Start with the idea
A profiler shows where time actually goes, and the usual answers are allocation, copying, and syscalls rather than arithmetic. In Rust specifically: check you built with --release, look for clones in a hot loop, prefer with_capacity over repeated growth, and confirm bounds checks are the problem before reaching for unsafe. A benchmark that is not statistically stable is not a benchmark.
Start with a user-visible performance question and a baseline. Is the problem p95 request latency, startup time, battery use, memory footprint, or throughput? These metrics can move in different directions. A release build is necessary for a fair Rust measurement, but it is not enough. Keep input sizes representative, warm caches deliberately, repeat measurements, and record variance. A profiler points to expensive stacks or allocations; it does not automatically tell you which change is safe or worthwhile.
Suppose a hot path clones a vector on every request.
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