What are caching strategies?
Caching stores results so you can skip repeating expensive work. In a full-stack app there are many places to cache — the browser, a CDN, the server, the database, a Redis layer — and choosing where, plus how to invalidate, is the strategy.
Why it matters
Caching is the cheapest big performance win, but a careless cache serves stale or wrong data confidently. Full-stack developers decide caching across the whole chain, so understanding the layers and the hard part — invalidation — is what lets you speed up an app without introducing subtle correctness bugs.
What to learn
- The caching layers: browser, CDN, server, data
- HTTP cache headers
- Client query caching (TanStack Query)
- Server and database result caching
- Cache invalidation strategies
- TTLs versus explicit invalidation
- Cache keys and avoiding stale data
Common pitfall
Adding caching with no invalidation plan, so users see stale data after an update. Every cached value needs an answer to "when does this refresh?" — a TTL, an explicit bust on write, or both. Caching without that plan trades a real correctness bug for a performance gain, which is rarely worth it.
Resources
Primary (free):
- MDN — HTTP caching · docs
- TanStack Query — Caching · docs
- web.dev — HTTP cache · article
Practice
Add caching at two layers: client query caching for a list, and a server or HTTP cache for a slow endpoint with a TTL. Then add explicit invalidation so an update busts the cache and the UI shows fresh data. Done when an update is reflected immediately despite caching.
Outcomes
- Identify the caching layers across the stack.
- Use client, server, and HTTP caching appropriately.
- Choose TTL versus explicit invalidation.
- Avoid stale data with a clear invalidation plan.