performance

Identify frontend performance bottlenecks by measuring Core Web Vitals like LCP, CLS, and INP to establish baselines. Use profiling data to apply targeted fixes such as code-splitting, then verify improvements through repeatable tests.

The best way to measure backend API latency and find N+1 queries is profiling real user data to establish baselines. Analyze the data to pinpoint slow interactions, apply efficient API fixes, and verify through repeatable tests.

Establish a performance baseline by running a profiling pass on your target page or API to collect real user metrics. This measured data identifies current bottlenecks and guides subsequent targeted optimization improvements.

Yes, you can apply code-splitting and caching to speed up page loads. After profiling to establish baselines, apply these targeted fixes to resolve identified bottlenecks and verify the improvements using repeatable tests.

Yes, this measurement-first optimization workflow works for both staging and production environments. It measures real user metrics across pages, APIs, and bundles to identify bottlenecks and guide targeted improvements.

Prevent web performance regressions by implementing guardrails with monitoring and performance budget checks. After applying targeted fixes, verify improvements through repeatable tests to ensure metrics remain within established baselines.