CompanySite/scripts/README-PERFORMANCE.md

Performance Testing Scripts

Quick reference for performance testing and monitoring.

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Quick Start

Test Current Server Performance

# Quick check (recommended)
curl -w "Time: %{time_total}s\n" -o /dev/null -s http://localhost:10000/

# Comprehensive test
python scripts/performance_test.py

# Shell script (Unix/Mac)
bash scripts/quick-perf-check.sh

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Available Scripts

1. performance_test.py

Purpose: Comprehensive Python-based performance testing

Usage:

python scripts/performance_test.py

Features:

• Tests multiple endpoints (pages + APIs)
• Statistical analysis (mean, median, std dev)
• Domain verification
• Performance recommendations
• JSON output support

Output:

• Response time statistics per endpoint
• Overall performance summary
• Recommendations for slow endpoints
• Pass/fail status

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2. quick-perf-check.sh

Purpose: Fast performance spot-check

Usage:

# Default (localhost:10000)
bash scripts/quick-perf-check.sh

# Custom URL
bash scripts/quick-perf-check.sh https://workroot.in

Features:

• Quick response time checks
• Color-coded status indicators
• Minimal dependencies (just curl)
• Production-ready

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3. lighthouse_audit.py

Purpose: Lighthouse performance audit

Usage:

python scripts/lighthouse_audit.py <url>

# Example
python scripts/lighthouse_audit.py http://localhost:10000

Features:

• Full Lighthouse audit
• Performance, accessibility, SEO scores
• Best practices analysis
• Detailed issue reporting

Note: May have encoding issues on Windows. Use WSL or fix Unicode output.

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Performance Targets

Metric	Excellent	Good	Needs Work
SSR Page Load	< 200ms	< 500ms	> 500ms
API Response	< 100ms	< 200ms	> 200ms
TTFB	< 200ms	< 300ms	> 300ms

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Core Web Vitals (Production)

Metric	Good	Needs Improvement	Poor
LCP	< 2.5s	2.5s - 4.0s	> 4.0s
INP	< 200ms	200ms - 500ms	> 500ms
CLS	< 0.1	0.1 - 0.25	> 0.25

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Manual Testing with curl

Basic Response Time

curl -w "\nTime: %{time_total}s\n" -o /dev/null -s http://localhost:10000/

Detailed Timing

curl -w "\n
Total Time: %{time_total}s
DNS Lookup: %{time_namelookup}s
TCP Connect: %{time_connect}s
TLS Handshake: %{time_appconnect}s
Time to First Byte: %{time_starttransfer}s
HTTP Code: %{http_code}
\n" -o /dev/null -s http://localhost:10000/

Test Multiple Endpoints

for endpoint in / /contact /about /api/health.json; do
  echo "Testing $endpoint"
  curl -w "Time: %{time_total}s\n" -o /dev/null -s http://localhost:10000$endpoint
  echo ""
done

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CI/CD Integration

GitHub Actions Example

- name: Performance Test
  run: |
    npm run build
    npm run preview &
    sleep 5
    python scripts/performance_test.py

Pre-deployment Check

# Build and test
npm run build
npm run preview &
sleep 5
python scripts/performance_test.py

# If all tests pass, deploy
if [ $? -eq 0 ]; then
  echo "Performance tests passed"
  # Deploy command here
else
  echo "Performance tests failed"
  exit 1
fi

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Troubleshooting

Slow Response Times (> 500ms)

Possible Causes:

1. Development server (not optimized)
2. Cold start (first request)
3. Large bundle size
4. Unoptimized images
5. Missing caching

Solutions:

# 1. Build for production
npm run build

# 2. Analyze bundle
npm run build -- --analyze

# 3. Check bundle size
du -sh dist/

# 4. Test production build
npm run preview

High Variance in Response Times

Possible Causes:

1. Network issues
2. System load
3. Garbage collection
4. Cache inconsistency

Solutions:

• Run multiple iterations (10+)
• Test during low system load
• Close other applications
• Clear caches between tests

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Monitoring in Production

Recommended Tools

• DataDog RUM: Real User Monitoring
• New Relic: Application Performance Monitoring
• Google Analytics: Core Web Vitals
• Sentry: Performance tracking + errors

Custom Performance Monitoring

// Add to your app
if (typeof window !== 'undefined') {
  window.addEventListener('load', () => {
    const perfData = performance.getEntriesByType('navigation')[0];
    console.log('Page Load Time:', perfData.loadEventEnd - perfData.fetchStart, 'ms');
    console.log('DOM Interactive:', perfData.domInteractive - perfData.fetchStart, 'ms');
    console.log('TTFB:', perfData.responseStart - perfData.requestStart, 'ms');
  });
}

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Best Practices

1. Test Regularly: Run performance tests before each deployment
2. Set Baselines: Document baseline performance metrics
3. Monitor Trends: Track performance over time
4. Test Production: Dev server performance != production performance
5. Real Users: Use RUM to understand actual user experience
6. Set Budgets: Define performance budgets and enforce them

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Resources

• Web.dev Performance
• Lighthouse Scoring
• Core Web Vitals
• Astro Performance

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Quick Reference

# Test homepage
curl -w "%{time_total}s\n" -o /dev/null -s http://localhost:10000/

# Comprehensive test
python scripts/performance_test.py

# Lighthouse audit
npx lighthouse http://localhost:10000 --view

# Bundle analysis
npm run build -- --analyze