Cache-Aside Pattern With Redis: How It Works and Where It Can Fail

Cache-aside, also known as lazy loading, is one of the most widely used caching patterns, where the application checks Redis first and only queries the database on a cache miss before storing the result with a TTL. On writes, the standard approach is to update the database and then delete the cache key, letting the next read repopulate it with fresh data. The pattern is resilient by design — if Redis goes down, requests fall through to the database, keeping the application functional albeit slower. However, cache-aside carries two known risks: a stale-cache race condition where an outdated value can be written after a newer update, and a thundering herd problem where many requests simultaneously hit the database when a popular key expires. Common mitigations include setting sensible TTLs, adding jitter to expiry times, and using locks to ensure only one request rebuilds a cache entry at a time.