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

1. 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).
2. 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).
3. Build a cache-aside middleware that checks the cache before executing the handler, returning cached responses with X-Cache: HIT header, or executing the handler, caching the result, and returning with X-Cache: MISS.
4. 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.