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

title: botkube migrate Automatically migrates Botkube installation into Botkube Cloud Automatically migrates Botkube installation to Botkube Cloud. This command will create a new Botkube Cloud instance based on your existing Botkube configuration, and upgrade your Botkube installation to use the remote configuration. Supported Botkube bot platforms for migration: Socket Slack Discord Mattermost Limitations: Plugins are sourced from Botkube repository Use label selector to choose which Botkube pod you want to migrate. By default it's set to app=botkube. Examples: $ botkube migrate --label app=botkube --instance-name botkube-slack # Creates new Botkube Cloud instance with name botkube-slack and migrates pod with label app=botkube to it ``` botkube migrate [OPTIONS] [flags] ``` ``` -y, --auto-approve Skips interactive approval for upgrading Botkube installation. --cfg-exporter-image-registry string Registry for the Config Exporter job image (default "ghcr.io") --cfg-exporter-image-repo string Repository for the Config Exporter job image (default "kubeshop/botkube-config-exporter") --cfg-exporter-image-tag string Tag of the Config Exporter job image (default "v9.99.9-dev") --cfg-exporter-poll-period duration Interval used to check if Config Exporter job was finished (default 1s) --cfg-exporter-timeout duration Maximum execution time for the Config Exporter job (default 1m0s) --cloud-api-url string Botkube Cloud API URL (default "https://api.botkube.io/graphql") --cloud-dashboard-url string Botkube Cloud URL (default "https://app.botkube.io") --cloud-env-api-key string API key environment variable name specified under Deployment for cloud installation. (default "CONFIGPROVIDERAPI_KEY") --cloud-env-endpoint string Endpoint environment variable name specified under Deployment for cloud installation. (default "CONFIGPROVIDERENDPOINT") --cloud-env-id string Identifier environment variable name specified under Deployment for cloud installation. (default "CONFIGPROVIDERIDENTIFIER") -h, --help help for migrate --image-tag string Botkube image tag, e.g. "latest" or "v1.7.0" --instance-name string Botkube Cloud Instance name that will be created --kubeconfig string Paths to a kubeconfig. Only required if out-of-cluster. -l, --label string Label used for identifying the Botkube pod (default "app=botkube") -n, --namespace string Namespace of Botkube pod (default "botkube") -q, --skip-connect Skips connecting to Botkube Cloud after migration --skip-open-browser Skips opening web browser after migration --timeout duration Maximum time during which the Botkube installation is being watched, where "0" means "infinite". Valid time units are "ns", "us" (or "s"), "ms", "s", "m", "h". (default 10m0s) --token string Botkube Cloud authentication token -w, --watch --timeout Watches the status of the Botkube installation until it finish or the defined --timeout occurs. (default true) ``` ``` -v, --verbose int/string[=simple] Prints more verbose output. Allowed values: 0 - disable, 1 - simple, 2 - trace (default 0 - disable) ``` - Botkube CLI
Project: Flagsmith (Observability and Analysis / Feature Flagging)
File: 03-OAuth.md

title: OAuth To configure OAuth for Google: Create the Flagsmith on Flagsmith flag as it shows . As a pre-requisite for this configuration make sure to have set up. Configure the following environment variables: `GITHUBCLIENTID` `GITHUBCLIENTSECRET` To configure OAuth for GitHub: For the Authorization callback URL use: `https://<your flagsmith domain name>/oauth/github` Create the Flagsmith on Flagsmith flag as it shows . Now you would be able to see the GitHub SSO option. <div style={{textAlign: 'center'}}><img width="75%" src="/img/FlagsmithGitHubSignUp.png"/></div>
Project: Checkmk (Observability and Analysis / Observability)
File: 16319.md

key | value | compatible | no version | 2.4.0b1 date | 2024-02-27T09:10:58+00:00 level | 1 class | fix component | reporting edition | cee Since 2.2 the content element "Metrics graph of a single service" allowed to configure multiple context/search filters. This was wrong because this element is limited to e specific host and service. This change should have no effect on your configuration but we recommend to check reports with such content elements.
Project: Netdata (Observability and Analysis / Observability)
File: cockroachdb_used_usable_storage_capacity.md

This alert indicates that the usable storage space allocated for your CockroachDB is being highly utilized. If the percentage of used space exceeds 85%, the alert raises a warning, and if it exceeds 95%, the alert becomes critical. High storage utilization can lead to performance issues and potential data loss if not properly managed. Check the current storage utilization To understand the current utilization, you can use SQL commands to query the `crdbinternal.kvstore_status` table. ```sql SELECT nodeid, storeid, capacity, used, available FROM crdbinternal.kvstore_status; ``` This query will provide information about the available and used storage capacity of each node in your CockroachDB cluster. Identify tables and databases with high storage usage Use the following command to list the top databases in terms of storage usage: ```sql SELECT databasename, sum(datasizeint) as totalsize FROM crdb_internal.tables WHERE databasename != 'crdbinternal' GROUP BY database_name ORDER BY total_size DESC LIMIT 10; ``` Additionally, you can list the top tables in terms of storage usage: ```sql SELECT databasename, tablename, data_size FROM crdb_internal.tables WHERE databasename != 'crdbinternal' ORDER BY datasizeint DESC LIMIT 10; ``` Optimize storage usage Based on your findings from steps 1 and 2, consider the following actions: Delete unneeded data from tables with high storage usage. Apply data compression to reduce the overall storage consumption. Archive old data or move it to external storage. Add more storage to the nodes If necessary, increase the storage allocated to your CockroachDB cluster by adding more space to each node. To increase the usable storage capacity, modify the `--store` flag when restarting your CockroachDB nodes. Set the new size by replacing `<YOUR_PATH>` with the actual store path and `<SIZE>` with the desired new size: ``` --store=path=<YOUR_PATH>,size=<SIZE> ``` Add more nodes to the cluster If increasing the storage capacity of your existing nodes isn't enough, consider adding more nodes to your CockroachDB cluster. By adding more nodes, you can distribute storage more evenly and prevent single points of failure due to storage limitations. Refer to the on how to add a new node to a cluster.
Project: Litmus (Observability and Analysis / Chaos Engineering)
File: DOC_SETUP.md

This guide details the steps to set up and generate API documentation for your project using Swagger and GoSwagger. Swagger is used to create an OpenAPI specification file (`swagger.yaml`), and GoSwagger serves this specification file on a local server. . Before beginning, ensure that you have the following installed: Go programming language environment `swaggo/swag` library `goswagger.io` tool First, you need to install `swag`, a tool for generating Swagger 2.0 documents for Go applications. Use the following command to install it: ```bash go get -u github.com/swaggo/swag/cmd/swag ``` For more details, visit the . Next, install GoSwagger, which will serve your Swagger specification file: ```bash go get -u github.com/go-swagger/go-swagger/cmd/swagger ``` For additional information, refer to the . You need to annotate your Go functions to define the API specifications. These annotations are used by Swagger to generate documentation. ```go // DexLogin godoc // // @Description DexRouter creates all the required routes for OAuth purposes. // @Tags DexRouter // @Accept json // @Produce json // @Failure 500 {object} response.ErrServerError // @Success 200 {object} response.Response{} // @Router /dex/login [get] // // DexLogin handles and redirects to DexServer to proceed with OAuth func DexLogin() gin.HandlerFunc { // ... function implementation ... } ``` After adding the annotations run this command to fix and update the annotation formatting ```bash swag fmt . ``` In your handler folder, create or update a file named `doc.go`. Here, define the structures for your responses and errors. ```go package handler // LoginResponse represents the response structure for login. type LoginResponse struct { accessToken string projectID string projectRole string expiresIn string } // ErrServerError represents an error structure for server errors. type ErrServerError struct { Code int `json:"code" example:"500"` Message string `json:"message" example:"Unexpected server error"` } ``` After annotating your API and defining your responses, run the following command in your project root to generate the `swagger.yaml` file: ```bash swag init ``` This command scans your project and creates a Swagger specification from your annotations. Finally, use GoSwagger to serve your Swagger specification file. This allows you to view your API documentation in a web browser. By default the API docs will be generated with Redocly. ```bash swagger serve swagger.yaml ``` To run the orginal swagger format ```bash swagger serve -F=swagger swagger.yaml ``` This command starts a local server hosting your API documentation. With these steps, you should now have a fully functional API documentation setup using Swagger and GoSwagger. Remember to regularly update your annotations and regenerate the Swagger file to keep your documentation in sync with your API.
Project: Grafana Mimir (Observability and Analysis / Observability)
File: v4.5.md

title: "Grafana Mimir Helm chart version 4.5 release notes" menuTitle: "V4.5 release notes" description: "Release notes for Grafana Mimir Helm chart version 4.5" weight: 300 Grafana Labs is excited to announce version 4.5 of the Grafana Mimir Helm chart, which is compatible with Grafana Mimir v2.9 or Grafana Enterprise Metrics (GEM) v2.9. The `mimir-distributed` Helm chart is the best way to install Mimir on Kubernetes. To learn about new features and enhancements in Grafana Mimir or GEM, see the release notes for or . The highlights that follow include the top features, enhancements, and bugfixes in this release. For a comprehensive list of changes, see the . Note: If you are upgrading from a previous major version, review the changelog entry for all the major releases since then and perform the necessary migrations. The `graphite-web` component was removed from the graphite proxy. The `graphite-web` component had several configuration issues which meant it was failing to process requests. The `graphite-web` component was used to render queries that the native query engine cannot, however the majority of graphite functions and features are supported by the native GEM graphite query engine and there is development ongoing to reach feature parity. Cardinality estimation is enabled in the query-frontend via `frontend.queryshardingtargetseriesper_shard` in the Mimir configuration for query sharding by default if `results-cache.enabled` is true. This change improves query performance in case the overhead of query sharding is more than its benefit. Notable enhancements are as follows: The Nginx read timeout (`proxyreadtimeout`) is increased to 300 seconds (increase from default 60 seconds), so that it doesn't interfere with the querier's default 120 seconds timeout (`mimir.structuredConfig.querier.timeout`). Store-gateway: set `GOMEMLIMIT` to the memory request value. This should reduce the likelihood the store-gateway may go out of memory, at the cost of an higher CPU utilization due to more frequent garbage collections when the memory utilization gets closer or above the configured requested memory. Store-gateway: dynamically set `GOMAXPROCS` based on the CPU request. This should reduce the likelihood a high load on the store-gateway will slow down the entire Kubernetes node. Added `global.podLabels` which can add POD labels to PODs directly controlled by this chart (mimir services, nginx). Enabled the `track_sizes` feature for Memcached pods to help determine cache efficiency. Fix Pod Anti-Affinity rule to allow ingesters from the same zone to run on same node, by using `zone` label since the old `app.kubernetes.io/component` did not allow for this.
Project: Grafana Loki (Observability and Analysis / Observability)
File: install-from-source.md

title: Build from source menuTitle: Install from source description: Describes how to install Loki from the source code. aliases: ../../installation/install-from-source/ weight: 700 Clone the Grafana Loki repository and use the provided `Makefile` to build Loki from source. , version 1.14 or later; set your `$GOPATH` environment variable `make` Docker (for updating protobuf and yacc files) Clone Loki to `$GOPATH/src/github.com/grafana/loki`: ```bash git clone https://github.com/grafana/loki $GOPATH/src/github.com/grafana/loki ``` With a current working directory of `$GOPATH/src/github.com/grafana/loki`: ```bash make loki ``` The built executable will be in `$GOPATH/src/github.com/grafana/loki/cmd/loki/loki`.
Project: Grafana Pyroscope (Observability and Analysis / Observability)
File: troubleshooting.md

title: "Troubleshoot eBPF installation" menuTitle: "Troubleshoot" description: "Troubleshoot Grafana eBPF installation." weight: 40 Learn how to troubleshoot and resolve eBPF installation issues. Profiling interpreted languages like Ruby, JavaScript, etc., is not ideal using this implementation. The JIT-compiled methods in these languages are typically not in ELF file format, demanding additional steps for profiling. For instance, using perf-map-agent and enabling frame pointers for Java. Interpreted methods will display the interpreter functions name rather than the actual function. Symbols are extracted from various sources, including: The `.symtab` and `.dynsym` sections in the ELF file. The `.symtab` and `.dynsym` sections in the debug ELF file. The `.gopclntab` section in Go language ELF files. The search for debug files follows . For example, if the profiler wants to find the debug file for `/lib/x86_64-linux-gnu/libc.so.6` with a `.gnu_debuglink` set to `libc.so.6.debug` and a build ID `0123456789abcdef`. The following paths are examined: `/usr/lib/debug/.build-id/01/0123456789abcdef.debug` `/lib/x86_64-linux-gnu/libc.so.6.debug` `/lib/x86_64-linux-gnu/.debug/libc.so.6.debug` `/usr/lib/debug/lib/x86_64-linux-gnu/libc.so.6.debug` Unknown symbols in the profiles youve collected indicate that the profiler couldn't access an ELF file associated with a given address in the trace. This can occur for several reasons: The process has terminated, making the ELF file inaccessible. The ELF file is either corrupted or not recognized as an ELF file. There is no corresponding ELF file entry in `/proc/pid/maps` for the address in the stack trace. If you only see module names (e.g., `/lib/x86_64-linux-gnu/libc.so.6`) without corresponding function names, this indicates that the symbols couldn't be mapped to their respective function names. This can occur for several reasons: The binary has been stripped, leaving no `.symtab`, `.dynsym`, or `.gopclntab` sections in the ELF file. The debug file is missing or could not be located. To fix this for your binaries, ensure that they are either not stripped or that you have separate debug files available. You can achieve this by running: ```bash objcopy --only-keep-debug elf elf.debug strip elf -o elf.stripped objcopy --add-gnu-debuglink=elf.debug elf.stripped elf.debuglink ``` For system libraries, ensure that debug symbols are installed. On Ubuntu, for example, you can install debug symbols for `libc` by executing: ```bash apt install libc6-dbg ``` If your profiles show many shallow stack traces, typically 1-2 frames deep, your binary might have been compiled without frame pointers. To compile your code with frame pointers, include the `-fno-omit-frame-pointer` flag in your compiler options.
Project: OpenCost (Observability and Analysis / Continuous Optimization)
File: ROADMAP.md

The following items are considered the current OpenCost roadmap. 2023 roadmap Improved testing frameworks for backend APIs as well as frontend UI Add conformance tests to confirm implementation meets standards Deeper billing integrations with other cloud providers, e.g. Alibaba Add external cloud asset cost monitoring () More accessible & improved user interface Continued improvement of the More robust and examples. Expose carbon emission ratings Please reach us on in the channel or attend the biweekly from the to discuss OpenCost development.
Project: Netdata (Observability and Analysis / Observability)
File: vsphere_inbound_packets_errors_ratio.md

The `vsphereinboundpacketserrorsratio` alert presents the ratio of inbound packet errors for the network interface of a virtual machine (VM) in VMware vSphere. If the ratio is equal to or greater than 2% and there are at least 10k packets within a 10 minute period, the alert switches to the warning state. Packet errors occur when there's an issue with the packet during transmission. Common reasons include: Transmission errors, where a packet is damaged on its way to its destination. Format errors, where the packet's format doesn't match what the receiving device was expecting. Damaged packets can occur due to bad cables, bad ports, broken fiber cables, dirty fiber connectors, or high radio frequency interference. Identify the affected virtual machine and its corresponding network interface by checking the alert details. Inspect the network hardware by checking for any visible damage or loose connections related to the affected network interface. This may include Ethernet cables, fiber cables, and connectors. Replace or repair any damaged components. Check for radio frequency interference from nearby devices, such as Bluetooth devices or microwaves. If interference is suspected, move or disable the interfering devices, or consider using shielded cables for network connections. Monitor vSphere network performance and error metrics by using VMware vSphere's monitoring tools or other third-party monitoring software, such as Netdata. This can help pinpoint which network devices, interfaces, or protocols are causing packet errors. Verify that network devices and virtual machines are configured correctly to ensure optimal network performance. This may include checking Quality of Service (QoS) settings, VLAN configurations, or network resource allocation. Update VMware vSphere to the latest version, as well as the network drivers and firmware of the physical host, to ensure compatibility and bug fixes are applied. If the issue persists, consider reaching out to VMware support for further assistance.
Project: Jaeger (Observability and Analysis / Observability)
File: README.md

The table below lists Jaeger releases in which new cassandra schema were introduced. | Jaeger Version | Cassandra Schema File | Notes | ||--|| | | `v001.cql.tmpl` | | | | `v002.cql.tmpl` | See for more details on the migration. | | | `v003.cql.tmpl` | See for more details on the migration. | | | `v004.cql.tmpl` | See for more details on the migration. |
Project: Elastic (Observability and Analysis / Observability)
File: st_contains.md

<!-- This is generated by ESQL's AbstractFunctionTestCase. Do no edit it. See ../README.md for how to regenerate it. --> Returns whether the first geometry contains the second geometry. This is the inverse of the <<esql-stwithin,STWITHIN>> function. ``` FROM airportcityboundaries | WHERE STCONTAINS(cityboundary, TO_GEOSHAPE("POLYGON((109.35 18.3, 109.45 18.3, 109.45 18.4, 109.35 18.4, 109.35 18.3))")) | KEEP abbrev, airport, region, city, city_location ```
Project: HertzBeat (Observability and Analysis / Observability)
File: guide.md

id: guide title: Help Center sidebar_label: Help Center Hertzbeat - An open source, real-time monitoring tool with custom-monitor and agentLess. Help documents and auxiliary information during use Regularly collect and monitor the performance Metrics exposed by end-to-end services, provide visual interfaces, and process data for alarm and other service scheduling. Planned monitoring typeapplication service, database, operating system, cloud native, open source middleware. &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> More liberal threshold alarm configuration (calculation expression), supports email, SMS, WebHook, DingDing, WeChat and FeiShu for alarm notification. The positioning of alarm service is to trigger the threshold accurately and timely, and the alarm notification can be reached in time. The triggered alarm information center provides query and filtering of alarm deletion, alarm processing, mark unprocessed, alarm level status, etc. The Metric threshold configuration provides the Metric threshold configuration in the form of expression, which can set the alarm level, trigger times, alarm notification template and whether it is enabled, correlation monitoring and other functions. More details see&emsp;&#x1F449;&emsp; <br /> &emsp;&emsp;&emsp;&#x1F449;&emsp; After triggering the alarm information, in addition to being displayed in the alarm center list, it can also be notified to the designated recipient in a specified way (e-mail, wechat and FeiShu etc.) Alarm notification provides different types of notification methods, such as email recipient, enterprise wechat robot notification, DingDing robot notification, and FeiShu robot notification. After setting the receiver, you need to set the associated alarm notification strategy to configure which alarm information is sent to which receiver. &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br /> &emsp;&#x1F449;&emsp; <br />
Project: HertzBeat (Observability and Analysis / Observability)
File: website.md

id: website title: Monitoring Website sidebar_label: Website Monitor keywords: [open source monitoring tool, open source website monitoring tool, monitoring website metrics] Monitor whether the website is available, response time and other Metrics. | Parameter name | Parameter help description | | -- | -- | | Monitoring Host | Monitored IPV4, IPV6 or domain name. NoteWithout protocol header (eg: https://, http://) | | Monitoring name | Identify the name of this monitoring. The name needs to be unique | | Port | Ports provided by website, http generally defaults to 80 and https generally defaults to 443 | | Relative path | Suffix path of website address except IP port. For example, the relative path of `www.tancloud.cn/console` website is `/console` | | Enable HTTPS | Whether to access the website through HTTPS. NoteWhen HTTPS is enabled, the default corresponding port needs to be changed to 443 | | Collection interval | Interval time of monitor periodic data collection, unit: second, and the minimum interval that can be set is 30 seconds | | Whether to detect | Whether to detect and check the availability of monitoring before adding monitoring. Adding and modifying operations will continue only after the detection is successful | | Description remarks | For more information about identifying and describing this monitoring, users can note information here | | Metric name | Metric unit | Metric help description | | -- | -- | -- | | responseTime | ms | Website response time |