Caching is one of the most misunderstood tools in software engineering. It’s often suggested as a performance fix long before the real problem is understood.
Caching doesn’t remove complexity, it moves it. Suddenly you’re dealing with invalidation rules, stale reads, consistency tradeoffs, and edge cases that only appear under load. Many systems end up slower overall because they cache the wrong data or cache too early.
The right time to add caching is after you understand where time is actually being spent. Measure first. Identify stable, high-read data with clear invalidation rules. Cache where it simplifies the system, not where it adds uncertainty.
In many cases, better queries, fewer round trips, or clearer data models eliminate the need for caching entirely. Performance improvements that reduce complexity are almost always better than ones that add it.
Caching is powerful, but only when used deliberately.
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