Long‑term Storage Options for Prometheus
Introduction
Prometheus is a powerful monitoring system and time series database. While it is efficient for short-term storage, it has limitations for long-term data retention. This lesson covers various options for extending Prometheus' storage capabilities.
Long‑term Storage Options
1. Remote Write
Prometheus can send samples to a remote storage system using the remote_write
configuration. This allows for integration with various backends such as InfluxDB, TimescaleDB, and others.
remote_write:
- url: "http://example.com/api/v1/write"
2. Thanos
Thanos is a project that extends Prometheus with long-term storage capabilities. It enables you to store metrics in object storage like S3, GCS, or Azure Blob Storage.
thanos store --objstore.config-file=./objstore.yml
3. Cortex
Cortex is another option that allows you to horizontally scale Prometheus and provides a long-term storage solution. It supports various storage backends including S3, GCS, and DynamoDB.
4. Migrate to a Dedicated Database
For organizations needing extensive metrics retention, consider migrating to a dedicated time-series database like InfluxDB or TimescaleDB.
influx -import -path=path/to/metrics.csv -precision=s
5. Prometheus Operator
Using the Prometheus Operator allows for easier management of Prometheus instances and can facilitate long-term storage setups.
Best Practices
- Evaluate storage requirements based on data retention needs.
- Choose a solution that aligns with your infrastructure and scalability needs.
- Regularly review and optimize your configuration for performance.
- Consider using compression to save storage space.
- Implement monitoring on your long-term storage solution to detect issues early.
FAQ
What is the maximum retention period for Prometheus?
The default retention period is 15 days, but it can be configured using the --storage.tsdb.retention.time
flag.
Can I use multiple long-term storage options simultaneously?
Yes, you can configure Prometheus to use multiple remote write endpoints, but consider the implications on performance and data consistency.