cwielenb/CNCF-Dataset huggingface dataset:
Project: Netdata (Observability and Analysis / Observability)
File: net.inet.ip.stats.md

<!--startmeta customediturl: "https://github.com/netdata/netdata/edit/master/src/collectors/freebsd.plugin/integrations/net.inet.ip.stats.md" meta_yaml: "https://github.com/netdata/netdata/edit/master/src/collectors/freebsd.plugin/metadata.yaml" sidebar_label: "net.inet.ip.stats" learn_status: "Published" learnrelpath: "Collecting Metrics/FreeBSD" most_popular: False message: "DO NOT EDIT THIS FILE DIRECTLY, IT IS GENERATED BY THE COLLECTOR'S metadata.yaml FILE" endmeta--> <img src="https://netdata.cloud/img/network.svg" width="150"/> Plugin: freebsd.plugin Module: net.inet.ip.stats <img src="https://img.shields.io/badge/maintained%20by-Netdata-%2300ab44" /> Collect IP stats The plugin calls `sysctl` function to collect necessary data. This collector is supported on all platforms. This collector supports collecting metrics from multiple instances of this integration, including remote instances. This integration doesn't support auto-detection. The default configuration for this integration does not impose any limits on data collection. The default configuration for this integration is not expected to impose a significant performance impact on the system. Metrics grouped by scope. The scope defines the instance that the metric belongs to. An instance is uniquely identified by a set of labels. These metrics show IPv4 connections statistics. This scope has no labels. Metrics: | Metric | Dimensions | Unit | |:|:-|:-| | ipv4.packets | received, sent, forwarded, delivered | packets/s | | ipv4.fragsout | ok, failed, created | packets/s | | ipv4.fragsin | ok, failed, all | packets/s | | ipv4.errors | InDiscards, OutDiscards, InHdrErrors, OutNoRoutes, InAddrErrors, InUnknownProtos | packets/s | There are no alerts configured by default for this integration. No action required. The configuration file name for this integration is `netdata.conf`. Configuration for this specific integration is located in the `[plugin:freebsd:net.inet.ip.stats]` section within that file. The file format is a modified INI syntax. The general structure is: ```ini [section1] option1 = some value option2 = some other value [section2] option3 = some third value ``` You can edit the configuration file using the `edit-config` script from the Netdata . ```bash cd /etc/netdata 2>/dev/null || cd /opt/netdata/etc/netdata sudo ./edit-config netdata.conf ``` <details><summary>Config options</summary> | Name | Description | Default | Required | |:-|:--|:-|:--:| | ipv4 packets | Enable or disable IPv4 packets metric. | yes | no | | ipv4 fragments sent | Enable or disable IPv4 fragments sent metric. | yes | no | | ipv4 fragments assembly | Enable or disable IPv4 fragments assembly metric. | yes | no | | ipv4 errors | Enable or disable IPv4 errors metric. | yes | no | </details> There are no configuration examples.
Project: Netdata (Observability and Analysis / Observability)
File: poc-without-k8s.md

These instructions are about installing a light version of Netdata Cloud, for clients who do not have a Kubernetes cluster installed. This setup is only for demonstration purposes, as it has no built-in resiliency on failures of any kind. Ubuntu 22.04 (clean installation will work best). 10 CPU Cores and 24 GiB of memory. Access to shell as a sudo. TLS certificate for Netdata Cloud On-Prem PoC. A single endpoint is required. The certificate must be trusted by all entities connecting to this installation. AWS ID and License Key - we should have provided this to you, if not contact us: <info@netdata.cloud>. To install the whole environment, log in to the designated host and run: ```bash curl https://netdata-cloud-netdata-static-content.s3.amazonaws.com/provision.sh -o provision.sh chmod +x provision.sh sudo ./provision.sh install \ -key-id "" \ -access-key "" \ -onprem-license-key "" \ -onprem-license-subject "" \ -onprem-url "" \ -certificate-path "" \ -private-key-path "" ``` What does the script do during installation? Prompts for user to provide: `-key-id` - AWS ECR access key ID. `-access-key` - AWS ECR Access Key. `-onprem-license-key` - Netdata Cloud On-Prem license key. `-onprem-license-subject` - Netdata Cloud On-Prem license subject. `-onprem-url` - URL for the On-prem (without http(s) protocol). `-certificate-path` - path to your PEM encoded certificate. `-private-key-path` - path to your PEM encoded key. After all the above installation will begin. The script will install: Helm Kubectl AWS CLI K3s cluster (single node) When all the required software is installed script starts to provision the K3s cluster with gathered data. After cluster provisioning netdata is ready to be used. WARNING: This script will automatically expose not only netdata but also a mailcatcher under `<URL from point 1.>/mailcatcher`. Only login by mail can work without further configuration. Every mail this Netdata Cloud On-Prem sends, will appear on the mailcatcher, which acts as the SMTP server with a simple GUI to read the mails. Steps: Open Netdata Cloud On-Prem PoC in the web browser on URL you specified Provide email and use the button to confirm Mailcatcher will catch all the emails so go to `<URL from point 1.>/mailcatcher`. Find yours and click the link. You are now logged into Netdata Cloud. Add your first nodes! To uninstall the whole PoC, use the same script that installed it, with the `uninstall` switch. ```shell cd <script dir> sudo ./provision.sh uninstall ```
Project: Litmus (Observability and Analysis / Chaos Engineering)
File: raspbernetes.md

is an open source project with multiple contributors for running Kubernetes clusters on Raspberry Pis. The project started with a goal to automate the setup and management of a Kubernetes cluster on Raspberry Pis. It aims to be completely declarative and idempotent. For internal workload pods and storage resilience (OpenEBS). This is to test built-in cluster resilience whilst running on arm64 architecture and building confidence in the design and overall architecture. To run on RPi based (home) Kubernetes clusters running personal production workloads. (, Maintainer) I reviewed several chaos tools and felt that Litmus being associated with CNCF and being an open-source tool aligns with my personal preference and values. It has a very active community and repository, and there was well-documented information that helped during the initial learning phases.
Project: Grafana (Observability and Analysis / Observability)
File: release-notes-8-4-7.md

hide_menu: true labels: products: cloud enterprise oss title: Release notes for Grafana 8.4.7 <!-- Auto generated by update changelog github action --> CloudWatch: Added missing MemoryDB Namespace metrics. , Histogram Panel: Take decimal into consideration. , TimeSeries: Sort tooltip values based on raw values. , API: Include userId, orgId, uname in request logging middleware. , Elasticsearch: Respect maxConcurrentShardRequests datasource setting. ,
Project: Checkmk (Observability and Analysis / Observability)
File: 16623.md

key | value | compatible | yes version | 2.4.0b1 date | 2024-03-11T14:37:28+00:00 level | 1 class | fix component | inv edition | cre When filtering the Checkmk versions -> #Sites inventory column, a crash occurs with ``` TypeError (expected string or bytes-like object) ... File "/omd/sites/oldstable/lib/python3/cmk/gui/query_filters.py", line 510, in <lambda> return lambda row: bool(regex.search(row.get(column, ""))) ``` This crash has been fixed.
Project: Grafana Pyroscope (Observability and Analysis / Observability)
File: querier.md

title: "Pyroscope querier" menuTitle: "Querier" description: "The querier evaluates Profiling queries." weight: 50 The querier is a stateless component that evaluates query expressions by fetching profiles series and labels on the read path. The querier uses the for gathering recently written data and the . You must configure the querier with the same `-ingester.ring.*` flags (or their respective YAML configuration parameters) that you use to configure the ingesters so that the querier can access the ingester hash ring and discover the addresses of the ingesters. For details about querier configuration, refer to .
Project: Netdata (Observability and Analysis / Observability)
File: hdfs_capacity_usage.md

This alert calculates the percentage of used space capacity across all DataNodes in the Hadoop Distributed File System (HDFS). If you receive this alert, it means that your HDFS DataNodes space capacity utilization is high. The alert is triggered into warning when the percentage of used space capacity across all DataNodes is between 70-80% and in critical when it is between 80-90%. Data is priceless. Before you perform any action, make sure that you have taken any necessary backup steps. Netdata is not liable for any loss or corruption of any data, database, or software. Inspect the Disk Usage for each DataNode: ``` root@netdata # hadoop dfsadmin -report ``` If all the DataNodes are in Disk pressure, you should consider adding more disk space. Otherwise, you can perform a balance of data between the DataNodes. Perform a balance: ``` root@netdata # hdfs balancer threshold 15 ``` This means that the balancer will balance data by moving blocks from over-utilized to under-utilized nodes, until each DataNodes disk usage differs by no more than plus or minus 15 percent. Review your Hadoop applications, jobs, and scripts that write data to HDFS. Identify the ones with excessive disk usage or logging. Optimize or refactor these applications, jobs, or scripts to reduce their disk usage. Delete any unnecessary or temporary files from HDFS, if safe to do so. Consider data compression or deduplication strategies, if applicable, to reduce storage usage in HDFS.
Project: Headlamp (Observability and Analysis / Observability)
File: plugin_registry.PodAttachEvent.md

title: "Interface: PodAttachEvent" linkTitle: "PodAttachEvent" slug: "plugin_registry.PodAttachEvent" .PodAttachEvent Event fired when attaching to a pod. data: `Object` | Name | Type | Description | | : | : | : | | `resource?` | | The resource for which the terminal was opened (currently this only happens for Pod instances). | | `status` | `OPENED` \| `CLOSED` | What exactly this event represents. 'OPEN' when the attach dialog is opened. 'CLOSED' when it is closed. | _ type: `POD_ATTACH`
Project: Grafana Pyroscope (Observability and Analysis / Observability)
File: tanka-jsonnet.md

description: Learn how to deploy Pyroscope on Kubernetes with Jsonnet and Tanka. keywords: Pyroscope deployment Kubernetes Jsonnet Tanka menuTitle: Deploy with Jsonnet and Tanka title: Deploy Pyroscope with Jsonnet and Tanka weight: 60 aliases: /docs/phlare/latest/operators-guide/deploying-grafana-phlare/jsonnet/ /docs/phlare/latest/deploy-kubernetes/tanka-jsonnet/ Grafana Labs publishes a library that you can use to deploy Pyroscope. The Jsonnet files are located in the and are using the helm charts as a source. You can use and to generate Kubernetes YAML manifests from the jsonnet files. Install `tanka` and `jb`: Follow the steps at . If you have `go` installed locally you can also use: ```console go install github.com/grafana/tanka/cmd/tk@latest go install github.com/jsonnet-bundler/jsonnet-bundler/cmd/jb@latest ``` Set up a Jsonnet project, based on the example that follows: Initialize Tanka Install Pyroscope and Kubernetes Jsonnet libraries Set up an environment ```console mkdir jsonnet-example && cd jsonnet-example tk init --k8s=1.21 jb install github.com/grafana/pyroscope/operations/pyroscope@main jb install github.com/grafana/jsonnet-libs/tanka-util@master tk env set environments/default --server-from-context=$(kubectl config current-context) ``` Decide if you want to run Pyroscope in the monolithic or the microservices mode Option A) For monolithic mode the file `environments/default/main.jsonnet`, should look like; ```jsonnet local pyroscope = import 'pyroscope/jsonnet/pyroscope/pyroscope.libsonnet'; local tk = import 'tk'; pyroscope.new(overrides={ namespace: tk.env.spec.namespace, }) ``` Option B) For microservices mode the file `environments/default/main.jsonnet`, should look like; ```jsonnet local pyroscope = import 'pyroscope/jsonnet/pyroscope/pyroscope.libsonnet'; local valuesMicroServices = import 'pyroscope/jsonnet/values-micro-services.json'; local tk = import 'tk'; pyroscope.new(overrides={ namespace: tk.env.spec.namespace, values+: valuesMicroServices, }) ``` Generate the Kubernetes YAML manifests and store them in the `./manifests` directory: ```console tk show environments/default tk export ./manifests environments/default ``` Deploy the manifests to a Kubernetes cluster, in one of two ways: Use the `tk apply` command. Tanka supports commands to show the `diff` and `apply` changes to a Kubernetes cluster: ```console tk diff environments/default tk apply environments/default ``` Use the `kubectl apply` command. You generated the Kubernetes manifests and stored them in the `./manifests` directory in the previous step. You can run the following command to directly apply these manifests to your Kubernetes cluster: ```console kubectl apply --dry-run=client -k manifests/ kubectl apply -k manifests/ ``` > Note: The generated Kubernetes manifests create resources in the `default` namespace. To use a different namespace, change the `namespace` configuration option in the `environments/default/main.jsonnet` file, and re-generate the Kubernetes manifests.
Project: Elastic (Observability and Analysis / Observability)
File: ceil.md

<!-- This is generated by ESQL's AbstractFunctionTestCase. Do no edit it. See ../README.md for how to regenerate it. --> Round a number up to the nearest integer. ``` ROW a=1.8 | EVAL a=CEIL(a) ``` Note: This is a noop for `long` (including unsigned) and `integer`. For `double` this picks the closest `double` value to the integer similar to Math.ceil.
Project: Graylog (Observability and Analysis / Observability)
File: ReactGridContainer.md

Regular `ReactGridContainer`: ```js import createReactClass from 'create-react-class'; const ReactGridContainerExample = createReactClass({ getInitialState() { return { positions: { '1': { col: 0, row: 0, height: 1, width: 2 }, '2': { col: 2, row: 0, height: 1, width: 4 }, '3': { col: 6, row: 0, height: 1, width: 2 }, '4': { col: 8, row: 0, height: 1, width: 4 }, }, }; }, onPositionsChange(nextPositions) { console.log('positions changed to ', nextPositions); }, widgetDiv(id) { return ( <div key={id} style={{ backgroundColor: '#f9f9f9', fontSize: '6em', textAlign: 'center' }}> {id} </div> ); }, render() { const { positions } = this.state; const columns = { xxl: 6, xl: 5, lg: 4, md: 4, sm: 4, xs: 4, }; return ( <ReactGridContainer positions={positions} onPositionsChange={this.onPositionsChange} columns={columns}> {this.widgetDiv(1)} {this.widgetDiv(2)} {this.widgetDiv(3)} {this.widgetDiv(4)} </ReactGridContainer> ); }, }); <ReactGridContainerExample /> ``` Lock or block resizing in `ReactGridContainer`: ```js import createReactClass from 'create-react-class'; import { Button, ButtonToolbar } from 'components/bootstrap'; const ReactGridContainerExampleLocked = createReactClass({ getInitialState() { return { positions: { '1': { col: 0, row: 0, height: 1, width: 2 }, '2': { col: 2, row: 0, height: 1, width: 4 }, '3': { col: 6, row: 0, height: 1, width: 2 }, '4': { col: 8, row: 0, height: 1, width: 4 }, }, locked: false, isResizable: false, }; }, onPositionsChange(nextPositions) { console.log('positions changed to ', nextPositions); }, toggleLocked() { this.setState({ locked: !this.state.locked }); }, toggleIsResizable() { this.setState({ isResizable: !this.state.isResizable }); }, widgetDiv(id) { return ( <div key={id} style={{ backgroundColor: '#f9f9f9', fontSize: '6em', textAlign: 'center' }}> {id} </div> ); }, render() { const { positions, locked, isResizable } = this.state; const columns = { xxl: 6, xl: 5, lg: 4, md: 4, sm: 4, xs: 4, }; return ( <div> <ButtonToolbar> <Button bsStyle="info" active={locked} onClick={this.toggleLocked}> Locked is {String(locked)} </Button> <Button bsStyle="info" active={isResizable} onClick={this.toggleIsResizable}> isResizable is {String(isResizable)} </Button> </ButtonToolbar> <br/> <ReactGridContainer positions={positions} onPositionsChange={this.onPositionsChange} columns={columns} rowHeight={100} locked={locked} isResizable={isResizable}> {this.widgetDiv(1)} {this.widgetDiv(2)} {this.widgetDiv(3)} {this.widgetDiv(4)} </ReactGridContainer> </div> ); }, }); <ReactGridContainerExampleLocked /> ```
Project: Netdata (Observability and Analysis / Observability)
File: okta_sso.md

<!--startmeta customediturl: "https://github.com/netdata/netdata/edit/master/integrations/cloud-authentication/integrations/okta_sso.md" meta_yaml: "https://github.com/netdata/netdata/edit/master/integrations/cloud-authentication/metadata.yaml" sidebar_label: "Okta SSO" learn_status: "Published" learnrelpath: "Netdata Cloud/Authentication & Authorization/Cloud Authentication & Authorization Integrations" message: "DO NOT EDIT THIS FILE DIRECTLY, IT IS GENERATED BY THE AUTHENTICATION'S metadata.yaml FILE" endmeta--> <img src="https://netdata.cloud/img/okta.png" width="150"/> Integrate your organization's Okta account with Netdata to better manage your team's access controls to Netdata Cloud. <img src="https://img.shields.io/badge/maintained%20by-Netdata-%2300ab44" /> An Okta account A Netdata Cloud account Access to the Space as an Admin Space needs to be on a paid plan Steps needed to be done on Okta Admin Portal: Click on Applications tab and choose to Browse App Catalogue Find Netdata's preconfigured app for easy setup and click Add Integration Give the app, that will be in your apps dashboard, the preferred Application label and click Next to move to the Sign-On options tab In the Sign-On Options all the values we expect are already filled and no additional data is required Click Done. You are able to go back and edit any fields later if need be Go to the Assignments tab and enter the People or Group assignments as per your organizations policies Click on the Space settings cog (located above your profile icon) Click on the Authentication tab On the Okta SSO card, click on Configure Fill in the , you get them from Okta Admin Portal: Issuer URL you can get it from your profile icon on top, e.g. `https://company-name.okta.com` Client ID you can get it from General tab on application you configured on Okta Client Secret you can get it from General tab on application you configured on Okta SP-initiated SSO (Single Sign-On) IdP-initiated SSO If you start your authentication flow from Netdata sign-in page please check .
Project: Graylog (Observability and Analysis / Observability)
File: Colors.md

All colors are available via the ThemeProvider `theme.color` prop Click any color block below to copy the color path. ```jsx noeditor import React, { useEffect } from 'react'; import styled, { useTheme } from 'styled-components'; import chroma from 'chroma-js'; import ColorSwatch from './Colors'; const { colors } = useTheme(); const CategoryTitle = styled.h3` margin: 0 0 6px; `; const SubcategoryName = styled.h4` margin: 0 0 6px; `; const Swatches = styled.div` display: flex; margin: 0 0 15px; flex-wrap: wrap; `; const StyledColorSwatch = styled(ColorSwatch)` flex-basis: ${(props) => props.categoryName === 'global' ? '100px' : '1px'}; max-width: ${(props) => props.categoryName === 'global' ? '200px' : 'auto'}; button { margin-right: 6px; margin-bottom: 3px; &:last-of-type { margin: 0; } } `; const getValues = (data = {}, callback = () => {}) => { return Object.keys(data).map((key) => callback(key)); } const CategoryWrap = (categoryName, categoryColors) => ( <> <Swatches> {getValues(categoryColors, (name) => { if (typeof categoryColors[name] === 'string' && chroma.valid(categoryColors[name])) { const copyTextName = categoryName === 'gray' ? `${categoryName}[${name}]` : `${categoryName}.${name}`; return ( <StyledColorSwatch name={name} section={categoryName} color={categoryColors[name]} copyText={`theme.colors.${copyTextName}`} key={`${categoryName}-${name}`} /> ) } })} </Swatches> <div> {getValues(categoryColors, (name) => typeof categoryColors[name] === 'object' && ( <div key={`${categoryName}-${name}`}> <SubcategoryName>{categoryName} &mdash; {name}</SubcategoryName> <Swatches> {getValues(categoryColors[name], (subname) => ( <StyledColorSwatch name={subname} categoryName={categoryName} color={categoryColors} copyText={`theme.colors.${categoryName}.${name}.${subname}`} key={`${categoryName}-${name}-${categoryColors}`} /> ))} </Swatches> </div> ) )} </div> </> ); const Colors = () => ( <> {getValues(colors, (categoryName) => ( <div key={categoryName}> <CategoryTitle key={`title-${categoryName}`}>{categoryName}</CategoryTitle> {CategoryWrap(categoryName, colors[categoryName])} </div> ))} </> ); <Colors /> ```
Project: Krkn (Observability and Analysis / Chaos Engineering)
File: service_disruption_scenarios.md

Using this type of scenario configuration one is able to delete crucial objects in a specific namespace, or a namespace matching a certain regex string. Configuration Options: namespace: Specific namespace or regex style namespace of what you want to delete. Gets all namespaces if not specified; set to "" if you want to use the label_selector field. Set to '^.*$' and label_selector to "" to randomly select any namespace in your cluster. label_selector: Label on the namespace you want to delete. Set to "" if you are using the namespace variable. delete_count: Number of namespaces to kill in each run. Based on matching namespace and label specified, default is 1. runs: Number of runs/iterations to kill namespaces, default is 1. sleep: Number of seconds to wait between each iteration/count of killing namespaces. Defaults to 10 seconds if not set Refer to config file. ``` scenarios: namespace: "^.*$" runs: 1 namespace: "^.ingress.$" runs: 1 sleep: 15 ``` This scenario will select a namespace (or multiple) dependent on the configuration and will kill all of the below object types in that namespace and will wait for them to be Running in the post action Services Daemonsets Statefulsets Replicasets Deployments We do a post chaos check to wait and verify the specific objects in each namespace are Ready Here there are two options: Pass a custom script in the main config scenario list that will run before the chaos and verify the output matches post chaos scenario. See for an example ``` namespace_scenarios: - scenarios/regex_namespace.yaml scenarios/postactionnamespace.py ``` Allow kraken to wait and check all killed objects in the namespaces become 'Running' again. Kraken keeps a list of the specific objects in namespaces that were killed to verify all that were affected recover properly. ``` wait_time: <seconds to wait for namespace to recover> ```
Project: Litmus (Observability and Analysis / Chaos Engineering)
File: TRAINING_AND_COURSES.md

Here is a list of training and courses related to LitmusChaos available out there. LitmusChaos is a CNCF project which does not endorse any particular course. If you have created a training or course for LitmusChaos and wish to add the same, please raise a PR against this document.
Project: Weave Scope (Observability and Analysis / Observability)
File: ISSUE_TEMPLATE.md

What version of Go are you running? (Paste the output of `go version`) What version of gorilla/mux are you at? (Paste the output of `git rev-parse HEAD` inside `$GOPATH/src/github.com/gorilla/mux`) Describe your problem (and what you have tried so far) Paste a minimal, runnable, reproduction of your issue below (use backticks to format it)