18 KiB
18 KiB
Performance Benchmarking Operation
You are executing the benchmark operation to perform load testing, rendering benchmarks, query benchmarks, and regression detection.
Parameters
Received: $ARGUMENTS (after removing 'benchmark' operation name)
Expected format: type:"load|rendering|query|integration|all" [baseline:"version-or-tag"] [duration:"seconds"] [concurrency:"number"] [target:"url-or-endpoint"]
Parameter definitions:
type(required): Benchmark type -load,rendering,query,integration, orallbaseline(optional): Baseline version for comparison (e.g., "v1.2.0", "main", "baseline-2025-10-14")duration(optional): Test duration in seconds (default: 60s)concurrency(optional): Number of concurrent users/connections (default: 50)target(optional): Specific URL or endpoint to benchmark
Workflow
1. Setup Benchmarking Environment
# Install benchmarking tools
npm install -g k6 lighthouse-ci autocannon
# For database benchmarking
npm install -g pg-bench
# Create benchmark results directory
mkdir -p benchmark-results/$(date +%Y-%m-%d)
2. Load Testing with k6
Basic Load Test Script:
// loadtest.js
import http from 'k6/http';
import { check, sleep } from 'k6';
import { Rate } from 'k6/metrics';
const errorRate = new Rate('errors');
export const options = {
stages: [
{ duration: '30s', target: 20 }, // Ramp up to 20 users
{ duration: '1m', target: 50 }, // Stay at 50 users
{ duration: '30s', target: 100 }, // Spike to 100 users
{ duration: '1m', target: 50 }, // Back to 50 users
{ duration: '30s', target: 0 }, // Ramp down
],
thresholds: {
http_req_duration: ['p(95)<500', 'p(99)<1000'], // 95% < 500ms, 99% < 1s
http_req_failed: ['rate<0.01'], // Error rate < 1%
errors: ['rate<0.1'],
},
};
export default function () {
const responses = http.batch([
['GET', 'https://api.example.com/users'],
['GET', 'https://api.example.com/posts'],
['GET', 'https://api.example.com/comments'],
]);
responses.forEach((res) => {
const success = check(res, {
'status is 200': (r) => r.status === 200,
'response time < 500ms': (r) => r.timings.duration < 500,
});
errorRate.add(!success);
});
sleep(1);
}
Run Load Test:
# Basic load test
k6 run loadtest.js
# Custom configuration
k6 run --vus 100 --duration 300s loadtest.js
# Output to JSON for analysis
k6 run --out json=results.json loadtest.js
# Cloud run (for distributed testing)
k6 cloud run loadtest.js
Advanced Load Test with Scenarios:
// advanced-loadtest.js
import http from 'k6/http';
import { check } from 'k6';
export const options = {
scenarios: {
// Scenario 1: Constant load
constant_load: {
executor: 'constant-vus',
vus: 50,
duration: '5m',
tags: { scenario: 'constant' },
},
// Scenario 2: Spike test
spike_test: {
executor: 'ramping-vus',
startVUs: 0,
stages: [
{ duration: '10s', target: 200 },
{ duration: '30s', target: 200 },
{ duration: '10s', target: 0 },
],
startTime: '5m',
tags: { scenario: 'spike' },
},
// Scenario 3: Stress test
stress_test: {
executor: 'ramping-arrival-rate',
startRate: 50,
timeUnit: '1s',
stages: [
{ duration: '2m', target: 100 },
{ duration: '3m', target: 200 },
{ duration: '2m', target: 400 },
],
startTime: '10m',
tags: { scenario: 'stress' },
},
},
thresholds: {
'http_req_duration{scenario:constant}': ['p(95)<500'],
'http_req_duration{scenario:spike}': ['p(95)<1000'],
'http_req_failed': ['rate<0.05'],
},
};
export default function () {
const res = http.get('https://api.example.com/users');
check(res, {
'status is 200': (r) => r.status === 200,
});
}
3. Frontend Rendering Benchmarks
Lighthouse CI Configuration:
// lighthouserc.json
{
"ci": {
"collect": {
"url": [
"http://localhost:3000",
"http://localhost:3000/dashboard",
"http://localhost:3000/profile"
],
"numberOfRuns": 3,
"settings": {
"preset": "desktop",
"throttling": {
"rttMs": 40,
"throughputKbps": 10240,
"cpuSlowdownMultiplier": 1
}
}
},
"assert": {
"assertions": {
"categories:performance": ["error", {"minScore": 0.9}],
"categories:accessibility": ["error", {"minScore": 0.9}],
"first-contentful-paint": ["error", {"maxNumericValue": 2000}],
"largest-contentful-paint": ["error", {"maxNumericValue": 2500}],
"cumulative-layout-shift": ["error", {"maxNumericValue": 0.1}],
"total-blocking-time": ["error", {"maxNumericValue": 300}]
}
},
"upload": {
"target": "filesystem",
"outputDir": "./benchmark-results"
}
}
}
Run Lighthouse CI:
# Single run
lhci autorun
# Compare with baseline
lhci autorun --config=lighthouserc.json
# Upload results for comparison
lhci upload --target=temporary-public-storage
Custom Rendering Benchmark:
// rendering-benchmark.js
const puppeteer = require('puppeteer');
async function benchmarkRendering(url, iterations = 10) {
const browser = await puppeteer.launch();
const results = [];
for (let i = 0; i < iterations; i++) {
const page = await browser.newPage();
// Start performance measurement
await page.goto(url, { waitUntil: 'networkidle2' });
const metrics = await page.evaluate(() => {
const navigation = performance.getEntriesByType('navigation')[0];
const paint = performance.getEntriesByType('paint');
return {
domContentLoaded: navigation.domContentLoadedEventEnd - navigation.domContentLoadedEventStart,
loadComplete: navigation.loadEventEnd - navigation.loadEventStart,
firstPaint: paint.find(p => p.name === 'first-paint')?.startTime,
firstContentfulPaint: paint.find(p => p.name === 'first-contentful-paint')?.startTime,
domInteractive: navigation.domInteractive,
};
});
results.push(metrics);
await page.close();
}
await browser.close();
// Calculate averages
const avg = (key) => results.reduce((sum, r) => sum + r[key], 0) / results.length;
return {
avgDOMContentLoaded: avg('domContentLoaded'),
avgLoadComplete: avg('loadComplete'),
avgFirstPaint: avg('firstPaint'),
avgFirstContentfulPaint: avg('firstContentfulPaint'),
avgDOMInteractive: avg('domInteractive'),
};
}
// Run benchmark
benchmarkRendering('http://localhost:3000').then(console.log);
4. Database Query Benchmarks
PostgreSQL - pg_bench:
# Initialize benchmark database
pgbench -i -s 50 benchmark_db
# Run benchmark (50 clients, 1000 transactions each)
pgbench -c 50 -t 1000 benchmark_db
# Custom SQL script benchmark
cat > custom-queries.sql <<'EOF'
SELECT * FROM users WHERE email = 'test@example.com';
SELECT p.*, u.name FROM posts p JOIN users u ON p.user_id = u.id LIMIT 100;
EOF
pgbench -c 10 -t 100 -f custom-queries.sql benchmark_db
# Output JSON results
pgbench -c 50 -t 1000 --log --log-prefix=benchmark benchmark_db
Custom Query Benchmark Script:
// query-benchmark.js
const { Pool } = require('pg');
const pool = new Pool({ connectionString: process.env.DATABASE_URL });
async function benchmarkQuery(query, params = [], iterations = 1000) {
const times = [];
for (let i = 0; i < iterations; i++) {
const start = process.hrtime.bigint();
await pool.query(query, params);
const end = process.hrtime.bigint();
times.push(Number(end - start) / 1_000_000); // Convert to ms
}
times.sort((a, b) => a - b);
return {
iterations,
min: times[0].toFixed(2),
max: times[times.length - 1].toFixed(2),
avg: (times.reduce((a, b) => a + b, 0) / times.length).toFixed(2),
p50: times[Math.floor(times.length * 0.50)].toFixed(2),
p95: times[Math.floor(times.length * 0.95)].toFixed(2),
p99: times[Math.floor(times.length * 0.99)].toFixed(2),
};
}
// Run benchmarks
async function runBenchmarks() {
console.log('Benchmarking user lookup by email...');
const userLookup = await benchmarkQuery(
'SELECT * FROM users WHERE email = $1',
['test@example.com']
);
console.log(userLookup);
console.log('\nBenchmarking posts with user join...');
const postsJoin = await benchmarkQuery(
'SELECT p.*, u.name FROM posts p JOIN users u ON p.user_id = u.id LIMIT 100'
);
console.log(postsJoin);
await pool.end();
}
runBenchmarks();
5. Integration/E2E Benchmarks
Playwright Performance Testing:
// e2e-benchmark.js
const { chromium } = require('playwright');
async function benchmarkUserFlow(iterations = 10) {
const results = [];
for (let i = 0; i < iterations; i++) {
const browser = await chromium.launch();
const context = await browser.newContext();
const page = await context.newPage();
const startTime = Date.now();
// User flow
await page.goto('http://localhost:3000');
await page.fill('input[name="email"]', 'user@example.com');
await page.fill('input[name="password"]', 'password123');
await page.click('button[type="submit"]');
await page.waitForSelector('.dashboard');
await page.click('a[href="/profile"]');
await page.waitForSelector('.profile-page');
const endTime = Date.now();
results.push(endTime - startTime);
await browser.close();
}
const avg = results.reduce((a, b) => a + b, 0) / results.length;
const min = Math.min(...results);
const max = Math.max(...results);
return { avg, min, max, results };
}
benchmarkUserFlow().then(console.log);
6. Baseline Management and Comparison
Save Baseline:
# Save current performance as baseline
mkdir -p baselines/
# k6 results
k6 run --out json=baselines/baseline-$(date +%Y-%m-%d)-load.json loadtest.js
# Lighthouse results
lhci autorun --config=lighthouserc.json
cp -r .lighthouseci/ baselines/baseline-$(date +%Y-%m-%d)-lighthouse/
# Query benchmarks
node query-benchmark.js > baselines/baseline-$(date +%Y-%m-%d)-queries.json
Compare with Baseline:
// compare-benchmarks.js
const fs = require('fs');
function compareBenchmarks(currentFile, baselineFile) {
const current = JSON.parse(fs.readFileSync(currentFile));
const baseline = JSON.parse(fs.readFileSync(baselineFile));
const metrics = ['p50', 'p95', 'p99', 'avg'];
const comparison = {};
metrics.forEach(metric => {
const currentValue = parseFloat(current[metric]);
const baselineValue = parseFloat(baseline[metric]);
const diff = currentValue - baselineValue;
const percentChange = (diff / baselineValue) * 100;
comparison[metric] = {
current: currentValue,
baseline: baselineValue,
diff: diff.toFixed(2),
percentChange: percentChange.toFixed(2),
regression: diff > 0,
};
});
return comparison;
}
// Usage
const comparison = compareBenchmarks(
'results/current-queries.json',
'baselines/baseline-2025-10-01-queries.json'
);
console.log('Performance Comparison:');
Object.entries(comparison).forEach(([metric, data]) => {
const emoji = data.regression ? '⚠️' : '✅';
console.log(`${emoji} ${metric}: ${data.percentChange}% change`);
});
7. Regression Detection
Automated Regression Detection:
// detect-regression.js
function detectRegression(comparison, thresholds = {
p50: 10, // 10% increase is regression
p95: 15,
p99: 20,
}) {
const regressions = [];
Object.entries(comparison).forEach(([metric, data]) => {
const threshold = thresholds[metric] || 10;
if (data.percentChange > threshold) {
regressions.push({
metric,
change: data.percentChange,
threshold,
current: data.current,
baseline: data.baseline,
});
}
});
return {
hasRegression: regressions.length > 0,
regressions,
};
}
// Usage in CI/CD
const comparison = compareBenchmarks('current.json', 'baseline.json');
const regression = detectRegression(comparison);
if (regression.hasRegression) {
console.error('Performance regression detected!');
regression.regressions.forEach(r => {
console.error(`${r.metric}: ${r.change}% increase (threshold: ${r.threshold}%)`);
});
process.exit(1); // Fail CI build
}
8. Continuous Performance Monitoring
GitHub Actions Workflow:
# .github/workflows/performance.yml
name: Performance Benchmarks
on:
pull_request:
branches: [main]
schedule:
- cron: '0 0 * * *' # Daily at midnight
jobs:
benchmark:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Setup Node.js
uses: actions/setup-node@v3
with:
node-version: '18'
- name: Install dependencies
run: |
npm ci
npm install -g k6 @lhci/cli
- name: Build application
run: npm run build
- name: Start server
run: npm start &
env:
NODE_ENV: production
- name: Wait for server
run: npx wait-on http://localhost:3000
- name: Run Lighthouse CI
run: lhci autorun --config=lighthouserc.json
- name: Run load tests
run: k6 run --out json=results-load.json loadtest.js
- name: Compare with baseline
run: node scripts/compare-benchmarks.js
- name: Upload results
uses: actions/upload-artifact@v3
with:
name: benchmark-results
path: benchmark-results/
- name: Comment PR with results
if: github.event_name == 'pull_request'
uses: actions/github-script@v6
with:
script: |
const fs = require('fs');
const results = JSON.parse(fs.readFileSync('benchmark-results/summary.json'));
github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: `## Performance Benchmark Results\n\n${results.summary}`
});
Output Format
# Performance Benchmark Report
**Benchmark Date**: [Date]
**Benchmark Type**: [load/rendering/query/integration/all]
**Baseline**: [version or "none"]
**Duration**: [test duration]
**Concurrency**: [concurrent users/connections]
## Executive Summary
[Summary of benchmark results and any regressions detected]
## Load Testing Results (k6)
### Test Configuration
- **Virtual Users**: 50 (ramped from 0 to 100)
- **Duration**: 5 minutes
- **Scenarios**: Constant load, spike test, stress test
### Results
| Metric | Value | Threshold | Status |
|--------|-------|-----------|--------|
| Total Requests | 45,230 | - | - |
| Request Rate | 150.77/s | - | - |
| Request Duration (p50) | 85ms | <200ms | ✅ Pass |
| Request Duration (p95) | 245ms | <500ms | ✅ Pass |
| Request Duration (p99) | 680ms | <1000ms | ✅ Pass |
| Failed Requests | 0.02% | <1% | ✅ Pass |
### Comparison with Baseline
| Metric | Current | Baseline (v1.2.0) | Change |
|--------|---------|-------------------|--------|
| p50 | 85ms | 120ms | -29% ✅ |
| p95 | 245ms | 450ms | -46% ✅ |
| p99 | 680ms | 980ms | -31% ✅ |
| Request Rate | 150.77/s | 85/s | +77% ✅ |
**Overall**: 46% improvement in p95 response time
## Frontend Rendering Benchmarks (Lighthouse)
### Home Page
| Metric | Score | Value | Baseline | Change |
|--------|-------|-------|----------|--------|
| Performance | 94 | - | 62 | +32 ✅ |
| FCP | - | 0.8s | 2.1s | -62% ✅ |
| LCP | - | 1.8s | 4.2s | -57% ✅ |
| TBT | - | 45ms | 280ms | -84% ✅ |
| CLS | - | 0.02 | 0.18 | -89% ✅ |
### Dashboard Page
| Metric | Score | Value | Baseline | Change |
|--------|-------|-------|----------|--------|
| Performance | 89 | - | 48 | +41 ✅ |
| LCP | - | 2.1s | 5.8s | -64% ✅ |
| TBT | - | 65ms | 420ms | -85% ✅ |
## Database Query Benchmarks
### User Lookup by Email (1000 iterations)
| Metric | Current | Baseline | Change |
|--------|---------|----------|--------|
| Min | 6ms | 380ms | -98% ✅ |
| Avg | 8ms | 450ms | -98% ✅ |
| p50 | 7ms | 445ms | -98% ✅ |
| p95 | 12ms | 520ms | -98% ✅ |
| p99 | 18ms | 680ms | -97% ✅ |
**Optimization**: Added index on users.email
### Posts with User Join (1000 iterations)
| Metric | Current | Baseline | Change |
|--------|---------|----------|--------|
| Avg | 45ms | 820ms | -95% ✅ |
| p95 | 68ms | 1200ms | -94% ✅ |
| p99 | 95ms | 2100ms | -95% ✅ |
**Optimization**: Fixed N+1 query with eager loading
## Integration/E2E Benchmarks
### User Login Flow (10 iterations)
| Metric | Value | Baseline | Change |
|--------|-------|----------|--------|
| Average | 1,245ms | 3,850ms | -68% ✅ |
| Min | 1,120ms | 3,200ms | -65% ✅ |
| Max | 1,420ms | 4,500ms | -68% ✅ |
**Flow**: Home → Login → Dashboard → Profile
## Regression Analysis
**Regressions Detected**: None
**Performance Improvements**: 12 metrics improved
- Load testing: 46% faster p95 response time
- Frontend rendering: 57% faster LCP
- Database queries: 98% faster average query time
- E2E flows: 68% faster completion time
## Recommendations
1. **Continue Monitoring**: Set up daily benchmarks to catch regressions early
2. **Performance Budget**: Establish budgets based on current metrics
- p95 response time < 300ms
- LCP < 2.5s
- Database queries < 100ms average
3. **Optimize Further**: Investigate remaining slow queries in analytics module
## Testing Instructions
### Run Load Tests
```bash
k6 run --vus 50 --duration 60s loadtest.js
Run Rendering Benchmarks
lhci autorun --config=lighthouserc.json
Run Query Benchmarks
node query-benchmark.js
Compare with Baseline
node scripts/compare-benchmarks.js results/current.json baselines/baseline-2025-10-01.json