Connection Pooling: Managing Database Connections at Scale
Issue #87: System Design Interview Roadmap • Section 4: Scalability
📋 What We'll Master Today
The Hidden Economics - Why connection pools aren't just performance optimizations but fundamental resilience patterns
Pool Exhaustion Anatomy - Understanding the cascading failure progression that catches experienced teams off-guard
Advanced Sizing Strategies - Moving beyond "connections = core_count × 2" to Netflix's bimodal query patterns
Enterprise Case Studies - Real implementations from Netflix, Uber, and Shopify's Black Friday preparation
Production Monitoring - Metrics that separate amateur implementations from battle-tested systems
Hands-On Mastery - Build and experiment with a complete connection pooling system
The e-commerce platform is down during peak shopping hours, and customers can't complete purchases. The culprit? Your application exhausted all database connections, leaving new requests hanging indefinitely. Each failed connection attempt cascades into timeouts, creating a perfect storm of angry customers and lost revenue.
This exact scenario has humbled engineers at Netflix, Uber, and countless startups. The solution isn't just throwing more database connections at the problem—it's understanding how connection pooling transforms your application's relationship with data persistence from a liability into a competitive advantage.
[📍] Connection Pool Architecture diagram here showing the relationship between application threads, connection pool, and database connections.