| name | performance-profiling |
| description | Performance profiling principles. Measurement, analysis, and optimization techniques. |
| type | skill |
| created | 2026-02-27T00:00:00.000Z |
| domain | data |
| category | data-analysis |
| risk | unknown |
| source | community |
| tags | ["skill","data","data-analysis","performance","profiling"] |
Performance Profiling
Measure, analyze, optimize - in that order.
🔧 Runtime Scripts
Execute these for automated profiling:
| Script | Purpose | Usage |
|---|
scripts/lighthouse_audit.py | Lighthouse performance audit | python scripts/lighthouse_audit.py https://example.com |
1. Core Web Vitals
Targets
| Metric | Good | Poor | Measures |
|---|
| LCP | < 2.5s | > 4.0s | Loading |
| INP | < 200ms | > 500ms | Interactivity |
| CLS | < 0.1 | > 0.25 | Stability |
When to Measure
| Stage | Tool |
|---|
| Development | Local Lighthouse |
| CI/CD | Lighthouse CI |
| Production | RUM (Real User Monitoring) |
2. Profiling Workflow
The 4-Step Process
1. BASELINE → Measure current state
2. IDENTIFY → Find the bottleneck
3. FIX → Make targeted change
4. VALIDATE → Confirm improvement
Profiling Tool Selection
| Problem | Tool |
|---|
| Page load | Lighthouse |
| Bundle size | Bundle analyzer |
| Runtime | DevTools Performance |
| Memory | DevTools Memory |
| Network | DevTools Network |
3. Bundle Analysis
What to Look For
| Issue | Indicator |
|---|
| Large dependencies | Top of bundle |
| Duplicate code |