Managing API Cache
Overview
Implement intelligent API response caching using Redis, Memcached, or in-memory stores with cache key generation, TTL management, cache invalidation strategies, and HTTP cache headers. Support read-through, write-through, and cache-aside patterns with tag-based invalidation for related resources and stale-while-revalidate behavior.
Prerequisites
- Redis 6+ or Memcached for distributed caching (required for multi-instance deployments)
- Cache client library:
ioredis(Node.js),redis-py(Python), or Lettuce (Java) - CDN with cache control support for edge caching (CloudFront, Cloudflare, Fastly) -- optional
- Monitoring for cache hit/miss ratios and eviction rates
- Understanding of data freshness requirements per endpoint
Instructions
- Analyze endpoint characteristics using Read and Grep to classify endpoints by cacheability: fully cacheable (static data), conditionally cacheable (user-specific data), and never cacheable (mutations, real-time data).
- Implement cache key generation middleware that creates deterministic keys from method, path, query parameters (sorted), and relevant headers (Accept, Authorization hash for user-specific caches).
- Build a cache-aside middleware that checks the cache before executing the handler, returning cached responses with
X-Cache: HITheader, or executing the handler, caching the result, and returning withX-Cache: MISS. - Configure TTL per endpoint category: long TTL (1 hour) for reference data, medium TTL (5 minutes) for frequently changing lists, short TTL (30 seconds) for near-real-time data.
- Implement cache invalidation on mutations: when a POST/PUT/DELETE modifies a resource, invalidate all cached responses containing that resource using tag-based invalidation.
- Add
Cache-Control,ETag, andLast-Modifiedresponse headers for HTTP-level caching, enabling CDN and browser cache participation. - Implement stale-while-revalidate behavior: serve stale cached responses immediately while asynchronously refreshing the cache in the background, reducing perceived latency.
- Add cache warming for critical endpoints: pre-populate cache entries on application startup or schedule for frequently accessed resources.
- Write tests verifying cache hits, misses, invalidation correctness, TTL expiration, and stale-while-revalidate behavior.
See ${CLAUDE_SKILL_DIR}/references/implementation.md for the full implementation guide.
Output
${CLAUDE_SKILL_DIR}/src/middleware/cache.js- Cache-aside middleware with hit/miss tracking${CLAUDE_SKILL_DIR}/src/cache/key-generator.js- Deterministic cache key generation${CLAUDE_SKILL_DIR}/src/cache/invalidator.js- Tag-based cache invalidation on mutations${CLAUDE_SKILL_DIR}/src/cache/store.js- Redis/Memcached cache store abstraction${CLAUDE_SKILL_DIR}/src/config/cache-policies.js- Per-endpoint TTL and caching policy configuration${CLAUDE_SKILL_DIR}/tests/cache/- Cache behavior verification tests
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Cache stampede | TTL expires simultaneously for popular key; many requests hit database | Use lock-based revalidation (only one request refreshes); apply jittered TTLs |
| Stale data served | Cache invalidation missed a related resource after mutation | Implement tag-based invalidation covering all affected cache keys; add invalidation audit logging |
| Redis connection failure | Cache store unavailable due to network or server issue | Fall through to database with degraded performance; log cache bypass; alert on sustained failures |
| Cache key collision | Different requests generating identical cache keys | Include all varying parameters in key; hash the full normalized request for uniqueness |
| Memory pressure | Cache grows unbounded consuming all available Redis memory | Configure Redis maxmemory-policy to allkeys-lru; set per-key size limits; monitor memory usage |
Refer to ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error patterns.
Examples
Product catalog caching: Cache GET /products list for 5 minutes and GET /products/:id for 1 hour, invalidating both when any product is created, updated, or deleted via tag products.
User-specific dashboard: Cache dashboard data per user using cache:dashboard:{userId} keys with 30-second TTL, serving stale data during revalidation to keep perceived response time under 50ms.
CDN edge caching: Set Cache-Control: public, max-age=300, stale-while-revalidate=60 on public endpoints, enabling CloudFront to serve cached responses at the edge while revalidating asynchronously.
See ${CLAUDE_SKILL_DIR}/references/examples.md for additional examples.
Resources
- Redis caching patterns: https://redis.io/docs/manual/patterns/
- HTTP caching (MDN): https://developer.mozilla.org/en-US/docs/Web/HTTP/Caching
- Cache-aside vs. read-through vs. write-through patterns
- Stale-while-revalidate: RFC 5861