cwielenb/CNCF-Dataset huggingface dataset:
Project: external-secrets (Provisioning / Security & Compliance)
File: using-latest-image.md

You can test a feature that was not yet released using the following methods, use them at your own discretion: Create a `values.yaml` file with the following content: ```yaml replicaCount: 1 image: repository: ghcr.io/external-secrets/external-secrets pullPolicy: IfNotPresent tag: "main" installCRDs: false ``` Install the crds ```shell make crds.install ``` Install the external-secrets Helm chart indicating the values file created before: ``` helm install external-secrets external-secrets/external-secrets -f values.yaml ``` Build the Docker image ```shell docker build -f Dockerfile.standalone -t my-org/external-secrets:latest . ``` Apply the `bundle.yaml` ```shell kubectl apply -f deploy/crds/bundle.yaml ``` Modify your configs to use the image ```yaml kind: Deployment metadata: name: external-secrets|external-secrets-webhook|external-secrets-cert-controller ... image: my-org/external-secrets:latest ```
Project: Harbor (Provisioning / Container Registry)
File: 9-02-DB-user-push-unsigned-images.md

Test 9-02 User Push unsigned images(DB mode) ======= To verify UI will difference unsigned images from signed images. User guide This test requires one Harbor instance is running and available. A Linux host with Docker CLI (Docker client) installed. Login UI and create a project. Unset DOCKERCONTENTTRUST on Docker client and login Harbor. Push a image to project created in step1. A red cross will displayed under signed column in UI. None
Project: ClickHouse (App Definition and Development / Database)
File: varpop.md

title: "varPop" slug: "/en/sql-reference/aggregate-functions/reference/varpop" sidebar_position: 32 This page covers the `varPop` and `varPopStable` functions available in ClickHouse. Calculates the population covariance between two data columns. The population covariance measures the degree to which two variables vary together. Calculates the amount `((x - x)^2) / n`, where `n` is the sample size and `x`is the average value of `x`. Syntax ```sql covarPop(x, y) ``` Parameters `x`: The first data column. `y`: The second data column. Returned value Returns an integer of type `Float64`. Implementation details This function uses a numerically unstable algorithm. If you need numerical stability in calculations, use the slower but more stable . Example Query: ```sql DROP TABLE IF EXISTS test_data; CREATE TABLE test_data ( x Int32, y Int32 ) ENGINE = Memory; INSERT INTO test_data VALUES (1, 2), (2, 3), (3, 5), (4, 6), (5, 8); SELECT covarPop(x, y) AS covar_pop FROM test_data; ``` Result: ```response 3 ``` Calculates population covariance between two data columns using a stable, numerically accurate method to calculate the variance. This function is designed to provide reliable results even with large datasets or values that might cause numerical instability in other implementations. Syntax ```sql covarPopStable(x, y) ``` Parameters `x`: The first data column. `y`: The second data column. Returned value Returns an integer of type `Float64`. Implementation details Unlike , this function uses a stable, numerically accurate algorithm to calculate the population variance to avoid issues like catastrophic cancellation or loss of precision. This function also handles `NaN` and `Inf` values correctly, excluding them from calculations. Example Query: ```sql DROP TABLE IF EXISTS test_data; CREATE TABLE test_data ( x Int32, y Int32 ) ENGINE = Memory; INSERT INTO test_data VALUES (1, 2), (2, 9), (9, 5), (4, 6), (5, 8); SELECT covarPopStable(x, y) AS covarpopstable FROM test_data; ``` Result: ```response 0.5999999999999999 ```
Project: KICS (Provisioning / Security & Compliance)
File: dd29336b-fe57-445b-a26e-e6aa867ae609.md

title: Container Is Privileged hide: toc: true navigation: true <style> .highlight .hll { background-color: #ff171742; } .md-content { max-width: 1100px; margin: 0 auto; } </style> Query id: dd29336b-fe57-445b-a26e-e6aa867ae609 Query name: Container Is Privileged Platform: Kubernetes Severity: <span style="color:#bb2124">High</span> Category: Insecure Configurations URL: Privileged containers lack essential security restrictions and should be avoided by removing the 'privileged' flag or by changing its value to false<br> ```yaml title="Positive test num. 1 - yaml file" hl_lines="10 23" apiVersion: v1 kind: Pod metadata: name: security-context-demo-4 spec: containers: name: sec-ctx-4 image: gcr.io/google-samples/node-hello:1.0 securityContext: privileged: true capabilities: add: ["NETADMIN", "SYSTIME"] apiVersion: v1 kind: Pod metadata: name: security-context-demo-5 spec: initContainers: name: sec-ctx-4 image: gcr.io/google-samples/node-hello:1.0 securityContext: privileged: true capabilities: add: ["NETADMIN", "SYSTIME"] containers: name: sec-ctx-4 image: gcr.io/google-samples/node-hello:1.0 ``` ```yaml title="Positive test num. 2 - yaml file" hl_lines="21" apiVersion: apps/v1 kind: Deployment metadata: name: test-deployment labels: app: test spec: replicas: 3 selector: matchLabels: app: test template: metadata: labels: app: test spec: containers: name: pause image: k8s.gcr.io/pause securityContext: privileged: true ``` ```yaml title="Negative test num. 1 - yaml file" apiVersion: v1 kind: Pod metadata: name: security-context-demo-4 spec: containers: name: sec-ctx-4 image: gcr.io/google-samples/node-hello:1.0 securityContext: privileged: false capabilities: add: ["NETADMIN", "SYSTIME"] ```
Project: YDB (App Definition and Development / Database)
File: topfreq_mode.md

Getting an approximate list of the most common values in a column with an estimation of their count. Returns a list of structures with two fields: `Value`: the frequently occurring value that was found. `Frequency`: An estimated value occurrence in the table. Required argument: the value itself. Optional arguments: For `TOPFREQ`, the desired number of items in the result. `MODE` is an alias to `TOPFREQ` with this argument set to 1. For `TOPFREQ`, this argument is also 1 by default. The number of items in the buffer used: lets you trade memory consumption for accuracy. Default: 100. Examples ```yql SELECT MODE(my_column), TOPFREQ(my_column, 5, 1000) FROM my_table; ```
Project: YugabyteDB (App Definition and Development / Database)
File: do-clean-start.md

title: docleanstart.sql linkTitle: docleanstart.sql headerTitle: docleanstart.sql description: docleanstart.sql - Part of the code kit for the "Analyzing a normal distribution" section within the YSQL window functions documentation. menu: v2.18: identifier: do-clean-start parent: analyzing-a-normal-distribution weight: 20 type: docs Save this script as `docleanstart.sql`. ```plpgsql -- Get a clean start. -- These tables will store some query results so that, with -- all these in a single table, it is easy to use -- SQL to compare results from different tests. set clientminmessages = warning; drop table if exists dp_results cascade; create table dp_results( method text not null, bucket int not null, n int not null, min_s double precision not null, max_s double precision not null, constraint dpresultspk primary key(method, bucket)); drop table if exists int_results cascade; create table int_results( method text not null, bucket int not null, n int not null, min_s double precision not null, max_s double precision not null, constraint intresultspk primary key(method, bucket)); ```
Project: KICS (Provisioning / Security & Compliance)
File: 67bfdff1-31ce-4525-b564-e94368735360.md

title: NAS File System Not Encrypted hide: toc: true navigation: true <style> .highlight .hll { background-color: #ff171742; } .md-content { max-width: 1100px; margin: 0 auto; } </style> Query id: 67bfdff1-31ce-4525-b564-e94368735360 Query name: NAS File System Not Encrypted Platform: Terraform Severity: <span style="color:#bb2124">High</span> Category: Encryption URL: NAS File System must be encrypted<br> ```tf title="Positive test num. 1 - tf file" hl_lines="5" resource "alicloudnasfile_system" "foopos" { protocol_type = "NFS" storage_type = "Performance" description = "tf-testAccNasConfig" encrypt_type = "0" } ``` ```tf title="Positive test num. 2 - tf file" hl_lines="1" resource "alicloudnasfile_system" "foopos2" { protocol_type = "NFS" storage_type = "Performance" description = "tf-testAccNasConfig" } ``` ```tf title="Negative test num. 1 - tf file" resource "alicloudnasfile_system" "foo" { protocol_type = "NFS" storage_type = "Performance" description = "tf-testAccNasConfig" encrypt_type = "1" } ``` ```tf title="Negative test num. 2 - tf file" resource "alicloudnasfile_system" "foo2" { protocol_type = "NFS" storage_type = "Performance" description = "tf-testAccNasConfig" encrypt_type = "2" } ```
Project: ClickHouse (App Definition and Development / Database)
File: v20.8.17.25-lts.md

Backported in : Disable constant folding for subqueries on the analysis stage, when the result cannot be calculated. (). Backported in : Fix wait for mutations on several replicas for ReplicatedMergeTree table engines. Previously, mutation/alter query may finish before mutation actually executed on other replicas. (). Backported in : Fix possible hangs in zk requests in case of OOM exception. Fixes . (). Backported in : Update timezones info to 2020e. ().
Project: EMQ Technologies (App Definition and Development / Streaming & Messaging)
File: feat-12719.en.md

Multi clientid/username queries examples: "/clients?clientid=client1&clientid=client2 "/clients?username=user11&username=user2" "/clients?clientid=client1&clientid=client2&username=user1&username=user2" Request response fields examples: "/clients?fields=all" (omitting "fields" Qs parameter defaults to returning all fields) "/clients?fields=clientid,username"
Project: SuperEdge (Provisioning / Automation & Configuration)
File: CHANGELOG-0.5.md

- - Edgeadm: add kube-vip as default HA component support(,) TunnelCloud HPA: add tunnel-cloud metrics for HPA(,), support tunnel-cloud HPA based on the number of connected edge nodes(,). Deploy Prometheus(,), TunnelCloud DNS: Separate the synchronization of podIP and Endpoints(,) Edgeadm: Deploy coredns for every edge node by servicegroup(,) Edgeadm: Fix x509 certificate bug when joining edge nodes(,) Edgeadm: Fix tunnel-coredns addr when join master(,) Add technical articles related to SuprEdge(,) Add proposal template(,)
Project: Apache Heron (App Definition and Development / Streaming & Messaging)
File: deployment-overview.md

id: version-0.20.0-incubating-deployment-overview title: Deployment Overiew sidebar_label: Deployment Overiew original_id: deployment-overview <!-- 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. --> Heron is designed to be run in clustered, scheduler-driven environments. It can be run in a `multi-tenant` or `dedicated` clusters. Furthermore, Heron supports `multiple clusters` and a user can submit topologies to any of these clusters. Each of the cluster can use `different scheduler`. A typical Heron deployment is shown in the following figure. <br /> <br/> A Heron deployment requires several components working together. The following must be deployed to run Heron topologies in a cluster: Scheduler* Heron requires a scheduler to run its topologies. It can be deployed on an existing cluster running alongside other big data frameworks. Alternatively, it can be deployed on a cluster of its own. Heron currently supports several scheduler options: * * * State Manager* Heron state manager tracks the state of all deployed topologies. The topology state includes its logical plan, physical plan, and execution state. Heron supports the following state managers: * Uploader* The Heron uploader distributes the topology jars to the servers that run them. Heron supports several uploaders * Metrics Sinks* Heron collects several metrics during topology execution. These metrics can be routed to a sink for storage and offline analysis. Currently, Heron supports the following sinks `File Sink` `Graphite Sink` `Scribe Sink` Heron Tracker* Tracker serves as the gateway to explore the topologies. It exposes a REST API for exploring logical plan, physical plan of the topologies and also for fetching metrics from them. Heron UI* The UI provides the ability to find and explore topologies visually. UI displays the DAG of the topology and how the DAG is mapped to physical containers running in clusters. Furthermore, it allows the ability to view logs, take heap dump, memory histograms, show metrics, etc.
Project: Koperator (App Definition and Development / Streaming & Messaging)
File: PULL_REQUEST_TEMPLATE.md

Please provide a meaningful description of what this change will do, or is for. Bonus points for including links to related issues, other PRs, or technical references. Note that by not including a description, you are asking reviewers to do extra work to understand the context of this change, which may lead to your PR taking much longer to review, or result in it not being reviewed at all. <!-- Place an '[x]' (no spaces) in all applicable fields. Please remove unrelated fields. --> [ ] Bug Fix [ ] New Feature [ ] Breaking Change [ ] Refactor [ ] Documentation [ ] Other (please describe) <!-- Place an '[x]' (no spaces) in all applicable fields. Please remove unrelated fields. --> [ ] Existing issues have been referenced (where applicable) [ ] I have verified this change is not present in other open pull requests [ ] Functionality is documented [ ] All code style checks pass [ ] New code contribution is covered by automated tests [ ] All new and existing tests pass
Project: RabbitMQ (App Definition and Development / Streaming & Messaging)
File: 3.9.19.md

RabbitMQ `3.9.19` is a maintenance release in the `3.9.x` release 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 23.2, and supports Erlang 24. has more details on Erlang version requirements for RabbitMQ. Release notes can be found on GitHub at . A minor quorum queue optimization. GitHub issue: Avoid seeding default user in old clusters that still use the deprecated `management.load_definitions` option. This could result in an extra user, `guest` or under an , to appear in addition to the user accounts imported from definitions. Note that the default user with well-known name , so this would not expose reasonably configured production nodes to remote connections. GitHub issue: Streams could run into an exception or fetch stale stream position data in some scenarios. GitHub issue: `rabbitmqctl setloglevel` did not have any effect on logging via (the system exchange for logging) Contributed by Pter @gomoripeti Gmri (CloudAMQP). GitHub issue: `rabbitmq-diagnostics status` is now more resilient and won't fail if free disk space monitoring repeatedly fails (gets disabled) on the node. GitHub issue: `ra` upgraded from To obtain source code of the entire distribution, please download the archive named `rabbitmq-server-3.9.19.tar.xz` instead of the source tarball produced by GitHub.
Project: Kyverno (Provisioning / Security & Compliance)
File: kyverno_create_user-info.md

Create a Kyverno user-info file. Create a Kyverno user-info file. ``` kyverno create user-info [flags] ``` ``` kyverno create user-info -u molybdenum@somecorp.com -g basic-user -c admin ``` ``` -c, --cluster-role strings Cluster role -g, --group strings Group -h, --help help for user-info -o, --output string Output path (uses standard console output if not set) -r, --role strings Role -u, --username string User name ``` ``` --adddirheader If true, adds the file directory to the header of the log messages --alsologtostderr log to standard error as well as files (no effect when -logtostderr=true) --logbacktraceat traceLocation when logging hits line file:N, emit a stack trace (default :0) --log_dir string If non-empty, write log files in this directory (no effect when -logtostderr=true) --log_file string If non-empty, use this log file (no effect when -logtostderr=true) --logfilemax_size uint Defines the maximum size a log file can grow to (no effect when -logtostderr=true). Unit is megabytes. If the value is 0, the maximum file size is unlimited. (default 1800) --logtostderr log to standard error instead of files (default true) --one_output If true, only write logs to their native severity level (vs also writing to each lower severity level; no effect when -logtostderr=true) --skip_headers If true, avoid header prefixes in the log messages --skiplogheaders If true, avoid headers when opening log files (no effect when -logtostderr=true) --stderrthreshold severity logs at or above this threshold go to stderr when writing to files and stderr (no effect when -logtostderr=true or -alsologtostderr=true) (default 2) -v, --v Level number for the log level verbosity --vmodule moduleSpec comma-separated list of pattern=N settings for file-filtered logging ``` - Helps with the creation of various Kyverno resources.
Project: Numaflow (App Definition and Development / Streaming & Messaging)
File: map.md

Map in a Map vertex takes an input and returns 0, 1, or more outputs (also known as flat-map operation). Map is an element wise operator. There are some that can be used directly. You can build your own UDF in multiple languages. Check the links below to see the UDF examples for different languages. After building a docker image for the written UDF, specify the image as below in the vertex spec. ```yaml spec: vertices: name: my-vertex udf: container: image: my-python-udf-example:latest ``` In cases the map function generates more than one output (e.g., flat map), the UDF can be configured to run in a streaming mode instead of batching, which is the default mode. In streaming mode, the messages will be pushed to the downstream vertices once generated instead of in a batch at the end. The streaming mode can be enabled by setting the annotation `numaflow.numaproj.io/map-stream` to `true` in the vertex spec. Note that to maintain data orderliness, we restrict the read batch size to be `1`. ```yaml spec: vertices: name: my-vertex metadata: annotations: numaflow.numaproj.io/map-stream: "true" limits: readBatchSize: 1 ``` Check the links below to see the UDF examples in streaming mode for different languages. Some environment variables are available in the user-defined function container, they might be useful in your own UDF implementation. `NUMAFLOW_NAMESPACE` - Namespace. `NUMAFLOW_POD` - Pod name. `NUMAFLOW_REPLICA` - Replica index. `NUMAFLOWPIPELINENAME` - Name of the pipeline. `NUMAFLOWVERTEXNAME` - Name of the vertex. Configuration data can be provided to the UDF container at runtime multiple ways. `args` `command`
Project: Kyverno (Provisioning / Security & Compliance)
File: kyverno_docs.md

Generates reference documentation. Generates reference documentation. The docs command generates Kyverno CLI reference documentation. It can be used to generate simple markdown files or markdown to be used for the website. ``` kyverno docs [flags] ``` ``` KYVERNO_EXPERIMENTAL=true kyverno docs -o . --autogenTag=false KYVERNO_EXPERIMENTAL=true kyverno docs -o . --website ``` ``` --autogenTag Determines if the generated docs should contain a timestamp (default true) -h, --help help for docs -o, --output string Output path (default ".") --website Website version ``` ``` --adddirheader If true, adds the file directory to the header of the log messages --alsologtostderr log to standard error as well as files (no effect when -logtostderr=true) --logbacktraceat traceLocation when logging hits line file:N, emit a stack trace (default :0) --log_dir string If non-empty, write log files in this directory (no effect when -logtostderr=true) --log_file string If non-empty, use this log file (no effect when -logtostderr=true) --logfilemax_size uint Defines the maximum size a log file can grow to (no effect when -logtostderr=true). Unit is megabytes. If the value is 0, the maximum file size is unlimited. (default 1800) --logtostderr log to standard error instead of files (default true) --one_output If true, only write logs to their native severity level (vs also writing to each lower severity level; no effect when -logtostderr=true) --skip_headers If true, avoid header prefixes in the log messages --skiplogheaders If true, avoid headers when opening log files (no effect when -logtostderr=true) --stderrthreshold severity logs at or above this threshold go to stderr when writing to files and stderr (no effect when -logtostderr=true or -alsologtostderr=true) (default 2) -v, --v Level number for the log level verbosity --vmodule moduleSpec comma-separated list of pattern=N settings for file-filtered logging ``` - Kubernetes Native Policy Management.
Project: Backstage (App Definition and Development / Application Definition & Image Build)
File: background.md

id: background title: The Spotify Story description: Backstage was born out of necessity at Spotify. We found that as we grew, our infrastructure was becoming more fragmented, our engineers less productive. Backstage was born out of necessity at Spotify. We found that as we grew, our infrastructure was becoming more fragmented, our engineers less productive. Instead of building and testing code, teams were spending more time looking for the right information just to get started. Wheres the API for that service were all supposed to be using? What version of that framework is everyone on? This service isnt responding, who owns it? I cant find documentation for anything! Context switching and cognitive overload were dragging engineers down, day by day. We needed to make it easier for our engineers to do their work without having to become an expert in every aspect of infrastructure tooling. Our idea was to centralize and simplify end-to-end software development with an abstraction layer that sits on top of all of our infrastructure and developer tooling. Thats Backstage. Its a developer portal powered by a centralized software catalog with a plugin architecture that makes it endlessly extensible and customizable. Manage all your services, software, tooling, and testing in Backstage. Start building a new microservice using an automated template in Backstage. Create, maintain, and find the documentation for all that software in Backstage. One place for everything. Accessible to everyone. Backstage was originally built by Spotify and then donated to the CNCF. Backstage is currently in the Incubation phase. Read the announcement . <img src="https://backstage.io/img/cncf-white.svg" alt="CNCF logo" width="400" />