How to optimize Prometheus storage and performance?

Prometheus storage optimization and performance tuning strategies:

Data Retention Policy:

yaml
storage:
  tsdb:
    retention.time: 15d
    retention.size: 10GB

• Set retention time based on disk space and query requirements
• Use retention.size to limit disk usage

Scraping Optimization:

• Set reasonable scrape_interval (recommended 15s-60s)
• Use scrape_timeout to avoid slow queries
• Set longer scrape intervals for less important metrics
• Use metric_relabel_configs to filter unnecessary metrics

Query Optimization:

• Avoid full queries, use label filtering
• Choose appropriate time window sizes
• Use Recording Rules to pre-calculate common queries
• Spread query times to avoid peak periods

Memory Optimization:

• Adjust --storage.tsdb.retention.time
• Use --storage.tsdb.head-chunks.write-queue-size to control write queue
• Monitor memory usage, clean old data promptly
• Consider using Thanos or VictoriaMetrics for long-term storage

Recording Rules Example:

yaml
groups:
  - name: api_rules
    rules:
      - record: job:http_requests:rate5m
        expr: sum by (job) (rate(http_requests_total[5m]))

Monitoring Prometheus Itself:

• prometheus_tsdb_compaction_duration
• prometheus_tsdb_head_samples_appended_total
• prometheus_target_interval_length_seconds

Best Practices:

• Regularly clean up unnecessary metrics
• Use federation architecture to distribute load
• Consider using remote write to separate hot and cold data