Why Cache
Slow database queries.
Expensive computations.
Third-party API calls.
Reduce load, increase speed.
Cache Levels
Browser: fastest, closest.
CDN: edge locations.
Reverse proxy: nginx, Varnish.
Application: in-memory, Redis.
Database: query cache.
What to Cache
Frequently accessed.
Expensive to compute.
Rarely changing.
Not: personalized per-user (mostly).
Not: security-critical data.
Cache Invalidation – The Hard Problem
Time-based: TTL (Time to Live).
Event-based: invalidate on update.
Version-based: cache key includes version.
Manual: purge specific keys.
In-Memory Caching
Node.js: LRU cache library.
Python: functools.lru_cache.
Java: Caffeine.
Redis in-memory for shared cache.
Redis – The Standard
Distributed in-memory store.
Fast (microseconds).
Rich data types.
Pub/sub built in.
Persistence optional.
Memcached
Simpler than Redis.
String values only.
Slightly faster for pure caching.
Redis has more features.
CDN Caching
Static assets: images, CSS, JS.
HTML: possible but complex.
API responses: rare but possible.
CloudFront, Cloudflare, Fastly.
Cache Aside Pattern
Check cache first.
Miss: fetch from source.
Update cache.
Return.
Most common pattern.
Write-Through Cache
Write to cache and DB simultaneously.
Always consistent.
Slower writes.
Simpler logic.
Write-Back Cache
Write to cache.
Async write to DB.
Fast writes.
Risk: cache failure = data loss.
Cache Stampede Protection
Popular key expires: all requests hit DB.
Solutions: locking, probabilistic early refresh, background refresh.
Critical for hot keys.
Distributed Caching
Multiple servers share cache.
Redis Cluster or Sentinel.
Consistent hashing for distribution.
Replication for reliability.
Cache Key Design
Include version/context.
Namespace by feature.
Include tenant for multi-tenant.
Don’t be too specific (poor hit rate) or too general (collisions).
Monitoring Cache
Hit rate: should be high (>80% typical).
Miss rate causes.
Eviction rate.
Memory usage.
Redis INFO command.
Common Mistakes
Caching everything.
Long TTLs on volatile data.
Not invalidating on update.
Cache stampedes.
Not monitoring hit rates.
Query Result Caching
Cache expensive queries.
TTL based on data change frequency.
Invalidate on relevant updates.
Postgres pg_bouncer for connection pooling.
Object Cache in WordPress
W3 Total Cache, WP Rocket, Redis Object Cache.
Reduces DB queries.
Significant performance boost.
Standard for high-traffic WP.
Cost/Benefit
Small site: browser + CDN sufficient.
Growing: add Redis.
Scale: Redis cluster.
Cost negligible vs performance gain.
Our Recommendation
Every app: CDN for static assets.
Every app: browser cache headers.
Growing: Redis for application cache.
Complex: multi-layer caching strategy.
Based on Real Projects
This guide is based on our work with:
Further Reading
If this guide helped you, you might also want to read our comprehensive guide on Custom SaaS Development.
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