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About this tool
Compute cache hit ratio, backend load reduction and effective latency (AMAT) from hit and miss counts and latencies.
This calculator computes a cache's hit ratio — hits ÷ (hits + misses) — and turns it into the numbers that matter for capacity planning: effective request latency via the AMAT formula (hit time + miss rate × miss penalty, from Hennessy & Patterson), the speedup versus running uncached, and the share of traffic that still reaches the backend. Feed it counters from Redis INFO, Memcached stats, a CDN dashboard or an application cache and it shows what the cache is really buying you.
Open Cache Hit Ratio Calculator on AltFTool — it loads instantly in your browser.
Enter the values you already know.
Fine-tune the options to match your scenario.
Read the result and use it in your planning or reporting.
Uses AMAT (hit time + miss rate × miss penalty) rather than pretending misses cost nothing.
Shows the exact requests/second your origin still serves at a given traffic rate and hit ratio.
Flags configurations where the cache lookup is slower than the backend it fronts.
Hit ratio = hits ÷ (hits + misses). For example 900 hits and 100 misses give 900/1000 = 90%. In Redis the counters are keyspace_hits and keyspace_misses in INFO stats; in Memcached they are get_hits and get_misses.
It depends on workload, but content and CDN caches commonly target 90%+ while database query caches may sit lower. The marginal value is nonlinear: going from 90% to 99% cuts backend traffic by another factor of ten (10% of requests down to 1%), which is why the last few percentage points matter most.
AMAT (average memory access time) = hit time + miss rate × miss penalty, from Hennessy and Patterson's computer architecture texts. With a 2 ms cache, a 50 ms backend and a 90% hit ratio: 2 + 0.10 × 50 = 7 ms average, a 7.1× speedup over the uncached 50 ms.
Exactly the hit ratio: at 90% hits only 10% of requests reach the backend, so 1,000 req/s of traffic becomes 100 req/s of origin load. This calculator multiplies your traffic rate by the miss ratio to give the residual backend requests per second.
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