performance-optimization

Identify frontend performance bottlenecks by profiling web vitals like LCP, CLS, and INP to pinpoint rendering delays. This approach uses measurement data to locate specific issues, guiding evidence-based fixes that measurably reduce load times and improve user experience.

The best way to optimize backend API performance is through systematic profiling to locate processing bottlenecks and applying measured fixes. This method requires access to performance metrics and validates improvements using repeated measurements to ensure workload speed targets are met.

Prevent performance regressions in web applications by establishing performance budgets and integrating CI checks. These mechanisms monitor web vitals and backend metrics continuously, automatically flagging violations to maintain speed targets and prevent degraded user experiences.

Yes, profiling data is required to improve application performance effectively. This optimization approach relies on measurement and metrics to locate actual bottlenecks across frontend and backend workloads, ensuring applied fixes are validated through repeatable measurements rather than guesswork.

Yes, performance optimization applies directly to single page applications (SPAs) alongside standard web apps and APIs. It targets SPA bottlenecks by measuring frontend web vitals and backend response times, guiding measurable improvements to reduce load times and elevate user experience.