The caching module covered the patterns and their failure modes one at a time. This article pulls them into a practical set of habits and warnings, the things experienced teams do by default and the mistakes that catch everyone at least once. None of it is complicated, but each item corresponds to a production incident someone had to debug, so treating them as defaults saves you from repeating the lesson.
This is part 15 and the last of the caching module in the Redis Masterclass, following cache stampede.
Cache the right things
Caching adds complexity, so it should earn its place. The data worth caching is read far more than it's written and expensive to produce: a query joining several tables, a computed aggregate, a rendered fragment, a rarely-changing config. Caching data that changes on every request, or that's trivial to fetch, adds moving parts for little gain. Before caching something, ask whether it's actually read-heavy and actually slow to fetch; if not, skip it.
The corollary is don't cache everything reflexively. Each cached key is another thing to invalidate correctly and another consumer of memory. A smaller cache of genuinely hot data is easier to keep correct than a sprawling one caching things that barely benefit.
