performance-optimization

Performance optimization requires capturing a baseline measurement, profiling the bottleneck, and re-running the same measurement to verify improvements. This workflow emits a structured performance-evidence report with a regression guard to prevent speculative tuning from shipping.

Motion budgeting for browser performance requires frame stability, long-task evidence, and bundle or memory budgets for canvas, WebGL, and media work. It enforces reduced-motion and fallback proof before approving claims of smooth or lightweight user experiences.

To stop performance regressions, define primary and guard metrics before applying the smallest scoped database or build change. Capture baseline command output, use profiling or tracing evidence, and generate a performance-evidence report including a regression guard.

Performance optimization applies to backend, database or search, build or bundle, and browser-facing motion or video surfaces. It requires verified before and after results, effect budgets, and reduced-motion proof when relevant across these distinct technical scopes.

The best way to profile a bottleneck is to run a baseline measurement for the complained-about route or workload first. Apply the smallest scoped performance fix, then re-run the same measurement and produce a structured performance-evidence report.

You need an effect budget and reduced-motion evidence when performance work alters browser-facing motion, video, canvas, WebGL, or media surfaces. This proof blocks handoff if evidence is missing and prevents unverified smooth or lightweight performance claims.