https://hub.docker.com/r/otopy/promscale
Promscale is an open-source long-term store for Prometheus data designed for analytics. It is a horizontally scalable, highly-compressed, and operationally mature platform for Prometheus data that offers the combined power of PromQL and SQL, enabling developers to ask any question, create any dashboard, and achieve greater visibility into their systems. Promscale is built on top of TimescaleDB, the leading relational database for time-series.
By allowing a user to use SQL, in addition to PromQL, this platform empowers the user to ask complex analytical queries from their metrics data, and thus extract more meaningful insights.
✅ Promscale is currently the only long-term store for Prometheus data to have received a 100% compliance test score (with no cross-cutting concerns) from PromLab's PromQL Compliance Test Suite.
For a detailed description of this architecture, please see [our design doc][design-doc].
If you have any questions, please join the #promscale channel on TimescaleDB Slack, or the Promscale Users Google Group.
You can limit the metrics being sent to the adapter (and thus being
stored in your long-term storage) by setting up write_relabel_configs
in Prometheus, via the prometheus.yml file.
Doing this can reduce the amount of space used by your database and thus
increase query performance.
The example below drops all metrics starting with the prefix go_,
which matches Golang process information exposed by exporters like
node_exporter:
remote_write:
- url: "http://promscale_connector:9201/write"
write_relabel_configs:
- source_labels: [__name__]
regex: 'go_.*'
action: drop
Content type
Image
Digest
Size
64.8 MB
Last updated
almost 6 years ago
docker pull otopy/promscale