Pattern Selection
Cache-Aside: Application checks cache first, queries DB on miss and backfills cache. The most common and flexible pattern. Read-Through: Cache layer automatically loads from the data source; applications only interact with the cache. Write-Behind: Writes update cache first, asynchronously batch-writing to the database — ideal for write-heavy scenarios.
Consistency Challenges
Cache-database consistency is the core challenge. The recommended strategy is "update database first, then delete cache" with message queue retry for failed deletions. Avoid "delete cache first, then update database" — it causes dirty data under concurrency.
Penetration/Avalanche/Breakdown
Penetration: Bloom filter + null value caching. Avalanche: Random TTL + multi-level caching. Breakdown: Mutex lock (SETNX) or logical expiration.
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