PostgreSQL Performance Tune provides a guided review for PostgreSQL performance problems, connecting activity, queries, waits, indexes, memory, and I/O evidence.
PostgreSQL performance tuning works best as an evidence-led process. Start with the symptom: slow application requests, high CPU, storage latency, lock waits, connection saturation, or memory pressure. Then use the Performance Tune page to connect that symptom to supporting evidence from activity, queries, waits, indexes, memory, and I/O.
Avoid changing multiple settings at once unless the system is in an emergency and the risk is understood. PostgreSQL settings such as memory allocation, parallelism, autovacuum behavior, logging, and checkpoint tuning can interact with each other. A query or index change may solve a performance problem more safely than a broad server-level change.
For production systems, record the baseline before tuning. Capture the time window, main waits, expensive queries, affected databases, and user impact. After the change, compare the same evidence rather than relying only on a general impression that the system feels faster.
Tune the thing that matches the evidence. If one query dominates, start with the query and indexes. If many workloads wait on storage, investigate I/O. If sessions are blocked, start with locking and transaction design.
Mini DBA is designed to show evidence and recommendations. Apply database changes through your normal controlled change process.
Compare before-and-after metrics for duration, waits, execution count, I/O, CPU, and user impact over a similar workload period.