RahulRachhoya Caching Strategies
Cache Levels
| Level | Storage | Speed | Use Case |
|---|---|---|---|
| L1 (in-memory) | Application RAM | <1ms | Hot data, repeated queries |
| L2 (distributed) | Redis/Memcached | 1-5ms | Shared across instances |
| L3 (HTTP/CDN) | Browser/CDN | 10-100ms | Static assets, API responses |
Caching Patterns
- Cache-aside: read from cache, miss → read DB → write to cache → return
- Write-through: write to cache first, then DB
- Write-behind: write to cache, async write to DB
- Cache invalidation: the hardest problem — use TTLs, version keys, or event-driven purges
HTTP Caching
- Use
Cache-Controlheaders:public,private,max-age,no-cache,no-store - Use ETags for conditional requests
- Set appropriate TTLs: static assets (1 year with hash in URL), API responses (seconds to minutes)
Rules
- Cache the result of expensive operations (DB queries, API calls, computation)
- Never cache sensitive data (PII, auth tokens)
- Always set a TTL (even if long) — prevent stale data
- Monitor cache hit rates — low hit rate means wrong cache strategy
- Have a cache warming strategy for critical data