performance-optimization

Identify frontend performance bottlenecks by measuring baseline metrics like LCP and TTI, then using profiling and tracing to pinpoint issues before applying minimal fixes and verifying improvements with repeatable benchmarks.

Measure API response time and database query latency by establishing a performance baseline in staging or production, profiling the backend bottlenecks, applying targeted fixes, and re-measuring to prove the latency improvements.

A measure-first approach improves web app performance by validating fixes with concrete data rather than guesswork, ensuring you document baseline metrics like bundle size and TTFB before applying changes to prove measurable gains.

Yes, you can use this measure-first optimization workflow for both frontend and backend systems, applying profiling and performance budgets across web apps, APIs, and database queries to validate improvements in production or staging environments.

Verify performance improvements after optimizing bundle size and load times by re-measuring the baseline metrics using repeatable tooling and benchmarks, comparing the new results against the initial data to prove the gains.

You should establish a performance baseline before fixing bottlenecks to document current metrics like response time, TTFB, LCP, and bundle size, providing a concrete reference point to validate that your minimal fixes deliver measurable improvements.