Redis High-Frequency Interview Questions: What's the Difference Between Cache Penetration, Avalanche, and Breakdown?

These three terms are almost guaranteed to come up in interviews, and many people can't tell them apart.

Cache Penetration

Phenomenon: The queried data doesn't exist in the database either, so naturally there's no cache. Every request hits the database directly.

Solutions: 1. Bloom filter: Pre-store all potentially queried keys in a Bloom filter, and directly filter out non-existent ones 2. Cache empty objects: Even if nothing is found, cache a null value with a short expiration time

Cache Breakdown

Phenomenon: A hot key expires, and a large number of concurrent requests hit the database at the same time.

Solutions: 1. Mutex lock: The first request queries the database and updates the cache, while other requests wait 2. Never expire: Don't set an expiration time for hot data, update it asynchronously instead

Cache Avalanche

Phenomenon: A large number of keys expire simultaneously, and all requests hit the database.

Solutions: 1. Add random values to expiration times: Avoid large batches expiring at the same time 2. Multi-level caching: Local cache + Redis + database 3. Rate limiting and degradation: Implement service degradation when the database can't handle the load

How to Remember

• Penetration: Data doesn't exist at all → Bloom filter
• Breakdown: Hot key expires → Mutex lock
• Avalanche: Large number of keys expire simultaneously → Random expiration times

Remember the differences between these three scenarios and their solutions, and you'll be halfway to acing the Redis part of your interview.