How to tame the thundering herd problem

The thundering herd problem arises when multiple clients or processes simultaneously request the same resource, overwhelming backend systems and causing performance degradation, particularly in web applications and distributed systems. This issue often occurs due to scenarios like cache expiration, high traffic spikes, or database lock contention, leading to increased latency, infrastructure costs, and user experience problems. Solutions involve smart caching strategies such as introducing jitter to cache expiration times, request coalescing, rate limiting, and load shedding. Redis is highlighted as a powerful tool to mitigate this problem through features like in-memory caching, Bloom filters, and distributed locks, although improper configuration can exacerbate the issue. The text contrasts Redis with other services like Amazon ElastiCache and Google Memorystore, emphasizing Redis’s advanced capabilities and cost-efficiency for handling large-scale concurrency challenges.