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Performance Optimization

Deep performance optimization based on Lighthouse performance audits. Focuses on loading speed, runtime efficiency, and resource optimization.

How it Works

  1. Identify performance bottlenecks in code and assets
  2. Prioritize by impact on Core Web Vitals
  3. Provide specific optimizations with code examples
  4. Measure improvement with before/after metrics

Performance Budget

| Resource | Budget | Rationale | |----------|--------|-----------|| | Total page weight | < 1.5 MB | 3G loads in ~4s | | JavaScript (compressed) | < 300 KB | Parsing + execution time | | CSS (compressed) | < 100 KB | Render blocking | | Images (above-fold) | < 500 KB | LCP impact | | Fonts | < 100 KB | FOIT/FOUT prevention | | Third-party | < 200 KB | Uncontrolled latency |

Critical Rendering Path

Server Response

  • TTFB < 800ms — Time to First Byte should be fast. Use CDN, caching, and efficient backends.
  • Enable compression — Gzip or Brotli for text assets. Brotli preferred (15-20% smaller).
  • HTTP/2 or HTTP/3 — Multiplexing reduces connection overhead.
  • Edge caching — Cache HTML at CDN edge when possible.

Resource Loading

JavaScript Optimization

Image Optimization

Format Selection

Responsive Images

LCP Image Priority

Font Optimization

Loading Strategy

Caching Strategy

Cache-Control Headers

Service Worker Caching

Runtime Performance

Avoid Layout Thrashing

Debounce Expensive Operations

Use requestAnimationFrame

Virtualize Long Lists

Third-Party Scripts

Load Strategies

Facade Pattern

Measurement

Key Metrics

Testing Commands

For Core Web Vitals specific optimizations, see Core Web Vitals.