From noise to signal: Monitoring Amazon DocumentDB like a pro

This article provides best practices for monitoring Amazon DocumentDB using a tiered alerting strategy, slow query diagnosis framework, and garbage collection health monitoring.

• Organize metrics into three response tiers: Critical (minutes to impact), Warning (hours to impact), and Advisory (weekly review)
• Critical metrics include CPUUtilization, FreeableMemory, BufferCacheHitRatio, ReadLatency, WriteLatency, DiskQueueDepth, and connection limits
• Use three-lens diagnosis for slow queries: profiler/explain plans, Performance Insights wait events, and CloudWatch infrastructure metrics
• Monitor garbage collection health via AvailableMVCCIds, LongestActiveGCRuntime, and collection-level MVCCIdScale to prevent MVCC exhaustion
• Implement preventive actions like transaction timeouts, session idle timeouts, and bulk operation scheduling to reduce GC strain

Effective monitoring reduces alert noise by alerting on predictive signals rather than all metrics equally, enabling faster root cause diagnosis through structured investigation workflows.