Preventing Redis Cache Avalanche: Interview Dialogue and Practical Solutions

Interview scenario: The interviewer asks the candidate about the Redis cache avalanche problem that can occur when many hot keys expire simultaneously, causing a sudden surge of database requests that may overload the system.

Definition: The phenomenon where massive, simultaneous cache expirations or temporary cache unavailability forces all requests to hit the database, leading to high CPU, memory load, and possible crashes, is called a "cache avalanche".

Solutions (four dimensions):

Cache pre‑warming : Before deployment, proactively access likely hot data so it is loaded into Redis, and manually trigger loading of different keys ahead of anticipated traffic spikes.

Mutex lock : Apply a mutual‑exclusion lock on the first request that misses the cache; other threads wait, and once the data is fetched and cached, subsequent requests read from the cache.

Staggered expiration times : Add a random factor to each key’s TTL so that expirations are distributed over time, avoiding a concentration of cache misses.

High‑availability cache architecture : Design Redis as a highly available service (e.g., using Redis Sentinel or Redis Cluster) so that node, machine, or even data‑center failures do not interrupt cache service.

The interviewer concludes by asking if the audience has learned how to handle cache avalanche, hoping they won’t be tripped up by this question in future interviews.