caching-strategy-implementerlisted

# Caching Strategy Implementer ## Prerequisites & Dependencies - Redis 7+ strongly recommended, or an in-memory cache (Node `node-cache`, Python `functools.lru_cache`) - Language runtime: Node.js 18+, Python 3.10+, or Go 1.21+ - Optional: `npm i ioredis` / `pip install redis` / `go-redis` for Redis client ## Execution Steps 1. Choose the caching strategy based on data access patterns: Cache-Aside for read-heavy, Write-Through for write-heavy, TTL/LRU for eviction policies 2. Set up the Redis (or LRU) client with connection pooling and default TTL (e.g., 300s for session data, 86400s for product catalogs) 3. Implement **Cache-Aside**: on read, check cache first; miss → fetch from DB → populate cache; on write → invalidate/update cache entry 4. Implement **Write-Through**: every write goes through cache, which synchronously writes through to the underlying DB 5. Configure eviction policies: `maxmemory-policy allkeys-lru` in Redis, or `maxsize` + `ttl` in Node/Python caches 6. Add cache warming for critical paths and monitor hit/miss ratios via Redis `INFO stats` or Prometheus metrics 7. Benchmark read/write latency with and without cache, iterate TTL/size values ```javascript // Cache-Aside pattern with ioredis (Node.js) const Redis = require('ioredis'); const redis = new Redis(); async function getUser(id) { const cacheKey = `user:${id}`; const cached = await redis.get(cacheKey); if (cached) return JSON.parse(cached); // cache hit // cache miss → fetch from DB c