Production PostgreSQL
PostgreSQL Guide for Monitoring, Performance, and Operations
PostgreSQL is reliable when operations are disciplined: good monitoring coverage, query-level visibility, controlled index rollout, and evidence-driven tuning. This page is the central entry point for MonPG's PostgreSQL knowledge hub.
PostgreSQL Monitoring
Build visibility around query behavior, lock pressure, vacuum, replication lag, and WAL growth before incidents escalate.
Query and Planner Behavior
Understand estimate drift, plan instability, and planner choices that create sudden latency regressions.
Slow Query Triage
Rank queries by total impact, investigate regressions, and validate remediation steps safely.
Sizing and Capacity
Model CPU, memory, storage, and connection pressure against real traffic and workload shape.
PostgreSQL operating model
Observe
Collect query, lock, vacuum, and replication signals continuously.
Diagnose
Correlate query fingerprints, planner evidence, and index state before changing production.
Change safely
Roll out indexes and tuning changes with explicit risk criteria and rollback gates.
PostgreSQL topic hubs
PostgreSQL diagnostic tools
pgvector HNSW Index Tuner
Benchmark 48 HNSW configurations against your real pgvector data in 10 minutes. Get the optimal m, ef_construction, and ef_search plus zero-downtime migration SQL.
PostgreSQL Plan Autopsy
Paste EXPLAIN ANALYZE output and get an incident-style read of the plan: planner estimate drift, loop explosions, disk spills, buffer pressure, and the evidence SQL to prove the fix.
PostgreSQL Index Rollout Simulator
Model a proposed PostgreSQL index as a production rollout: DDL shape, lock level, WAL pressure, write amplification, replica lag risk, validation SQL, and rollback criteria.
Tool comparisons
Use these pages when choosing between PostgreSQL monitoring approaches. They focus on decision quality in production workflows.