cwielenb/CNCF-Dataset huggingface dataset:
Project: SkyWalking (Observability and Analysis / Observability)
File: telegraf-receiver.md

The Telegraf receiver supports receiving InfluxDB Telegraf's metrics by meter-system. The OAP can load the configuration at bootstrap. The files are located at `$CLASSPATH/telegraf-rules`. If the new configuration is not well-formed, the OAP may fail to start up. This is the Document, the Telegraf receiver can handle Telegraf's , . There are many other telegraf input plugins, users can customize different input plugins' rule files. The rule file should be in YAML format, defined by the scheme described in . Please see the for more input plugins information. Notice: The Telegraf receiver module uses `HTTP` to receive telegraf's metrics, so the outputs method should be set `[[outputs.http]]` in telegraf.conf file. Please see the for more details. The Telegraf receiver module only* process telegraf's `JSON` metrics format, the data format should be set `data_format = "json"` in telegraf.conf file. Please see the for more details. The default `jsontimestampunits` is second in JSON output, and the Telegraf receiver module only process `second` timestamp unit. If users configure `jsontimestampunits` in telegraf.conf file, `jsontimestampunits = "1s"` is feasible. Please see the for more details. The following is the default telegraf receiver YAML rule file in the `application.yml`, Set `SWRECEIVERTELEGRAF:default` through system environment or change `SWRECEIVERTELEGRAFACTIVEFILES:vm` to activate the OpenTelemetry receiver with `vm.yml` in telegraf-rules. ```yaml receiver-telegraf: selector: ${SWRECEIVERTELEGRAF:default} default: activeFiles: ${SWRECEIVERTELEGRAFACTIVEFILES:vm} ``` | Rule Name | Description | Configuration File | Data Source | |--|-||-| | vm | Metrics of VMs | telegraf-rules/vm.yaml | Telegraf inputs plugins --> Telegraf Receiver --> SkyWalking OAP Server |
Project: Inspektor Gadget (Observability and Analysis / Observability)
File: mountsnoop.md

title: Gadget mountsnoop mountsnoop traces mount and umount syscalls ```yaml apiVersion: gadget.kinvolk.io/v1alpha1 kind: Trace metadata: name: mountsnoop namespace: gadget spec: node: ubuntu-hirsute gadget: mountsnoop runMode: Manual outputMode: Stream filter: namespace: default ``` Start mountsnoop gadget ```bash $ kubectl annotate -n gadget trace/mountsnoop \ gadget.kinvolk.io/operation=start ``` Stop mountsnoop gadget ```bash $ kubectl annotate -n gadget trace/mountsnoop \ gadget.kinvolk.io/operation=stop ``` Stream
Project: Flagsmith (Observability and Analysis / Feature Flagging)
File: github.md

title: GitHub description: View your Flagsmith flags inside GitHub sidebar_position: 10 hide_title: true <img src="/img/integrations/github/github-logo.svg" alt="GitHub Logo" width="30%" height="30%"/> View your Flagsmith Flags inside your GitHub Issues and Pull Request :::tip The GitHub integration is currently only supported with our hosted Flagsmith SaaS service. ::: In the Integrations Option in the side bar, find the GitHub integration and click on 'Add Integration'. A window will open asking you to select an organization you belong to. Select the repositories and save. In the Flagsmith application, the button will now say "Manage Integration", click on it. Finally, select the repository you wish to link. In GitHub, add the app from the . Select your organisation. Select your repositories where you want install the app. You will be redirected back to the Flagsmith app to finish the integration setup. Select your Flagsmith Organisation. Select the Flagmsith Project you want to associate with the repository where the app was installed to create the Integration. Create or select a Feature Flag. Go to settings section. Select your integration. Select GitHub Issue or GitHub PR. Select your external resource and save. In the Integrations Option in the side bar, find the GitHub integration and click on 'Manage Integration'. Click on 'Delete Integracion' button, and confirm. In your GitHub organisation, uninstall the Flagsmith GitHub App.
Project: Tracetest (Observability and Analysis / Observability)
File: tracetest_completion_bash.md

Generate the autocompletion script for bash Generate the autocompletion script for the bash shell. This script depends on the 'bash-completion' package. If it is not installed already, you can install it via your OS's package manager. To load completions in your current shell session: ``` source <(tracetest completion bash) ``` To load completions for every new session, execute once: ``` tracetest completion bash > /etc/bash_completion.d/tracetest ``` ``` tracetest completion bash > $(brew --prefix)/etc/bash_completion.d/tracetest ``` You will need to start a new shell for this setup to take effect. ``` tracetest completion bash ``` ``` -h, --help help for bash --no-descriptions disable completion descriptions ``` ``` -c, --config string config file will be used by the CLI (default "config.yml") -o, --output string output format [pretty|json|yaml] -s, --server-url string server url -v, --verbose display debug information ``` - Generate the autocompletion script for the specified shell
Project: Netdata (Observability and Analysis / Observability)
File: postgres_txid_exhaustion_perc.md

This alert monitors the percentage of transaction ID (TXID) exhaustion in a PostgreSQL database, specifically the rate at which the system is approaching a `TXID wraparound`. If the alert is triggered, it means that your PostgreSQL database is more than 90% towards exhausting its available transaction IDs, and you should take action to prevent transaction ID wraparound. In PostgreSQL, transaction IDs are 32-bit integers, and a new one is assigned to each new transaction. Once the system has used all possible 32-bit integers for transaction IDs, it wraps back around to the beginning, reusing previous transaction IDs. This wraparound can lead to data loss or database unavailability if transactions' tuple visibility information becomes muddled. Check the number of remaining transactions before wraparound. Connect to your PostgreSQL database, and run the following SQL query: ```sql SELECT datname, age(datfrozenxid) as age, currentlimit FROM pgdatabase JOIN (SELECT setting AS currentlimit FROM pgsettings WHERE name = 'autovacuumvacuumscale_factor') AS t1 ORDER BY age DESC; ``` Vacuum the database to prevent transaction ID wraparound. Run the following command: ``` vacuumdb --all --freeze ``` The command `vacuumdb` reclaims storage, optimizes the database for better performance, and prevents transaction ID wraparound. Configure Autovacuum settings for long-term prevention. Adjust `autovacuumvacuumscalefactor`, `autovacuumanalyzescalefactor`, `vacuumcostlimit`, and `maintenanceworkmem` in the PostgreSQL configuration file `postgresql.conf`. Then, restart the PostgreSQL service for the changes to take effect. ``` service postgresql restart ```
Project: Checkmk (Observability and Analysis / Observability)
File: 14859.md

key | value | date | 2024-01-16T14:13:44+00:00 version | 2.3.0b1 class | fix edition | cre component | ec level | 2 compatible | yes The bug was introduced by the werk: in version 2.2.0p18. A workaround would be: make a trivial change to the rules/rule packs (edit description) and activate the changes. Or reload the EC manually after the initial reload to apply the correct config.
Project: HertzBeat (Observability and Analysis / Observability)
File: account-modify.md

id: account-modify title: Modify Account Username Password sidebar_label: Update Account HertzBeat default built-in three user accounts, respectively admin/hertzbeat tom/hertzbeat guest/hertzbeat If you need add, delete or modify account or password, configure `sureness.yml`. Ignore this step without this demand. The configuration file content refer to project repository Modify the following part parameters in sureness.yml[NoteOther default sureness configuration parameters should be retained] ```yaml resourceRole: /api/account/auth/refresh===post===[admin,user,guest] /api/apps/===get===[admin,user,guest] /api/monitor/===get===[admin,user,guest] /api/monitor/===post===[admin,user] /api/monitor/===put===[admin,user] /api/monitor/===delete==[admin] /api/monitors/===get===[admin,user,guest] /api/monitors/===post===[admin,user] /api/monitors/===put===[admin,user] /api/monitors/===delete===[admin] /api/alert/===get===[admin,user,guest] /api/alert/===post===[admin,user] /api/alert/===put===[admin,user] /api/alert/===delete===[admin] /api/alerts/===get===[admin,user,guest] /api/alerts/===post===[admin,user] /api/alerts/===put===[admin,user] /api/alerts/===delete===[admin] /api/notice/===get===[admin,user,guest] /api/notice/===post===[admin,user] /api/notice/===put===[admin,user] /api/notice/===delete===[admin] /api/tag/===get===[admin,user,guest] /api/tag/===post===[admin,user] /api/tag/===put===[admin,user] /api/tag/===delete===[admin] /api/summary/===get===[admin,user,guest] /api/summary/===post===[admin,user] /api/summary/===put===[admin,user] /api/summary/===delete===[admin] excludedResource: /api/account/auth/===* /api/i18n/===get /api/apps/hierarchy===get /===get /dashboard/===get /monitors/===get /alert/===get /account/===get /setting/===get /passport/===get //*.html===get //*.js===get //*.css===get //*.ico===get //*.ttf===get //*.png===get //*.gif===get //*.jpg===get //*.svg===get //*.json===get /swagger-resources/===get /v2/api-docs===get /v3/api-docs===get account: appId: admin credential: hertzbeat role: [admin,user] appId: tom credential: hertzbeat role: [user] appId: guest credential: hertzbeat role: [guest] ``` Modify the following part parameters in sureness.yml [NoteOther default sureness configuration parameters should be retained] ```yaml account: appId: admin credential: hertzbeat role: [admin,user] appId: tom credential: hertzbeat role: [user] appId: guest credential: hertzbeat role: [guest] ``` This secret is the key for account security encryption management and needs to be updated to your custom key string of the same length. Update the `application.yml` file in the `config` directory, modify the `sureness.jwt.secret` parameter to your custom key string of the same length. ```yaml sureness: jwt: secret: 'CyaFv0bwq2Eik0jdrKUtsA6bx3sDJeFV643R LnfKefTjsIfJLBa2YkhEqEGtcHDTNe4CU6+9 8tVt4bisXQ13rbN0oxhUZR73M6EByXIO+SV5 dKhaX0csgOCTlCxq20yhmUea6H6JIpSE2Rwp' ``` Restart HertzBeat, access http://ip:1157/ to explore
Project: Netdata (Observability and Analysis / Observability)
File: COLLECTORS.md

Netdata uses collectors to help you gather metrics from your favorite applications and services and view them in real-time, interactive charts. The following list includes collectors for both external services/applications and internal system metrics. Learn more about , and then learn how to [enable or configure](https://github.com/netdata/netdata/blob/master/src/collectors/REFERENCE.md#enable-and-disable-a-specific-collection-module) any of the below collectors using the same process. Some collectors have both Go and Python versions as we continue our effort to migrate all collectors to Go. In these cases, Netdata always prioritizes the Go version, and we highly recommend you use the Go versions for the best experience. If you want to use a Python version of a collector, you need to explicitly , and enable the Python version. Netdata then skips the Go version and attempts to load the Python version and its accompanying configuration file. If you don't see the app/service you'd like to monitor in this list: If your application has a Prometheus endpoint, Netdata can monitor it! Look at our . If your application is instrumented to expose metrics, see our . If you have data in CSV, JSON, XML or other popular formats, you may be able to use our , Check out our . Use the search bar to look for previous discussions about that collectorwe may be looking for assistance from users such as yourself! If you don't see the collector there, you can make a on GitHub. If you have basic software development skills, you can add your own plugin in or <!-- AUTOGENERATED PART BY integrations/gendoccollector_page.py SCRIPT, DO NOT EDIT MANUALLY -->
Project: Litmus (Observability and Analysis / Chaos Engineering)
File: cnftestsuite.md

CNF Test Suite The is an open source test suite for Cloud Native Network Function (CNF) developers and network operators to evaluate how well a telecom service (a platform or network application, aka CNF) follows cloud native principles and best practices, like resilience. Subjecting the telecom services to chaos testing is useful in finding failure points and suggesting remediation steps toward improving resilience. Therefore, we chose LitmusChaos to create resilience tests in the CNF Test Suite. By including LitmusChaos experiments in the CNF Test Suite's workload tests, we are able to run telecom services in resilience experiments including: pod-network-duplication, pod-network-corruption, pod-io-stress, pod-memory-hog, pod-delete, disk-fill, pod-network-latency, and more. This helps the end user see how their service behaves when exposed to common application failures. The benefits we see in LitmusChaos are: it is part of the CNCF ecosystem, it is designed for Kubernetes workloads, it has a vibrant community and it is well maintained.
Project: HertzBeat (Observability and Analysis / Observability)
File: 2022-07-10-hertzbeat-v1.1.1.md

title: HertzBeat v1.1.1 is Publish author: tom author_title: tom author_url: https://github.com/tomsun28 authorimageurl: https://avatars.githubusercontent.com/u/24788200?s=400&v=4 tags: [opensource] Friendly Cloud Monitoring Tool. | , Agent, . Home: Hi guys! HertzBeat v1.1.1 is coming. This version brings custom monitoring enhancements, and the collected metric data can be assigned as a variable to the next collection. Fixed several bugs and improved the overall stable usability. Only one docker command is needed to install and experience hertzbeat `docker run -d -p 1157:1157 --name hertzbeat apache/hertzbeat` Thanks to the contributors! Feature . Bugfix. contribute by @DevilX5 . contribute by @DevilX5 . contribute by @djzeng contribute by @yangshihui Online https://console.tancloud.cn. Have Fun! is an opensource monitoring and alarm project incubated by and open sourced by , which supports Website, API, PING, Port, Database, OS Monitor etc. We also provide , people no longer need to deploy a cumbersome monitoring tool in order to monitor their website resources. . HertzBeat supports more liberal threshold alarm configuration (calculation expression), supports alarm notification, alarm template, email, DingDing, WeChat FeiShu and WebHook. Most important is HertzBeat supports , just by configuring the YML file, we can customize the monitoring types and metrics what we need. HertzBeat is modular, `manager, collector, scheduler, warehouse, alerter` modules are decoupled for easy understanding and custom development. Welcome to HertzBeat's to try and discover more. Welcome to join us to build hertzbeat together. `HertzBeat`'s multi-type support, easy expansion, low coupling, hope to help developers and micro teams to quickly build their own monitoring tool. If you like HertzBeat, star us on GitHub https://github.com/apache/hertzbeat https://gitee.com/hertzbeat/hertzbeat
Project: Logging Operator (Kube Logging) (Observability and Analysis / Observability)
File: stdout.md

title: StdOut weight: 200 generated_file: true Fluentd Filter plugin to print events to stdout This is the option of stdout format. {{< highlight yaml >}} apiVersion: logging.banzaicloud.io/v1beta1 kind: Flow metadata: name: demo-flow spec: filters: stdout: output_type: json selectors: {} localOutputRefs: demo-output {{</ highlight >}} Fluentd config result: {{< highlight yaml >}} <filter > @type stdout @id test_stdout output_type json </filter> {{</ highlight >}}
Project: Sentry (Observability and Analysis / Observability)
File: README.md

The fonts in this folder have been optimized for web rendering. There are two notable modifications: vertical metrics and file size. Before making any changes to these files, ensure that the metrics are correct and the files are properly minimized. For historical reasons, font files include three different sets of metrics (`win`, `typo`, and `hhea`). These metrics have been modified to standardize rendering across operating systems and browsers. The modified metrics are: `win` ascent: 840 `win` descent: 250 `typo` ascent: 840 `typo` descent: -250 `hhea` ascent: 935 `hhea` descent: -230 These files have been reprocessed using to reduce their size. Note that the default Optimal option will remove certain useful font features and settings. Before processing, select the Expert option, and change the following: Vertical metrics: no adjustment Opentype features: keep all features Subsetting: custom subsetting read more below Subsetting narrows the list of glyphs (characters) included in the exported font files. We split our fonts into files with different glyph sets, each defined by a . This way, we can serve only the files with the glyphs that the user needs. If the page contains only latin characters, then the browser will only download the file with latin glyphs (e.g. `/rubik-regular-latin.woff2`). But if the page also has cyrillic text, then the browser will additionally download the file with cyrillic glyphs (e.g. `/rubik-regular-cyrillic.woff2`). This split reduces the total font loading time, since only the relevant glyph sets are downloaded. We support four glyph sets: `latin`, `latin-ext`, `cyrillic`, and `cyrillic-ext`. The unicode ranges for each of these sets can be found in . In FontSquirrel's Webfont Generator, copy and paste these ranges into Subsetting -> Custom Subsetting -> Unicode Ranges. Once everything has been exported, check that each file contains the correct glyphs using .
Project: SkyWalking (Observability and Analysis / Observability)
File: slow-cache-command.md

Slow Cache command are sensitive for you to identify bottlenecks of a system which relies on cache system. Slow Cache command are based on sampling. Right now, the core samples are the top 50 slowest every 10 minutes. Note that the duration of these command must be slower than the threshold. Here's the format of the settings (in milliseconds): cache-type:thresholdValue,cache-type2:thresholdValue2 The default settings are `default:20,redis:10`. `Reserved Cache type` is default, which is the default threshold for all cache types, unless set explicitly. Note: The threshold should not be set too small, like `1ms`. Although it works in theory, OAP performance issues may arise if your system statement access time is usually more than 1ms. The OAP server would run statistic per service and only persistent the top 50 every 10(controlled by `topNReportPeriod: ${SWCORETOPNREPORTPERIOD:10}`) minutes by default.
Project: Graphite (Observability and Analysis / Observability)
File: README.md

These Graphite-Web unit tests are for the Django portions of the graphite-web code base. They utilize the Django test framework and run via `manage.py test`. For pull-requests, the tests run inside of Travis-ci using Python tox (https://pypi.python.org/pypi/tox) to invoke the tests across all the environments defined in tox.ini. The current tox.ini configuration uses Python coverage (http://coverage.readthedocs.io/en/latest/) to invoke `manage.py` and capture the code coverage levels. Invoke `tox` in the root of the tree and all tests across all environments will be run serially. There are currently 122 environment combinations (`tox -l` lists them all), so running tox without specifying an environment will take a while to run. A set of minimum environments to run tests against are: `py27-django111-pyparsing2` `py35-django111-pyparsing2` `lint` Passing multiple environments to tox can be done by separating with commas: `tox -e py27-django111-pyparsing2,py35-django111-pyparsing2,lint` To run only a specific test suite run (aka. run the file tests/test_finders.py): `tox -e py27-django111-pyparsing2,py35-django111-pyparsing2,lint -- tests.test_finders` To run only a specific class in a test suite run (aka. run the MetricsTester class inside of test/test_metrics.py): `tox -e py27-django111-pyparsing2,py35-django111-pyparsing2,lint -- tests.test_metrics.MetricsTester` To run only a specific test within a test suite's class run: `tox -e py27-django111-pyparsing2,py35-django111-pyparsing2,lint -- tests.testmetrics.MetricsTester.testindex_json` Run `coverage html` from the webapp directory. Afterwards, the webapp/htmlcov/index.html file can be loaded in a browser and the coverage map for the tested code can be evaluated. There may need to be additional system packages or python dependencies installed in order for tox to successfully install the required packages for the tests. Also, there may be system services running locally that are needed for the unit tests to complete successfully. Graphite-Web is licensed under version 2.0 of the Apache License. See the file for details.
Project: Netdata (Observability and Analysis / Observability)
File: lowest_entropy.md

This alert presents the minimum amount of entropy in the kernel entropy pool in the last 5 minutes. Low entropy can lead to a reduction in the quality of random numbers produced by `/dev/random` and `/dev/urandom`. The Netdata Agent checks for the minimum entropy value in the last 5 minutes. The alert gets raised into warning if the value < 100, and cleared if the value > 200. For further information on how our alerts are calculated, please have a look at our . Entropy is similar to "randomness". A Linux system gathers "real" random numbers by keeping an eye on different events: network activity, hard drive rotation speeds, hardware random number generator (if available), key-clicks, and so on. It feeds those to the kernel entropy pool, which is used by `/dev/random`. Encryption and cryptography applications require random numbers to operate. A function or an algorithm that produces numbers -that seem to be random- is very predictable, if you know what function is used. In real life, we use our surroundings and our thoughts to produce truly random numbers. A computer can't really do this by itself, so it gathers numbers from a lot of sources. For example, it can get the CO2 levels in a room from a sensor on the system and use that as a random number. This way all the values are random and there is no pattern to be found among them. The best tool to troubleshoot the lowest entropy alert is with `rng-tools`. If `rng-tools` are not available for your platform, or you run into trouble, you can use the tool `haveged` as an alternative.