Using Redis as a cache looks simple at first—store data, read it faster. In practice, caching introduces its own set of consistency, invalidation, and scaling problems. A good caching strategy is not about adding Redis everywhere. It is about deciding what to cache, when to update it, and how to keep it correct under change. This article focuses on the caching patterns that hold up in real systems