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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.