Datadog's Bits Database Optimization automates the full query optimization lifecycle within Database Monitoring (DBM). It scans your database fleet, ranks slow queries by total execution time, generates concrete rewrites or index recommendations, and validates them against a simulated copy of your schema using synthetic data that mirrors production statistics. Only proven improvements are surfaced. Once validated, Bits AI traces the query back to its source code via APM spans, locates the exact file and line, and opens a GitHub pull request with the diff and simulation evidence embedded. After merging, teams can verify real-traffic improvements directly in DBM Query Metrics. No write access to production databases is required, and no customer data leaves your environment.
