Skip the theory rabbit holes. This is the caching knowledge that shows up in system design interviews, code reviews, and the 2 AM production incidents nobody warned you about.

Table of Contents

Why Caching — The 30-Second Version

Where Do You Actually Cache?

Cache-Aside — The Pattern You'll Use 80% of the Time

Write Strategies — The Other Side of the Coin

Eviction Policies — LRU, LFU, and When It Matters

TTL — Getting Expiry Right

Cache Invalidation — The Hard Problem

Cache Stampede — The Failure Mode That Kills Systems

What NOT to Cache

Practical Decision Framework

Summary Cheat Sheet

1. Why Caching

Your database query takes 50ms. Your Redis lookup takes 0.5ms. If that same data is read 10,000 times before it changes, you're doing 10,000 × 50ms of database work — or you could do 1 × 50ms + 9,999 × 0.5ms. That's the entire case for caching.

Caching works because of read-heavy, write-light data patterns . Most applications read the same data far more than they change it.…