Understand memory management in Amazon RDS for PostgreSQL to avoid out of memory

This article explains how to manage memory in Amazon RDS and Aurora PostgreSQL to prevent out-of-memory (OOM) issues, covering memory allocation, diagnostic tools, and tuning strategies.

• PostgreSQL allocates memory across shared buffers (page cache), local per-backend memory (work_mem, maintenance_work_mem), and OS file system cache
• Identify memory-intensive queries using CloudWatch Database Insights, temp file logging, and memory context inspection functions
• Use EXPLAIN (ANALYZE, BUFFERS) to detect query spilling to disk and estimate memory consumption from plan node counts
• Aurora PostgreSQL includes rds.enable_memory_management (default: on) to cancel transactions before OOM killer terminates processes
• Set work_mem at session/transaction level rather than globally; use connection pooling to stabilize backend memory consumption
• Monitor FreeableMemory and SwapUsage with CloudWatch alarms; investigate when combined with rising swap or performance degradation

Effective memory management prevents database restarts and maintains stability by proactively identifying memory-intensive queries and tuning parameters appropriately.