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A cache only helps if it serves enough requests to beat its cost. Without measurement, you cannot tell a useful cache from wasted memory.

A hit is served from the cache; a miss requires fetching from the slow source. Counting both is the foundation of every cache metric.

The hit ratio is hits over total requests — the single most important cache metric. A higher ratio means the cache absorbs more of your load.

There is no universal target hit ratio: a read-heavy catalog may hit 95%, a personalized feed only 50%. Judge it against the cost saved.

The miss penalty is how much slower a miss is than a hit. Even a modest hit ratio is valuable when each miss is extremely expensive.

Combine hit ratio and miss penalty into the expected average latency per request: ratio times hit, plus (1 minus ratio) times miss.

A cache also cuts origin load: 80% hits means the database handles only 20% of traffic. Track origin queries-per-second before and after caching.

Watch eviction count and memory. A high eviction rate means the cache is too small — entries get pushed out before reuse, dragging down the hit ratio.

TTL is a trade-off: short TTLs lower the hit ratio but improve freshness; long ones do the reverse. Measure both hit ratio and stale-read rate to tune it.

A fresh cache is cold with a near-zero hit ratio, then warms as it fills. Judge effectiveness at steady state, not during the cold-start window.

Let metrics drive tuning: low hit ratio with high evictions means grow the cache; high hit ratio with stale complaints means shorten the TTL.

Your cache has a 55% hit ratio, which sounds low. When is this cache still clearly worth keeping?

You learned to measure cache effectiveness: hit ratio is the headline read with miss penalty, combine into average latency, watch evictions and stale reads, act on the numbers.