Connection pooling strategies in Amazon Aurora DSQL

This article presents four connection pooling strategies for Amazon Aurora DSQL to reduce overhead, stay within rate limits, and avoid reconnection storms.

• Use official AWS connectors (HikariCP, psycopg, node-postgres, pgxpool) that handle IAM token lifecycle automatically
• Configure maximum connection lifetime with jitter to spread recycling over time and prevent thundering herd reconnections
• Size pools conservatively (10-20 connections per instance) and monitor DPU consumption to balance throughput and latency
• For Lambda, instantiate pools at module scope outside handlers to persist across warm invocations
• In multi-Region deployments, create separate pools per Region since cross-Region latency occurs only at commit time
• Instrument client-side metrics like pool acquire latency, active connections, and exhaustion events to detect bottlenecks
• Avoid database-side proxies like PgBouncer since Aurora DSQL handles transaction-level multiplexing natively

Following these strategies enables applications to leverage Aurora DSQL's automatic scaling and high availability while maintaining minimal connection overhead and predictable latency.