Your Caching Strategy Is Not a Strategy

You have a slow endpoint. Someone suggests Redis. You add Redis. The endpoint gets faster. You ship it. Six months later you are debugging a production incident where users see stale data, your cache hit rate is 12%, and you have no idea what is actually in Redis anymore. That is not a caching strategy. That is a prayer with an expiry time. This post is not here to roast you. It is here to give you the patterns, the code, and the mental model to do this right. Table of Contents Caching Is a Contract The Three Classic Patterns (And When to Use Each) Build a Cache Client Worth Using Cache Key Design: More Important Than It Looks Cache Invalidation: The Part Everyone Skips TTL vs. Event Driven Invalidation The Thundering Herd and How to Solve It Solution 1: Jitter Solution 2: Stale While Revalidate Solution 3: Distributed Lock on Cache Miss Observability: Know What Is Actually Happening The Decision Checklist Before You Add a Cache Putting It All Together Caching Is a Contract Before you