Web Performance Audit

Overview

Web performance audits measure load times, identify bottlenecks, and guide optimization efforts to create faster, better user experiences.

When to Use

• Regular performance monitoring
• After major changes
• User complaints about slowness
• SEO optimization
• Mobile optimization
• Performance baseline setting

Core Web Vitals (Google Standards)

Largest Contentful Paint (LCP)

• Measure: Time to load largest visible element
• Good: <2.5 seconds | **Poor**: >4 seconds
• Impacts: User perception of speed

First Input Delay (FID)

• Measure: Time from user input to response
• Good: <100ms | **Poor**: >300ms
• Impacts: Responsiveness

Cumulative Layout Shift (CLS)

• Measure: Visual stability (unexpected layout shifts)
• Good: <0.1 | **Poor**: >0.25
• Impacts: User frustration

Additional Key Metrics

• First Contentful Paint (FCP): Target <1.8 seconds
• Time to Interactive (TTI): Target <3.8 seconds
• Total Blocking Time (TBT): Target <300ms
• Interaction to Next Paint (INP): Target <200ms

Measurement Tools

• Google PageSpeed Insights
• Lighthouse (Chrome DevTools)
• WebPageTest
• New Relic / Datadog
• GTmetrix

Quick Start Workflow

1. Measure Baseline

Run Lighthouse audit on both desktop and mobile to establish current performance:

# Chrome DevTools → Lighthouse → Generate Report
# Or use PageSpeed Insights: https://pagespeed.web.dev/

2. Identify Opportunities

Focus on metrics that fail "Good" thresholds:

• LCP > 2.5s → Optimize largest elements, images, fonts
• FID > 100ms → Reduce JavaScript blocking time
• CLS > 0.1 → Reserve space for dynamic content, fix layout shifts

3. Prioritize Fixes

Quick Wins (1-2 days):

• Enable gzip/brotli compression
• Minify CSS/JavaScript
• Compress images
• Defer non-critical JavaScript
• Preload critical fonts

Medium Effort (1-2 weeks):

• Implement lazy loading
• Code splitting
• Service worker caching
• WebP images with srcset
• Critical CSS extraction

Long-term (1-3 months):

• Framework optimization
• Database query optimization
• CDN implementation
• Architecture refactor

4. Implement & Monitor

• Make changes incrementally
• Measure impact after each optimization
• Setup continuous monitoring (Google Analytics Web Vitals, New Relic, etc.)
• Create performance budgets (JS <150KB, CSS <50KB, Images <500KB)

Performance Audit Process

For detailed audit framework with Python code examples: Read: references/analysis-process.md

Key steps:

1. Measure desktop + mobile metrics
2. Collect field data (real users) + lab data
3. Identify specific bottlenecks
4. Prioritize by impact
5. Generate actionable report with timeline

Optimization Strategies

For complete roadmap with checklists: Read: references/optimization-strategies.md

Categories:

• Network: Compression, HTTP/2, CDN, caching
• JavaScript: Code splitting, minification, deferring
• CSS: Critical CSS, unused CSS removal, minification
• Images: WebP, srcset, lazy loading, compression

Monitoring & Continuous Improvement

For monitoring setup and best practices: Read: references/monitoring-setup.md

Setup includes:

• Real-time monitoring tools
• Performance baselines and targets
• Alert configuration for regressions
• Performance budget enforcement

Best Practices

✅ DO

• Measure regularly (not just once)
• Use field data (real users) + lab data
• Focus on Core Web Vitals first
• Set realistic targets (10-20% improvement)
• Prioritize by impact
• Monitor continuously
• Setup performance budgets
• Test on slow networks (3G)
• Include mobile in all testing
• Document improvements

❌ DON'T

• Ignore field data from real users
• Focus on only one metric
• Set impossible targets
• Optimize without measurement
• Forget about image optimization
• Ignore JavaScript costs
• Skip mobile performance testing
• Over-optimize prematurely
• Forget about monitoring after launch
• Expect improvements without effort

Quick Tips

• Start with free Lighthouse audit in Chrome DevTools
• Use WebPageTest for detailed waterfall analysis
• Test on 3G mobile to find real bottlenecks
• Prioritize LCP optimization first (biggest user impact)
• Create performance budget and share with team
• Review performance weekly, not just at launch

References

Analysis Process: read references/analysis-process.md - Audit framework with code examples
Optimization Strategies: read references/optimization-strategies.md - Complete roadmap with checklists
Monitoring Setup: read references/monitoring-setup.md - Continuous monitoring best practices