Cache avalanche occurs when a large number of cache entries expire simultaneously, overwhelming the database. This article explores a multi-level caching architecture that pairs Caffeine, an in-process Java cache, with Redis, a distributed cache, to mitigate this risk. The local cache handles hot data with low latency, while Redis provides a shared, persistent layer. Key considerations include cache size tuning, eviction policies, and consistency between levels. This pattern is especially valuable for read-heavy, high-availability services. Engineers should evaluate trade-offs like memory overhead and data staleness. The approach is production-proven and can be adapted to other local caches like Guava or Ehcache.
Learn how combining Caffeine and Redis in a multi-level cache can protect your system from cache avalanche, a common high-concurrency failure.