Stabilizing Peak Load on a High-Traffic News Platform

Challenge

The platform was hitting database connection pool exhaustion once concurrent traffic reached 6,000 to 8,000 users at peak — a level of load where every new feature carried real risk of taking the whole platform down. The root cause traced back to N+1 query patterns compounding under load, alongside external integrations that could exhaust their own rate limits and cascade into further slowdowns.

Approach

• Eliminated the N+1 query patterns through optimized joins and indexing, addressing the root cause rather than just adding more hardware.
• Built a custom Redis caching layer (via RedisTemplate) to absorb repeat load away from the database.
• Introduced a hook-based integration pattern so third-party rate limits couldn't cascade into platform-wide slowdowns.
• Designed a reflection-based audit-logging library that automatically tracks entity state changes across every class in the system, with no added boilerplate per class.

Result

API latency dropped by roughly 50%, and the platform held steady through peak load instead of degrading. The audit-logging library also meant every entity in the system gained a change history automatically, without engineers needing to instrument each one by hand.