Resolve Amazon Aurora PostgreSQL lock contention with Database Insights: Part 2

This article demonstrates how to use CloudWatch Database Insights to identify and resolve Amazon Aurora PostgreSQL lock contention through monitoring, immediate fixes, configuration changes, and architectural patterns.

• CloudWatch Database Insights Lock Analysis provides visibility into blocking relationships via Lock Tree visualization and multi-dimensional analysis
• Immediate fixes include pg_cancel_backend() and pg_terminate_backend() to stop blocking sessions
• Timeout parameters (idle_in_transaction_session_timeout, statement_timeout, lock_timeout) automate protection against lock contention
• Query optimization and asynchronous processing reduce lock duration and contention probability
• Row splitting pattern distributes updates across multiple stripe rows, increasing concurrent throughput from 4,900 to 21,000+ TPS
• Optimistic concurrency control with NOWAIT and SKIP LOCKED enables graceful retry logic without long lock waits
• Combining read scalability, minimal lock duration, and striping provides comprehensive contention resolution

Lock contention is fundamentally a workload and schema design challenge requiring targeted application changes rather than additional compute capacity.