addy-performance-optimization

To identify and fix frontend performance bottlenecks, profile the application to find root causes, implement targeted changes, and verify improvements using metrics like Core Web Vitals. This ensures page load optimization is validated with real data and performance budgets.

Optimizing API response tuning requires profiling backend workloads to identify bottlenecks, applying iterative fixes, and ensuring improvements are validated with metrics. Performance budgets and monitoring guard against future regressions.

Fixing slow LCP or high CLS involves profiling the page to identify the root cause, implementing targeted optimizations, and measuring the impact. This workflow ensures improvements are validated with real data and monitoring.

You need to establish performance budgets when performance requirements exist or when you suspect regressions. Budgets help verify that frontend and backend optimizations result in measured improvements guarded by continuous monitoring.

Yes, the workflow guides measurement, bottleneck identification, and iterative fixes across both frontend and backend workloads. It applies to page load optimization and API response tuning, ensuring all improvements are validated with metrics.

Measuring Core Web Vitals is necessary because performance optimizations must be validated with real data. Profiling reveals bottlenecks, but metrics confirm that targeted changes actually improved load times and overall application performance.