|simon 592d03f936||1 year ago|
|.github/ISSUE_TEMPLATE||1 year ago|
|tubearchivist-metrics||1 year ago|
|.gitignore||1 year ago|
|CONTRIBUTING.md||1 year ago|
|Dockerfile||1 year ago|
|LICENSE||1 year ago|
|README.md||1 year ago|
|deploy.sh||1 year ago|
Tube Archivist Metrics
Provide Tube Archivist metrics in Prometheus/OpenMetrics format
This is an optional service as part of the Tube Archivist stack.
This is WIP
channel_count = Number of channels playlist_count = Number of playlists download_count = Number of downloads download_queue = Number of pending downloads subtitle_count = Number of subtitles downloaded for videos
ES_URL: The URL to your ElasticSearch server. Defaults to http://archivist-es:9200 ES_USER: The username for authentication to ElasticSearch. Defaults to elastic ES_PASSWORD: The password for authentication to ElasticSearch. No default is set. LISTEN_PORT: The listen port for the metrics server to run on. Defaults to 9934 POLL_INTERVAL: The interval in seconds for the data to be scraped from ElasticSearch. Defaults to 60
Running via Docker Compose (supported)
This metrics service is designed to be ran inside of docker.
To view the main compose file for TubeArchivist, please see the main repository here: TA Repo
To add the metrics service in, place this into your compose file and update the environment variables as required.
archivist-metrics: image: bbilly1/tubearchivist-metrics:latest container_name: archivist-metrics restart: always environment: - "ES_USER=elastic" - "ES_PASSWORD=verysecret" - "ES_URL=http://archivist-es:9200" - "LISTEN_PORT=9934" - "POLL_INTERVAL=60" ports: - 9934:9934
Running via Standalone
Should you want to, you can install and run this without docker.
To do so, clone this repo, install the python libraries with
pip3 install -r requirements.txt
Environment variables can be passed in via normal syntax for your OS.
Prometheus example config
- job_name: 'tubearchivist-metrics' metrics_path: / static_configs: - targets: - <server>:9934
How are metrics gathered?
Typically, a prometheus server will poll the HTTP endpoint of the metrics service to obtain its metrics.
In most scenarios, a service will then retrieve the data for the metric, and then respond to the prometheus http call. However this can be quite harsh on databases and applications, especially when prometheus is polling every 15 seconds.
To prevent performance issues and unncessecary load on ElasticSearch. We prefetch the metric information from ES every 60 seconds (default). The metric is then updated on the HTTP endpoint after we have retrieved the data and cached for prometheus to scrape.
This means prometheus can scrape the endpoint every second if it likes, but no database calls to ES will be made until the polling interval is reached.
If you require more granular polling, you can update the
POLLING_INTERVAL environment variable