Metadata-Version: 2.1
Name: frigga
Version: 1.0.7
Summary: Scrape only relevant metrics in Prometheus, according to your Grafana dashboards
Home-page: https://github.com/unfor19/frigga
Author: Meir Gabay
Author-email: unfor19@gmail.com
License: MIT
Download-URL: https://github.com/unfor19/frigga/archive/v1.0.7.tar.gz
Description: # frigga
        
        [![testing](https://github.com/unfor19/frigga/workflows/testing/badge.svg?branch=master)](https://github.com/unfor19/frigga/actions?query=workflow%3Atesting)
        
        <div style="text-align: center;">
        <img alt="frigga-logo" width="100%" src="https://frigga.s3-eu-west-1.amazonaws.com/frigga_transparent_background_github_readme.png" />
        </div>
        
        Do you have a Grafana instance? frigga makes sure you don’t scrape metrics in Prometheus, which you don’t present in Grafana dashboards.
        
        Scrape only relevant metrics in Prometheus, according to your Grafana dashboards, see the [before and after snapshot](https://snapshot.raintank.io/dashboard/snapshot/p4YmuKHu4jBlA2kPmOhbuda3jo4I51bt?orgId=2). frigga generates `keep` filters on [metric_relabel_configs](https://prometheus.io/docs/prometheus/latest/configuration/configuration/#metric_relabel_configs), and adds them to your `prometheus.yml` file
        
        frigga is extremely useful for [Grafana Cloud](https://grafana.com/products/cloud/) customers since the pricing is per DataSeries ingestions.
        
        ## Illustration
        <details>
        <summary>Expand/Collapse</summary>
           
        <div style="text-align: center;">
        <img alt="frigga-logo" width="100%" src="https://frigga.s3-eu-west-1.amazonaws.com/firrga-demo-light.gif" />
        </div>
        
        </details>
        
        ## Requirements
        
        Python 3.6.7+
        
        ## Installation
        
        ```bash
        $ pip install frigga
        ```
        
        ## Getting Started
        
        1. Grafana - Import the dashboard [frigga - Jobs Usage](docker-compose/grafana/provisioning/dashboards/jobs-usage.json) (ID: 12537) to Grafana, and check out the number of DataSeries
        1. Grafana - Generate an API Key for `Viewer`
        1. frigga - Get the list of metrics that are used in your Grafana dasboards
        
           ```bash
           $ frigga gl
           
           # gl is grafana-list, or good luck :)
        
           Grafana url [http://localhost:3000]: http://my-grafana.grafana.net
           Grafana api key: (hidden)
           >> [LOG] Getting the list of words to ignore when scraping from Grafana
           ...
           >> [LOG] Found a total of 269 unique metrics to keep
           ```
        
           `.metrics.json` - automatically generated in pwd
        
           ```json
           {
               "all_metrics": [
                   "cadvisor_version_info",
                   "container_cpu_usage_seconds_total",
                   "container_last_seen",
                   "container_memory_max_usage_bytes",
                   ...
               ]
           }
           ```
        
        1. Add the following snippet to the bottom of your `prometheus.yml` file. Check the example in [docker-compose/prometheus-original.yml](docker-compose/prometheus-original.yml)
        
           ```yml
            ---
            name: frigga
            exclude_jobs: []
           ```
        
        1. frigga - Use the `.metrics.json` file to apply the rules to your existing `prometheus.yml`
        
           ```bash
           $ frigga pa
           
           # pa is prometheus-apply, or pam-tada-dam
        
           Prom yaml path [docker-compose/prometheus.yml]: /etc/prometheus/prometheus.yml
           Metrics json path [./.metrics.json]: /home/willywonka/.metrics.json
           >> [LOG] Reading documents from docker-compose/prometheus.yml
           ...
           >> [LOG] Done! Now reload docker-compose/prometheus.yml with 'docker exec $PROM_CONTAINER_NAME kill -HUP 1'
           ```
        
        1. As mentioned in the previous step, reload the `prometheus.yml` to Prometheus, here are two ways of doing it
           - "Kill" Prometheus
             ```bash
             $ docker exec $PROM_CONTAINER_NAME kill -HUP 1
             ```
           - Send a POST request to `/-/reload` - this requires Prometheus to be loaded with `--web.enable-lifecycle`, for example, see [docker-compose.yml](docker-compose/docker-compose.yml)
             ```bash
             $ curl -X POST http://localhost:9090/-/reload
             ```
        1. Make sure the `prometheus.yml` was loaded successfully to Prometheus
        
           ```bash
           $ docker logs --tail 10 $PROM_CONTAINER_NAME
        
            level=info ts=2020-06-27T15:45:34.514Z caller=main.go:799 msg="Loading configuration file" filename=/etc/prometheus/prometheus.yml
            level=info ts=2020-06-27T15:45:34.686Z caller=main.go:827 msg="Completed loading of configuration file" filename=/etc/prometheus/prometheus.yml
           ```
        
        1. Grafana - Now check `frigga - Jobs Usage` dashboard, the numbers should be signifcantly lower (up to 60% or even more)
        
        ## Test it locally
        
        ### Requirements
        
        1. [Docker](https://docs.docker.com/get-docker/)
        1. [docker-compose](https://docs.docker.com/compose/install/)
        1. [jq](https://stedolan.github.io/jq/download/)
        
        ### Getting Started
        
        1. git clone this repository
        1. Deploy locally the services: Prometheus, Grafana, node-exporter and cadvisor
        
           ```bash
           $ bash docker-compose/deploy_stack.sh
        
           Creating network frigga_net1
           ...
           >> Grafana - Generating API Key - for Viewer
           eyJrIjoiT29hNGxGZjAwT2hZcU1BSmpPRXhndXVwUUE4ZVNFcGQiLCJuIjoibG9jYWwiLCJpZCI6MX0=
           # Save this key ^^^
           ```
        
        1. Open your browser, navigate to http://localhost:3000
        
           - Username and password are admin:admin
           - You'll be prompted to update your password, so just keep using `admin` or hit Skip
        
        1. Go to [Jobs Usage](http://localhost:3000/d/U9Se3uZMz/jobs-usage?orgId=1) dashboard, you'll see that Prometheus is processing ~2800 DataSeries
        1. Get all the metrics that are used in your Grafana dasboards
        
           ```bash
           $ frigga gl -gurl http://localhost:3000 -gkey $GRAFANA_API_KEY
        
           >> [LOG] Getting the list of words to ignore when scraping from Grafana
           ...
           >> [LOG] Found a total of 269 unique metrics to keep
           # Generated .metrics.json in pwd
           ```
        
        1. Apply the rules to `prometheus.yml`, keep the defaults
        
           ```bash
           $ frigga pa
           
           # prometheus-apply
        
           Prom yaml path [docker-compose/prometheus.yml]:
           Metrics json path [./.metrics.json]:
           ...
           >> [LOG] Done! Now reload docker-compose/prometheus.yml with 'docker exec $PROM_CONTAINER_NAME kill -HUP 1'
           ```
        
        1. Reload `prometheus.yml` to Prometheus
        
           ```bash
           $ bash docker-compose/reload_prom_config.sh show
        
           >> Reloading prometheus.yml configuration file
           ...
           level=info ts=2020-06-27T16:25:17.656Z caller=main.go:827 msg="Completed loading of configuration file" filename=/etc/prometheus/prometheus.yml
           ```
        
        1. Go to [Jobs Usage](http://localhost:3000/d/U9Se3uZMz/jobs-usage?orgId=1), you'll see that Prometheus is processing only ~1000 DataSeries (previously ~2800)
           - In case you don't see the change, don't forget to hit the refersh button
        1. Cleanup
           ```bash
           $ docker-compose -p frigga --file docker-compose/docker-compose.yml down
           ```
        
        ## Pros and Cons of this tool
        
        ### Pros
        
        1. [Grafana-Cloud](https://grafana.com/products/cloud/) - As a Grafana Cloud customer, the main reason for writing this tool was lowering the costs. This goal was achieved by sending only the relevant DataSeries to Grafana Cloud
        1. Saves disk-space on the machine running Prometheus
        1. Improves PromQL performance by querying less metrics; significant only when processing high volumes
        
        ### Cons
        
        1. After applying the rules in `prometheus.yml`, it makes the file less readable. Due to the fact it's not a file that you play with on a daily basis, it's okayish
        1. The memory usage of Prometheus increases slightly, around ~30MB, not significant, but worth mentioning
        1. If you intend to use more metrics, for example, you've added a new dashboard which uses more metrics, you'll need to do the same process again; `frigga gl` and `frigga pa`
        
        ## References
        - [metric_relabel_configs](https://prometheus.io/docs/prometheus/latest/configuration/configuration/#metric_relabel_configs)
        - [Or in relabelling](https://www.robustperception.io/or-in-relabelling)
        - [relabel_configs vs metrics_relabel_configs](https://www.robustperception.io/relabel_configs-vs-metric_relabel_configs)
        
        
        ## Contributing
        
        Report issues/questions/feature requests on the [Issues](https://github.com/unfor19/frigga/issues) section.
        
        Pull requests are welcome! Ideally, create a feature branch and issue for every single change you make. These are the steps:
        
        1. Fork this repo
        1. Create your feature branch from master (`git checkout -b my-new-feature`)
        1. Install from source
           ```bash
            $ git clone https://github.com/${GITHUB_OWNER}/frigga.git && cd frigga
            ...
            $ pip install --upgrade pip
            ...
            $ python -m venv ./ENV
            $ . ./ENV/bin/activate
            ...
            $ (ENV) pip install --editable .
            ...
            # Done! Now when you run 'frigga' it will get automatically updated when you modify the code
           ```
        1. Add the code of your new feature
        1. Test - make sure `frigga grafana-list` and `frigga prometheus-apply` commands work
        1. Commit your remarkable changes (`git commit -am 'Added new feature'`)
        1. Push to the branch (`git push --set-up-stream origin my-new-feature`)
        1. Create a new Pull Request and tell us about your changes
        
        ## Authors
        
        Created and maintained by [Meir Gabay](https://github.com/unfor19)
        
        ## License
        
        This project is licensed under the MIT License - see the [LICENSE](https://github.com/unfor19/frigga/blob/master/LICENSE) file for details
        
Keywords: prometheus grafana dashboard metrics monitor cloud
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
