postgres-pro

To analyze a slow PostgreSQL query, inspect its EXPLAIN execution plan to identify bottlenecks like sequential scans or inefficient joins. Verify index usage, refresh statistics with ANALYZE, and apply safer index changes to resolve performance bottlenecks in production.

Optimizing JSONB queries in PostgreSQL involves designing efficient query structures and choosing the right index types, such as GIN indexes. You can also leverage PostgreSQL extensions for advanced search and spatial data to improve JSONB workload performance.

Tune VACUUM and autovacuum in PostgreSQL by adjusting configuration parameters to manage bloat and transaction ID wraparound safely. Proper VACUUM tuning prevents maintenance operations from blocking production workloads and maintains operational reliability.

PostgreSQL replication lag occurs due to network latency, long-running transactions, or insufficient streaming and logical replication configuration. Monitor replication lag and overall health by tracking pg_stat views and conducting regular replication health checks.

Yes, you can make online index changes safely in a production PostgreSQL database by creating indexes concurrently. This approach avoids blocking table writes, but requires execution-plan verification and health checks afterward to confirm reliable outcomes.