Caching at Scale: Why Deciding What to Cache Matters More Than How

As platforms handling commodities, crypto, or e-commerce grow to thousands of concurrent users, repeated identical requests strain databases and downstream services unnecessarily. Caching is the common solution, but the critical architectural question is determining which data can safely be served stale and for how long. A gold price cached for two seconds may be acceptable in one system but problematic in another, while a balance used to execute a financial transaction carries far greater risk. Caching exists at multiple layers — browsers, CDNs, reverse proxies, and applications — each introducing a version of system state that may diverge from reality. The article argues that setting a TTL is straightforward, but deciding what to cache, where, and who handles invalidation is a far more consequential engineering decision.