Building safety tooling for risk-free AI tuning of Postgres | POSETTE: An Event for Postgres 2026
AI-based Postgres tuning needs built-in safety brakes to prevent dangerous configurations from destabilizing production systems.
“Fast Cars Need Fast Brakes.”
DBtune engineer Mohsin Ejaz argues that AI-driven Postgres tuning, while able to explore complex parameter spaces far faster than human DBAs, carries real risk of selecting dangerous configurations that cause OOM kills or performance degradation in production. The talk frames safety tooling as essential 'brakes' and walks through challenges like memory constraints and exploration cost, tested across RDS, Aurora, Azure, and Kubernetes environments. It matters as a practical engineering perspective on guardrails for autonomous AI acting on critical infrastructure.