# Cache-Aside ## Intent Let the application load data into a cache on misses and invalidate or refresh it after changes. ## Problem and forces Repeated reads need lower latency or backend load at acceptable staleness. ## Applicability Use after measurement for read-heavy data with clear keys, expiry, and consistency tolerance. ## When not to use Avoid highly sensitive, rapidly changing, low-reuse, or strongly consistent data without safeguards. ## Benefits Improves read latency and reduces backend load with incremental adoption. ## Liabilities Adds invalidation, stale reads, stampedes, memory cost, and sensitive-data exposure. ## Implementation considerations Define TTL, invalidation, negative caching, stampede control, key isolation, encryption, and metrics. ## Credible alternatives Database tuning, materialized view, CDN, request coalescing, or no cache. ## Related patterns Proxy, Flyweight. ## Architecture interview questions What measured bottleneck exists, how stale may data be, and may the data legally be cached?