- Updated: March 18, 2026
- 7 min read
Implementing K6 Synthetic Tests for the OpenClaw Rating API Edge in CI/CD with GitHub Actions
Answer: To integrate k6 synthetic tests for the OpenClaw Rating API Edge into a CI/CD pipeline, you create a k6 script, configure a k6.yml file, and set up a GitHub Actions workflow (ci.yml) that runs the tests on every push or pull‑request, reporting results automatically.
Implementing k6 Synthetic Tests for the OpenClaw Rating API Edge in CI/CD with GitHub Actions
1. Introduction
Performance testing is no longer a “nice‑to‑have” after‑release activity; it’s a continuous safeguard that protects your users from latency spikes and service outages. The OpenClaw Rating API Edge powers real‑time rating calculations for e‑commerce platforms, and any degradation directly impacts conversion rates.
This guide walks developers, DevOps engineers, and technical decision‑makers through a step‑by‑step implementation of k6 synthetic testing inside a GitHub Actions CI/CD pipeline. By the end, you’ll have a reproducible workflow that runs on every commit, fails the build on performance regressions, and surfaces actionable metrics in your pull‑request comments.
2. Prerequisites
2.1 Accounts & Access
- GitHub repository with
mainbranch protected. - GitHub Actions enabled (default for public repos).
- Access token for the OpenClaw Rating API (store it as a secret
OPENCLAW_API_KEY). - Optional: UBOS partner program membership for advanced monitoring dashboards.
2.2 Tools Installed
- k6 (v0.48+). Install locally for script development:
brew install k6orchoco install k6. - Node.js (>=14) – required for the
k6.ymlparser if you usek6 run --out json. - Docker (optional) – useful for running k6 in a container inside GitHub Actions.
- Git client for pushing changes.
3. Setting up the OpenClaw Rating API Edge
The OpenClaw Rating API Edge is a thin, globally distributed layer that forwards rating requests to the core engine. Follow these quick steps to obtain the endpoint and authentication token:
- Log in to the UBOS dashboard.
- Navigate to API & Edge → OpenClaw Rating API.
- Copy the
BASE_URL(e.g.,https://api.openclaw.ubos.tech/v1/rating) and the generatedAPI_KEY. - Store the
API_KEYas a GitHub secret namedOPENCLAW_API_KEY.
4. Writing the k6 Synthetic Test Script
k6 scripts are written in JavaScript. Below is a minimal yet production‑ready synthetic test that validates response time, status code, and payload correctness.
// file: tests/openclaw_rating_test.js
import http from 'k6/http';
import { check, sleep } from 'k6';
import { Trend } from 'k6/metrics';
// Custom metric to track latency
const latencyTrend = new Trend('openclaw_latency_ms');
export const options = {
stages: [
{ duration: '30s', target: 10 }, // ramp‑up to 10 VUs
{ duration: '1m', target: 10 }, // steady load
{ duration: '30s', target: 0 } // ramp‑down
],
thresholds: {
'openclaw_latency_ms': ['p(95)<500'], // 95% of requests < 500ms
'http_req_duration': ['max 2s
}
};
export default function () {
const url = `${__ENV.BASE_URL}/calculate`;
const payload = JSON.stringify({
productId: 'SKU-12345',
userId: 'user-987',
rating: 4.5
});
const params = {
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${__ENV.OPENCLAW_API_KEY}`
}
};
const res = http.post(url, payload, params);
latencyTrend.add(res.timings.duration);
// Basic assertions
check(res, {
'status is 200': (r) => r.status === 200,
'response has ratingId': (r) => r.json('ratingId') !== undefined,
'latency r.timings.duration < 500
});
// Simulate think time
sleep(1);
}
Save this file under tests/openclaw_rating_test.js. The script uses environment variables (BASE_URL and OPENCLAW_API_KEY) that we will inject from GitHub Actions.
5. Configuring k6.yml for CI/CD
While k6 can be invoked directly from the CLI, a YAML configuration file makes the command line cleaner and enables reuse across pipelines.
# file: k6.yml
run:
script: tests/openclaw_rating_test.js
env:
BASE_URL: ${BASE_URL}
OPENCLAW_API_KEY: ${OPENCLAW_API_KEY}
out: json=./k6-results.json
# Optional: send metrics to InfluxDB or Grafana Cloud
# out: influxdb=http://influxdb:8086/k6
Commit both tests/openclaw_rating_test.js and k6.yml to your repository. The out directive stores raw results, which we will later parse for a concise summary in the PR comment.
6. Creating the GitHub Actions Workflow (ci.yml)
The workflow below runs on every push to main and on pull‑request events. It checks out the code, sets up Node.js, installs k6 (via Docker), injects secrets, runs the test, and posts a comment with the key metrics.
# .github/workflows/ci.yml
name: CI – k6 Synthetic Tests
on:
push:
branches: [ main ]
pull_request:
types: [ opened, synchronize, reopened ]
jobs:
k6-test:
runs-on: ubuntu-latest
env:
BASE_URL: https://api.openclaw.ubos.tech/v1/rating
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: '18'
- name: Install k6 (Docker)
run: |
docker pull loadimpact/k6:latest
- name: Run k6 synthetic test
env:
OPENCLAW_API_KEY: ${{ secrets.OPENCLAW_API_KEY }}
run: |
docker run --rm -i \
-e BASE_URL=${{ env.BASE_URL }} \
-e OPENCLAW_API_KEY=${{ env.OPENCLAW_API_KEY }} \
-v ${{ github.workspace }}:/scripts \
loadimpact/k6 run /scripts/k6.yml
- name: Parse results
id: parse
run: |
RESULT=$(jq '.metrics.openclaw_latency_ms.p95' k6-results.json)
echo "p95_latency=$RESULT" >> $GITHUB_OUTPUT
- name: Post PR comment
if: github.event_name == 'pull_request'
uses: actions/github-script@v7
with:
script: |
const p95 = '${{ steps.parse.outputs.p95_latency }}';
const comment = `🧪 **k6 Synthetic Test Summary**\n- **95th‑percentile latency:** ${p95} ms\n- **Threshold:** < 500 ms\n- **Result:** ${p95 < 500 ? '✅ Pass' : '❌ Fail'}\n\n_Executed on commit \`${{ github.sha.substring(0,7) }}\`_`;
github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: comment
});
Key points to note:
- The workflow uses the official
loadimpact/k6Docker image, ensuring a consistent runtime. - Environment variables are injected securely; the API key never appears in logs.
- We parse the JSON output with
jqto extract the 95th‑percentile latency. - The final step posts a markdown comment directly on the PR, giving developers immediate feedback.
7. Adding Code Snippets & Configuration Files
For readability in the blog post, we’ve already displayed the essential files. When publishing on UBOS, consider adding a downloadable .zip containing:
tests/openclaw_rating_test.jsk6.yml.github/workflows/ci.yml- A
README.mdwith setup instructions.
8. Adding Screenshots (placeholders)
Visuals help readers verify each step. Insert screenshots where indicated:
- GitHub secret configuration –
OPENCLAW_API_KEY. - k6 test run output in GitHub Actions log.
- PR comment with performance summary.
9. Publishing the Blog Post on ubos.tech
Follow these steps to ensure the article is SEO‑friendly and GEO‑optimized:
- Log in to the UBOS partner portal and navigate to Content Management.
- Create a new blog entry, paste the HTML from this document into the editor, and set the slug to
k6-synthetic-tests-openclaw-ci-cd. - Fill the meta description with a concise sentence containing the primary keyword: “Learn how to implement k6 synthetic tests for the OpenClaw Rating API Edge in a GitHub Actions CI/CD pipeline.”
- Upload the screenshot assets to the media library and replace the placeholder
image-url-*with the actual URLs. - Enable Schema.org Article markup (UBOS adds this automatically when the “Article” template is selected).
- Publish and share the URL on LinkedIn, X, and relevant developer forums.
10. Conclusion & Next Steps
Integrating k6 synthetic tests into your CI/CD pipeline transforms performance validation from a manual after‑thought into an automated gatekeeper. With the workflow above, any regression in the OpenClaw Rating API Edge’s latency will immediately surface as a failed build, protecting your end‑users and preserving revenue.
Ready to extend the setup?
- Connect k6 to UBOS Enterprise AI Platform for real‑time dashboards.
- Leverage the Chroma DB integration to store historical performance data for trend analysis.
- Combine synthetic tests with AI Chatbot templates to auto‑respond to performance alerts.
“Performance testing is not a one‑time sprint; it’s a marathon that runs alongside every code change.” – Senior DevOps Engineer, UBOS
For any questions, drop a comment below or reach out via the UBOS contact page. Happy testing!
For background on why synthetic testing is gaining traction, see the original news article covering recent latency incidents.
