caching-strategies

name	caching-strategies
description	CDN, Redis, in-memory cache, cache invalidation, and distributed caching patterns
metadata	{"author":"cosmicstack-labs","version":"1.0.0","category":"backend","tags":["caching","performance","redis","cdn","distributed-systems"]}

Caching Strategies

Cache effectively to improve performance and reduce load.

Cache Layers

Layer	Latency	Storage	Examples
Browser	Local	Small	localStorage, HTTP cache
CDN	Regional	Large	CloudFront, CloudFlare, Fastly
Application	In-process	Small	L1 cache (heap)
Distributed	Network	Large	Redis, Memcached
Database	Same host	Very large	Buffer pool, query cache

Caching Patterns

Cache-Aside (Lazy Loading)

1. Check cache → miss
2. Query database
3. Store in cache
4. Return

Best for: Read-heavy, general purpose.

Write-Through

1. Write to cache
2. Cache writes to DB (sync)
3. Return

Best for: Consistency critical, write-heavy.

Write-Behind

1. Write to cache
2. Return immediately
3. Cache writes to DB (async)

Best for: High throughput writes, eventual consistency OK.

Refresh-Ahead

• Cache proactively refreshes before expiry
• Reduces latency spikes on cache miss
• Requires predictive logic or scheduled refresh

Cache Invalidation

Two hard things: naming, cache invalidation, off-by-one errors.

Strategy	How	Risk
TTL	Expire after X seconds	Stale data during TTL
Event-based	Invalidate on data change	Missed events
Version keys	user_42_v3	Unused old keys accumulate
Write-through	Update cache on write	Write amplification

Redis Patterns

• Use EXPIRE on every SET
• Use SCAN not KEYS in production
• Distributing: Redis Cluster for sharding
• Backup: RDB (snapshot) + AOF (append-only log)
• Monitor: hit rate, memory, evictions, latency