performance-profiling

To identify web performance bottlenecks, use a structured profiling workflow that establishes a baseline, identifies rendering or bundle issues, applies fixes like lazy loading, and validates the improvements through Lighthouse audits.

Measuring LCP, INP, and CLS metrics in CI/CD is best done by automating Lighthouse audits with a script like lighthouse_audit.py, which produces reproducible JSON performance reports to track core web vitals across builds.

Runtime analysis guides code-splitting and lazy loading by profiling web application execution to isolate heavy bottlenecks and unused JavaScript, enabling targeted performance optimization strategies that reduce bundle size and improve loading metrics.

Yes, you can automate Lighthouse audits to generate JSON performance reports by executing the lighthouse_audit.py script against your target URL, producing actionable scores and summaries for development and production monitoring.

Performance profiling is applicable across development, CI/CD, and production monitoring, allowing teams to consistently measure web vitals, analyze runtime bottlenecks, and validate optimization improvements throughout the application lifecycle.