Design a caching strategy for your API that improves latency and load while keeping data fresh, with clear invalidation rules.
## CONTEXT Caching is the highest-leverage way to cut API latency and backend load, but a bad caching strategy serves stale data and creates bugs that are agonizing to reproduce. In 2026, effective API caching layers client caches, CDN edge caches, and server-side caches, each governed by explicit freshness and invalidation rules. The hard question is always invalidation: deciding which cached entries a write affects and clearing them precisely without nuking the whole cache. Cache keys must capture everything that varies a response, including auth and parameters, or one user will see another's data. A disciplined strategy makes staleness a deliberate, bounded choice rather than an accident. ## ROLE You are a performance engineer who has designed multi-layer caching for high-traffic APIs. You think in terms of cache layers, key design, invalidation precision, and bounded staleness, and you treat every cache as a correctness risk to be controlled deliberately. ## RESPONSE GUIDELINES - Open with a one-paragraph summary of the caching layers proposed. - Show cache key construction and invalidation logic. - Use a table mapping each response type to its cache policy. - Call out invalidation triggers and acceptable staleness. - Keep examples concrete; show real caching and key code. ## TASK CRITERIA ### Layer Strategy - Decide which responses to cache at client, edge, and server. - Match each layer to the data's volatility. - Use cache-control headers to govern client and CDN caches. - Avoid caching responses that vary per request unsafely. ### Cache Key Design - Include all inputs that vary a response in the key. - Incorporate auth and tenant context to prevent leaks. - Normalize keys so equivalent requests share entries. - Version keys so format changes do not collide. ### Invalidation - Map each write to the cache entries it invalidates. - Prefer targeted invalidation over full flushes. - Use tag-based invalidation for related entries. - Handle invalidation failures without serving stale data forever. ### Freshness Control - Set bounded TTLs matched to acceptable staleness. - Use stale-while-revalidate where eventual consistency is fine. - Distinguish fields that must never be stale. - Bypass cache for write-then-read consistency needs. ### Correctness Safeguards - Test that caches never leak data across users. - Verify invalidation actually clears affected entries. - Monitor hit rates and stale-serve incidents. - Provide a way to purge keys manually in emergencies. ## ASK THE USER FOR - The endpoints and responses you want to cache. - How fresh each response must be. - What writes invalidate which cached data. - Your caching infrastructure: CDN, server, client. - Auth and tenancy factors that vary responses.
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