslaw Stankiewicz, Reuven Lax, Robbe Sneyders, Robert Bradshaw, Robert Burke, Rui Wang, Ruoyun Huang, Ryan Williams, Slava Chernyak, Shahar Frank, Sunil Pedapudi, Thomas Weise, Tim Robertson, Tanay Tummalapalli, Udi Meiri, Valentyn Tymofieiev, Xinyu Liu, Yifan Zou, Yueyang Qiu
Project: Lagoon (App Definition and Development / Application Definition & Image Build)
File: contributing.md

We gladly welcome any and all contributions to Lagoon! Lagoon benefits from any kind of contribution - whether it's a bugfix, new feature, documentation update, or simply some queue maintenance - we're happy that you want to help There's a whole section on how to get Lagoon running on your local machine using KinD over at . This documentation is still very WIP - but there are a lot of Makefile routines to help you out. We've got another section that outlines how to install Lagoon from Helm charts at - we'd love to get this process as slick as possible! Right now one of our biggest needs is putting together examples of Lagoon working with various content management systems, etc, other than Drupal. If you can spin up an open source CMS or framework that we dont currently have as a Docker Compose stack, send us a PR. Look at the existing examples at for tips, pointers and starter issues. One small catch wherever possible, wed like them to be built using our base Docker Hub images if we dont have a suitable image, or our images need modifying throw us a PR \(if you can\) or create an issue \(so someone else can\) at . Help us improve our existing examples, if you can - are we following best practices, is there something were doing that doesnt make sense? Bonus points for anyone that helps contribute to tests for any of these examples weve got some example tests in a couple of the projects you can use for guidance . The testing framework were using is , from the excellent team behind . Help us to document our other examples better were not expecting a full manuscript, but tidy-ups, links to helpful resources and clarifying statements are all super-awesome. If you have any questions, reach out to us on ! We take security very seriously. If you discover a security issue or think you found one, please bring it to the maintainers' attention. !!! Danger Please send your findings to . Please DO NOT file a GitHub issue for them. Security reports are greatly appreciated and will receive public karma and swag! We're also working on a Bug Bounty system. We're always interested in fixing issues, therefore issue reports are very welcome. Please make sure to check that your issue does not already exist in the . Cool! Create an and we're happy to look over it. We can't guarantee that it will be implemented. But we are always interested in hearing ideas of what we could bring to Lagoon. Another good way is also to talk to us via Discord about your idea. ! Epic! Please send us a pull request for it, we will do our best to review it and merge it if possible.