cwielenb/CNCF-Dataset huggingface dataset:
Project: Graylog (Observability and Analysis / Observability)
File: Tabs.md

```js import { Tab } from 'components/bootstrap'; <Tabs defaultActiveKey={2} id="uncontrolled-tab-example"> <Tab eventKey={1} title="Tab 1"> Tab 1 content </Tab> <Tab eventKey={2} title="Tab 2"> Tab 2 content </Tab> <Tab eventKey={3} title="Tab 3" disabled> Tab 3 content </Tab> </Tabs> ``` ```js import { Tab } from 'components/bootstrap'; const TabExample = () => { const [activeTab, setActiveTab] = React.useState(1); const handleSetActive = (key) => { alert(`Switching to Tab ${key}`); setActiveTab(key); } return ( <Tabs activeKey={activeTab} onSelect={handleSetActive} id="controlled-tab-example" > <Tab eventKey={1} title="Tab 1"> Tab 1 content </Tab> <Tab eventKey={2} title="Tab 2"> Tab 2 content </Tab> <Tab eventKey={3} title="Tab 3"> Tab 3 content </Tab> </Tabs> ) } <TabExample /> ``` ```js import { Row, Col, Nav, NavItem, NavDropdown, MenuItem, Tab } from 'components/bootstrap'; <Tab.Container defaultActiveKey="first" id="drodown-tab-example"> <Row className="clearfix"> <Col sm={12}> <Nav bsStyle="tabs"> <NavItem eventKey="first">Tab 1</NavItem> <NavItem eventKey="second">Tab 2</NavItem> <NavDropdown eventKey="3" title="Dropdown"> <MenuItem eventKey="3.1">Action</MenuItem> <MenuItem eventKey="3.2">Another action</MenuItem> <MenuItem eventKey="3.3">Something else here</MenuItem> <MenuItem divider /> <MenuItem eventKey="3.4">Separated link</MenuItem> </NavDropdown> </Nav> </Col> <Col sm={12}> <Tab.Content animation> <Tab.Pane eventKey="first">Tab 1 content</Tab.Pane> <Tab.Pane eventKey="second">Tab 2 content</Tab.Pane> <Tab.Pane eventKey="3.1">Tab 3.1 content</Tab.Pane> <Tab.Pane eventKey="3.2">Tab 3.2 content</Tab.Pane> <Tab.Pane eventKey="3.3">Tab 3.3 content</Tab.Pane> <Tab.Pane eventKey="3.4">Tab 3.4 content</Tab.Pane> </Tab.Content> </Col> </Row> </Tab.Container> ```
Project: Headlamp (Observability and Analysis / Observability)
File: lib_k8s_validatingWebhookConfiguration.KubeValidatingWebhookConfiguration.md

title: "Interface: KubeValidatingWebhookConfiguration" linkTitle: "KubeValidatingWebhookConfiguration" slug: "libk8svalidatingWebhookConfiguration.KubeValidatingWebhookConfiguration" .KubeValidatingWebhookConfiguration `KubeValidatingWebhookConfiguration` `Optional` apiVersion: `string` . _ kind: `string` Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. In CamelCase. Cannot be updated. `see` . _ metadata: . _ webhooks: { `admissionReviewVersions`: `string` ; `failurePolicy?`: `string` ; `matchPolicy?`: `string` ; `name`: `string` ; `namespaceSelector?`: { `matchExpressions`: `undefined` \| { `key`: `string` ; `operator`: `string` ; `values`: `string`[] ; `sideEffects?`: `string` ; `timeoutSeconds?`: `number` }[]
Project: OpenSearch (Observability and Analysis / Observability)
File: opensearch.release-notes-1.3.6.md

Update to Netty 4.1.80.Final () Revert to Netty 4.1.79.Final () Bumps jackson and snakeyaml dependencies () Bump commons-configuration2 from 2.7 to 2.8.0 in /plugins/repository-hdfs () Set analyzer to regex query string search ()
Project: Netdata (Observability and Analysis / Observability)
File: ip_virtual_server.md

<!--startmeta customediturl: "https://github.com/netdata/netdata/edit/master/src/collectors/proc.plugin/integrations/ipvirtualserver.md" meta_yaml: "https://github.com/netdata/netdata/edit/master/src/collectors/proc.plugin/metadata.yaml" sidebar_label: "IP Virtual Server" learn_status: "Published" learnrelpath: "Collecting Metrics/Linux Systems/Network" 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-wired.svg" width="150"/> Plugin: proc.plugin Module: /proc/net/ipvsstats <img src="https://img.shields.io/badge/maintained%20by-Netdata-%2300ab44" /> This integration monitors IP Virtual Server statistics 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. This scope has no labels. Metrics: | Metric | Dimensions | Unit | |:|:-|:-| | ipvs.sockets | connections | connections/s | | ipvs.packets | received, sent | packets/s | | ipvs.net | received, sent | kilobits/s | There are no alerts configured by default for this integration. No action required. There is no configuration file. There are no configuration options. There are no configuration examples.
Project: Grafana (Observability and Analysis / Observability)
File: release-notes-8-0-4.md

_build: list: false labels: products: cloud enterprise oss title: Release notes for Grafana 8.0.4 <!-- Auto generated by update changelog github action --> Live: Rely on app url for origin check. , PieChart: Sort legend descending, update placeholder to show default . , TimeSeries panel: Do not reinitialize plot when thresholds mode change. , Elasticsearch: Allow case sensitive custom options in date_histogram interval. , Elasticsearch: Restore previous field naming strategy when using variables. , Explore: Fix import of queries between SQL data sources. , InfluxDB: InfluxQL query editor: fix retention policy handling. , Loki: Send correct time range in template variable queries. , TimeSeries: Preserve RegExp series overrides when migrating from old graph panel. ,
Project: VictoriaMetrics (Observability and Analysis / Observability)
File: CHANGES.md

provide unmarshal options for streams () () bump protobuf dep to v1.33 () () v2/callctx:* fix SetHeader race by cloning header map () () add XGoogFieldMaskHeader constant () () v2/callctx:* add new callctx package () () v2:* add BuildHeaders and InsertMetadataIntoOutgoingContext to header () () v2:* add GoVersion package variable () () v2:* handle space in non-devel go version () () update dependencies () () v2:* drop cloud lro test dep () (), refs apierror:* add method to return HTTP status code conditionally () (), refs add ref to usage with clients () (), refs v2:* add WithTimeout option () () v2/apierror:* return Unknown GRPCStatus when err source is HTTP () (), refs update google.golang.org/api to latest () () v2/apierror:* add apierror.FromWrappingError () () v2:* copy DetermineContentType functionality () () v2:* resolve bad genproto pseudoversion in go.mod () () add ExtractProtoMessage to apierror () () v2:* add OnHTTPCodes CallOption () () v2/apierror:* use errors.As in FromError () () v2:* bump release-please processing () ()
Project: Graylog (Observability and Analysis / Observability)
File: TableList.md

```js import createReactClass from 'create-react-class'; import Immutable from 'immutable'; import { Button } from 'components/bootstrap'; const TableListExample = createReactClass({ getInitialState() { return { items: Immutable.List([ { id: '1', title: 'One', secret_key: 'uno', description: 'First number' }, { id: '2', title: 'Two', secret_key: 'dos', description: 'Second number' }, { id: '3', title: 'Three', secret_key: 'tres', description: 'Third number' }, { id: '4', title: 'Four', secret_key: 'cuatro', description: 'Fourth number' }, { id: '5', title: 'Five', secret_key: 'cinco', description: 'Fifth number' }, ]), }; }, action(text) { return () => { alert(`This is an action for "${text}"`); }; }, bulkActionsFactory(selectedNumbers) { return ( <Button bsStyle="info" bsSize="xsmall" onClick={this.action(selectedNumbers.join(', '))}> Bulk-operation </Button> ); }, itemActionsFactory(selectedNumber) { return ( <Button bsStyle="primary" bsSize="xsmall" onClick={this.action(JSON.stringify(selectedNumber))}> Do something </Button> ); }, render() { const { items } = this.state; return ( <TableList items={items} filterKeys={['title', 'secret_key']} bulkActionsFactory={this.bulkActionsFactory} itemActionsFactory={this.itemActionsFactory} /> ); }, }); <TableListExample /> ``` ```js import createReactClass from 'create-react-class'; import Immutable from 'immutable'; import { Button } from 'components/bootstrap'; const TableListExampleNoBulkActions = createReactClass({ getInitialState() { return { items: Immutable.List([ { id: '1', title: 'One', secret_key: 'uno', description: 'First number' }, { id: '2', title: 'Two', secret_key: 'dos', description: 'Second number' }, { id: '3', title: 'Three', secret_key: 'tres', description: 'Third number' }, { id: '4', title: 'Four', secret_key: 'cuatro', description: 'Fourth number' }, { id: '5', title: 'Five', secret_key: 'cinco', description: 'Fifth number' }, ]), }; }, action(text) { return () => { alert(`This is an action for "${text}"`); }; }, itemActionsFactory(selectedNumber) { return ( <Button bsStyle="primary" bsSize="xsmall" onClick={this.action(JSON.stringify(selectedNumber))}> Do something </Button> ); }, render() { const { items } = this.state; return ( <TableList items={items} enableFilter={false} enableBulkActions={false} itemActionsFactory={this.itemActionsFactory} /> ); }, }); <TableListExampleNoBulkActions /> ```
Project: Headlamp (Observability and Analysis / Observability)
File: plugin_registry.DeleteResourceEvent.md

title: "Interface: DeleteResourceEvent" linkTitle: "DeleteResourceEvent" slug: "plugin_registry.DeleteResourceEvent" .DeleteResourceEvent Event fired when a resource is to be deleted. <`HeadlampEventType.DELETE_RESOURCE`\> `DeleteResourceEvent` data: `Object` | Name | Type | Description | | : | : | : | | `resource` | `any` | The resource for which the deletion was called. | | `status` | `CONFIRMED` | What exactly this event represents. 'CONFIRMED' when the user confirms the deletion of a resource. For now only 'CONFIRMED' is sent. | . _ type: `DELETE_RESOURCE` .
Project: Vector (Observability and Analysis / Observability)
File: rollout.md

title: Rollout description: Strategies for rolling Vector out to production environments. weight: 5 {{< warning >}} This document assumes youve already decided on an architecture. If you have not, please read the . {{< /warning >}} Vector is designed to be deployed anywhere in your infrastructure, making it possible to follow the best practice of deploying within your network boundaries and avoiding a single point of failure. Our rollout strategy takes advantage of this through , , allowing for , and of switching to a new system. If you follow our , then you should deploy Vector within each network partition (i.e., cluster or VPC), one at a time. This makes it easy to adopt Vector incrementally, allowing for sustainable progress while building out your observability pipeline. Minimizing scope is the easiest way to ensure success. The scope should be minimized to one network partition and one system at a time. Then, follow the for each unit of scope. While setting up Vector, it should be allowed to fail without consequence to your business. This means Vector should be operating on a redundant stream of data without disrupting your current production workflows. This allows you to gain confidence in Vector before your business depends on it. Finally, by the time you cut over to Vector, you should have confidence in its ability. It should already be operating in a production capacity over a sustained period, removing any doubt that Vector will perform reliably in your production environment. {{< info >}} Follow this plan for each deployment within each network partition. {{< /info >}} (i.e., cluster or VPC) for your Vector deployment. with a single `blackhole` sink (the default) within that network partition. Vectors instances for the . Stream a copy of data from your agents to Vector. Verify that Vector receives data via the `vector top` and `vector tap` commands. Process your data according to your use cases. Integrate Vector with your downstream systems. Verify data within each destination. Enable so that Vector can scale down appropriately. Soak Vector for at least 24 hours and monitor performance to ensure production readiness. Safely shut down your agents to allow them to drain data without loss. Reconfigure your agents to send data to Vector exclusively. Start your agents. {{< success >}} Repeat for each network partition. {{< /success >}} For easy setup and maintenance of this architecture, consider Datadog Observability Pipelines, which comes with support.
Project: Grafana (Observability and Analysis / Observability)
File: release-notes-8-3-3.md

_build: list: false labels: products: cloud enterprise oss title: Release notes for Grafana 8.3.3 <!-- Auto generated by update changelog github action --> BarChart: Use new data error view component to show actions in panel edit. , CloudMonitor: Iterate over pageToken for resources. , Macaron: Prevent WriteHeader invalid HTTP status code panic. , AnnoListPanel: Fix interpolation of variables in tags. , CloudWatch: Allow queries to have no dimensions specified. , CloudWatch: Fix broken queries for users migrating from 8.2.4/8.2.5 to 8.3.0. , CloudWatch: Make sure MatchExact flag gets the right value. , Dashboards: Fix so that empty folders can be deleted from the manage dashboards/folders page. , InfluxDB: Improve handling of metadata query errors in InfluxQL. , Loki: Fix adding of ad hoc filters for queries with parser and line_format expressions. , Prometheus: Fix running of exemplar queries for non-histogram metrics. , Prometheus: Interpolate template variables in interval. , StateTimeline: Fix toolitp not showing when for frames with multiple fields. , TraceView: Fix virtualized scrolling when trace view is opened in right pane in Explore. , Variables: Fix repeating panels for on time range changed variables. , Variables: Fix so queryparam option works for scoped variables. ,
Project: Netdata (Observability and Analysis / Observability)
File: btrfs_device_read_errors.md

This alert monitors the number of BTRFS read errors on a device. If you receive this alert, it means that your system has encountered at least one BTRFS read error in the last 10 minutes. BTRFS (B-Tree File System) is a modern file system designed for Linux. BTRFS read errors are instances where the file system fails to read data from a device. This can occur due to various reasons like hardware failure, file system corruption, or disk problems. Check system logs for BTRFS errors Review the output from the following command to identify any BTRFS errors: ``` sudo journalctl -k | grep -i BTRFS ``` Identify the affected BTRFS device and partition List all BTRFS devices with their respective information by running the following command: ``` sudo btrfs filesystem show ``` Perform a BTRFS filesystem check To check the integrity of the BTRFS file system, run the following command, replacing `<device>` with the affected device path: ``` sudo btrfs check --readonly <device> ``` Note: Be careful when using the `--repair` option, as it may cause data loss. It is recommended to take a backup before attempting a repair. Verify the disk health Check the disk health using SMART tools to determine if there are any hardware issues. This can be done by first installing `smartmontools` if not already installed: ``` sudo apt install smartmontools ``` Then running a disk health check on the affected device: ``` sudo smartctl -a <device> ``` Analyze the read error patterns If the read errors are happening consistently or increasing, consider replacing the affected device with a new one or adding redundancy to the system by using RAID or BTRFS built-in features.
Project: Vector (Observability and Analysis / Observability)
File: gcp_stackdriver_logs.md

title: GCP Operations (formerly Stackdriver) logs description: Deliver logs to GCP's suite short: GCP Stackdriver component_kind: sink layout: component tags: ["gcp", "stackdriver", "operations", "component", "sink", "logs"] {{/* This doc is generated using: The template in layouts/docs/component.html The relevant CUE data in cue/reference/components/... */}}
Project: Grafana Pyroscope (Observability and Analysis / Observability)
File: setup-docker.md

title: "Setup eBPF Profiling on Docker" menuTitle: "Setting up on Docker" description: "Setting up eBPF Profiling with Grafana Agent on Docker" weight: 20 To set up eBPF profiling with Grafana Agent on Linux, you need to: Verify that your system meets the requirements. Create a Grafana Agent configuration file. For more information, refer to the . Run Grafana Agent or Grafana Alloy. Verify that profiles are received. {{< docs/shared lookup="agent-deprecation.md" source="alloy" version="next" >}} Before you begin, you need: A Pyroscope server where the agent will send profiling data. Access to Grafana with the provisioned. installed. {{% admonition type="note" %}} If you don't have a Grafana and/or a Pyroscope server, you can use the free plan to get started. {{% /admonition %}} The eBPF profiler requires a Linux kernel version >= 4.9 (due to ). `BPFPROGTYPEPERFEVENT` is a type of eBPF program that can be attached to hardware or software events, such as performance monitoring counters or tracepoints, in the Linux kernel. To print the kernel version of your docker host, run: ```shell docker info | grep Kernel ``` Make sure you have a kernel version >= 4.9. You can configure the Grafana Agent eBPF profiler to profile local containers. To do so, use the `discovery.docker` component to discover local containers and the `pyroscope.ebpf` component to profile them. Create a file named `agent.river` with the following content: ```river discovery.docker "local_containers" { host = "unix:///var/run/docker.sock" } pyroscope.ebpf "instance" { forward_to = [pyroscope.write.endpoint.receiver] targets = discovery.docker.local_containers.targets } pyroscope.write "endpoint" { endpoint { basic_auth { password = "<PASSWORD>" username = "<USERNAME>" } url = "<URL>" } external_labels = { "env" = "testing", "instance" = env("HOSTNAME"), } } ``` Replace the `<URL>` placeholder with the appropriate server URL. This could be the Grafana Cloud URL or your own custom Pyroscope server URL. If you need to send data to Grafana Cloud, you'll have to configure HTTP Basic authentication. Replace `<User>` with your Grafana Cloud stack user and `<Password>` with your Grafana Cloud API key. {{% admonition type="note" %}} If you're using your own Pyroscope server, you can remove the `basic_auth` section altogether. {{% /admonition %}} For more information, refer to the . To start Grafana Agent with Docker, run: ```shell docker run \ -e AGENT_MODE=flow \ -v $PWD/agent.river:/etc/agent/config.river \ -v /var/run/docker.sock:/var/run/docker.sock \ --pid=host \ --privileged \ -p 12345:12345 \ grafana/agent:latest \ run --server.http.listen-addr=0.0.0.0:12345 /etc/agent/config.river ``` Note: The `--pid=host` and `--privileged` flags are required to profile local containers with ebpf. To verify that the profiles are received by the Pyroscope server, go to the Pyroscope UI or . Then select a profile type and a service from the dropdown menu.
Project: Loggie (Observability and Analysis / Observability)
File: MAINTAINERS.md

This page lists all active maintainers of this repository. If you were a maintainer and would like to add your name to the Emeritus list, please send us a PR. See for governance guidelines and how to become a maintainer. See for general contribution guidelines. , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC , Google LLC
Project: Headlamp (Observability and Analysis / Observability)
File: lib_k8s_cluster.KubeContainerProbe.md

title: "Interface: KubeContainerProbe" linkTitle: "KubeContainerProbe" slug: "libk8scluster.KubeContainerProbe" .KubeContainerProbe `Optional` exec: `Object` | Name | Type | | : | : | | `command` | `string`[] | _ `Optional` failureThreshold: `number` _ `Optional` httpGet: `Object` | Name | Type | | : | : | | `host?` | `string` | | `path?` | `string` | | `port` | `number` | | `scheme` | `string` | _ `Optional` initialDelaySeconds: `number` _ `Optional` periodSeconds: `number` _ `Optional` successThreshold: `number` _ `Optional` tcpSocket: `Object` | Name | Type | | : | : | | `port` | `number` | _ `Optional` timeoutSeconds: `number`
Project: Grafana Loki (Observability and Analysis / Observability)
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: Checkmk (Observability and Analysis / Observability)
File: 16176.md

key | value | compatible | yes version | 2.4.0b1 date | 2024-03-13T09:57:01+00:00 level | 1 class | fix component | checks edition | cre Previously, Checkmk agent used the data from /proc to determine if Postfix instance is running. Since docker containers don't have permissions to read /proc, the agent always reported the Postfix instance as 'not running'. This resulted in CRIT 'Postfix status' service even if Postfix instance was running correctly.
Project: Vector (Observability and Analysis / Observability)
File: 2020-04-01-more-condition-predicates.md

date: "2020-04-13" title: "More Condition Predicates" description: "More options when filtering and routing events" authors: ["binarylogic"] pr_numbers: [1997, 2183, 2198] release: "0.9.0" hideonrelease_notes: true badges: type: "enhancement" domains: ["config", "transforms"] transforms: ["filter", "swimlanes"] Vector has a concept "conditions" that are used to qualify events. For example, this is used in Vector's , , and . This change adds new predicates that enable powerful matching and condition expression. Specifically, the following predicates were added: `begins_with` `contains` `ends_with` `is_log` `is_metric` `regex` For example, you can filter all messages that contain the `error` term with the new `contains` predicate: ```toml [transforms.errors] type = "filter" condition."message.contain" = "error" ``` The world is your oyster.