Load testing patterns
AI software team for Claude Code - 138 agents, 295 skills, 73 hooks. Self-learning, multi-agent swarm, autonomous skill evolution.
npx -y skills add vibeeval/vibecosystem --skill load-testing-patternsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
k6 script templates, load profiles, response time thresholds, SLO validation, and performance testing strategies.
SKILL.md
6.4 KB, as published. Nobody here has run it
Load Testing Patterns
Performance validation with k6 for SLO-driven load testing.
Basic k6 Script Template
import http from 'k6/http'
import { check, sleep } from 'k6'
import { Rate, Trend } from 'k6/metrics'
// Custom metrics
const errorRate = new Rate('errors')
const loginDuration = new Trend('login_duration')
// Thresholds define pass/fail criteria
export const options = {
thresholds: {
http_req_duration: ['p(95)<500', 'p(99)<1000'], // 95th < 500ms, 99th < 1s
http_req_failed: ['rate<0.01'], // Error rate < 1%
errors: ['rate<0.05'], // Custom error rate < 5%
},
scenarios: {
smoke: {
executor: 'constant-vus',
vus: 5,
duration: '1m',
}
}
}
export default function () {
const res = http.get('https://api.example.com/health')
check(res, {
'status is 200': (r) => r.status === 200,
'response time < 500ms': (r) => r.timings.duration < 500,
'body has status': (r) => JSON.parse(r.body).status === 'ok',
}) || errorRate.add(1)
sleep(1)
}
Load Profiles
export const options = {
scenarios: {
// 1. Smoke Test: verify system works under minimal load
smoke: {
executor: 'constant-vus',
vus: 3,
duration: '1m',
},
// 2. Load Test: normal expected traffic
load: {
executor: 'ramping-vus',
startVUs: 0,
stages: [
{ duration: '2m', target: 50 }, // Ramp up
{ duration: '5m', target: 50 }, // Steady state
{ duration: '2m', target: 0 }, // Ramp down
],
},
// 3. Stress Test: find breaking point
stress: {
executor: 'ramping-vus',
startVUs: 0,
stages: [
{ duration: '2m', target: 100 },
{ duration: '5m', target: 100 },
{ duration: '2m', target: 200 }, // Beyond normal
{ duration: '5m', target: 200 },
{ duration: '2m', target: 300 }, // Breaking point?
{ duration: '5m', target: 300 },
{ duration: '5m', target: 0 },
],
},
// 4. Spike Test: sudden traffic surge
spike: {
executor: 'ramping-vus',
startVUs: 0,
stages: [
{ duration: '30s', target: 10 },
{ duration: '10s', target: 500 }, // Instant spike
{ duration: '1m', target: 500 },
{ duration: '10s', target: 10 }, // Instant drop
{ duration: '1m', target: 10 },
],
},
// 5. Soak Test: sustained load over time (memory leaks, connection exhaustion)
soak: {
executor: 'constant-vus',
vus: 50,
duration: '2h',
},
}
}
Realistic User Scenarios
import http from 'k6/http'
import { check, group, sleep } from 'k6'
const BASE_URL = __ENV.BASE_URL || 'https://api.example.com'
export default function () {
// Simulate real user journey, not isolated endpoints
let token
group('01_login', () => {
const res = http.post(`${BASE_URL}/auth/login`, JSON.stringify({
email: `user${__VU}@test.com`,
password: 'testpass123'
}), { headers: { 'Content-Type': 'application/json' } })
check(res, { 'login successful': (r) => r.status === 200 })
token = JSON.parse(res.body).token
})
sleep(Math.random() * 3 + 1) // Think time: 1-4 seconds
group('02_browse_products', () => {
const headers = { Authorization: `Bearer ${token}` }
const listRes = http.get(`${BASE_URL}/products?page=1&limit=20`, { headers })
check(listRes, { 'products loaded': (r) => r.status === 200 })
const products = JSON.parse(listRes.body).data
if (products.length > 0) {
const product = products[Math.floor(Math.random() * products.length)]
const detailRes = http.get(`${BASE_URL}/products/${product.id}`, { headers })
check(detailRes, { 'product detail loaded': (r) => r.status === 200 })
}
})
sleep(Math.random() * 2 + 1)
group('03_add_to_cart', () => {
const res = http.post(`${BASE_URL}/cart/items`, JSON.stringify({
productId: 'prod_001',
quantity: 1
}), {
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${token}`
}
})
check(res, { 'item added to cart': (r) => r.status === 201 })
})
}
SLO Validation
export const options = {
thresholds: {
// SLO: Availability > 99.9%
http_req_failed: ['rate<0.001'],
// SLO: p50 < 100ms, p95 < 500ms, p99 < 1000ms
http_req_duration: [
'p(50)<100',
'p(95)<500',
'p(99)<1000',
],
// SLO per endpoint using tags
'http_req_duration{name:login}': ['p(95)<800'],
'http_req_duration{name:get_products}': ['p(95)<200'],
'http_req_duration{name:checkout}': ['p(95)<2000'],
// SLO: Throughput > 1000 RPS
http_reqs: ['rate>1000'],
}
}
// Tag requests for per-endpoint SLOs
export default function () {
http.get(`${BASE_URL}/products`, { tags: { name: 'get_products' } })
http.post(`${BASE_URL}/auth/login`, payload, { tags: { name: 'login' } })
}
CI Integration
# .github/workflows/load-test.yml
name: Load Test
on:
pull_request:
branches: [main]
jobs:
load-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: grafana/[email protected]
with:
filename: tests/load/smoke.js
env:
BASE_URL: ${{ secrets.STAGING_URL }}
# k6 exits non-zero if thresholds fail → PR check fails
Checklist
- Run smoke test on every PR (fast, catches regressions)
- Load test weekly against staging with production-like data
- Stress test quarterly to find breaking points
- Soak test before major releases (2+ hours, detect memory leaks)
- Thresholds set per endpoint, not just global p95
- Realistic think times between requests (sleep 1-5s)
- Use multiple VU scenarios (not everyone does the same thing)
- Store results in Grafana/InfluxDB for trend analysis
Anti-Patterns
- Testing only happy paths: include error scenarios (404, 429, 500)
- No think time: unrealistic request rate, not how users behave
- Testing against production without traffic control (use staging)
- Single endpoint tests: real users hit multiple endpoints per session
- Ignoring connection time: p95 duration hides DNS/TLS overhead
- Hardcoded test data: VUs sharing same user account causes contention