Three core steps in the performance-tuning life cycle Measure — establish performance metrics and a baseline (e.g., runtime, memory, latency) using profiling/benchmark tools like Hyperfine and DHAT. , Isolate — find the actual hotspots and bottlenecks (e.g., with Cargo Flame Graph, flamegraphs, or async tools like tracing/Tokio Console) so you know where to focus effort. , Optimize — apply targeted changes (better algorithms/data structures, reduce allocations, caching, parallelism), then rebuild, test, and re-run benchmarks to verify improvements. , Repeat this cycle iteratively: measure again after each change to confirm gains and avoid optimizing the wrong parts. ,