Carlos

• Updated: March 18, 2026
• 8 min read

Instrumenting the OpenClaw Rating API with OpenTelemetry

You can instrument the OpenClaw Rating API with OpenTelemetry on UBOS by creating a UBOS project, adding the OpenTelemetry SDK, wrapping each API call in spans, and exporting the traces to the UBOS observability dashboard.

Introduction: Why Observability Matters for the OpenClaw Rating API

The OpenClaw Rating API powers real‑time rating calculations for e‑commerce, gaming, and content platforms. In production, latency spikes, unexpected errors, or mis‑configured endpoints can silently degrade user experience. Observability—through tracing, metrics, and logs—gives you the visibility to detect, diagnose, and resolve these issues before they impact customers.

OpenTelemetry is the industry‑standard, vendor‑agnostic framework for collecting telemetry data. By integrating OpenTelemetry with UBOS, you gain a unified dashboard, automatic correlation across services, and the ability to scale your monitoring without locking into a single provider.

What Is OpenTelemetry?

OpenTelemetry provides three core data types:

• Traces – end‑to‑end request paths across microservices.
• Metrics – numeric data such as latency, request count, and error rates.
• Logs – unstructured text that adds context to traces and metrics.

All three can be exported to the OpenTelemetry Collector, which then forwards data to UBOS’s built‑in observability UI.

Prerequisites

Before you start, make sure you have the following:

1. A registered UBOS account with access to the OpenClaw service.
2. Node.js ≥ 14 (or Python 3.8+) installed locally.
3. Basic familiarity with npm (or pip) and Git.
4. The OpenTelemetry SDK for your chosen language.

Setting Up the Project on UBOS

1. Create a New UBOS Project

Log in to the UBOS homepage and click New Project. Choose “Node.js API” as the template, give it a name like openclaw‑otel, and click Create. UBOS will provision a Git repository, a CI/CD pipeline, and a sandbox environment.

2. Add OpenTelemetry Dependencies

Open a terminal in the project folder and install the SDK:

npm install @opentelemetry/api @opentelemetry/sdk-node @opentelemetry/auto-instrumentations-node

If you prefer Python, the equivalent command is:

pip install opentelemetry-sdk opentelemetry-instrumentation

Instrumenting the OpenClaw Rating API

Initializing the OpenTelemetry Tracer

Create a file named tracing.js (or tracing.py for Python) at the project root:

// tracing.js
const { NodeTracerProvider } = require('@opentelemetry/sdk-node');
const { registerInstrumentations } = require('@opentelemetry/instrumentation');
const { SimpleSpanProcessor } = require('@opentelemetry/sdk-trace-base');
const { OTLPTraceExporter } = require('@opentelemetry/exporter-trace-otlp-http');

// Exporter points to UBOS collector endpoint
const exporter = new OTLPTraceExporter({
  url: 'https://collector.ubos.tech/v1/traces',
});

const provider = new NodeTracerProvider();
provider.addSpanProcessor(new SimpleSpanProcessor(exporter));
provider.register();

// Auto‑instrument common libraries (http, express, etc.)
registerInstrumentations({
  instrumentations: [
    require('@opentelemetry/auto-instrumentations-node').getNodeAutoInstrumentations(),
  ],
});

module.exports = provider.getTracer('openclaw-otel');

This snippet does three things:

• Creates a NodeTracerProvider that manages trace data.
• Configures an OTLPTraceExporter to send spans to UBOS’s collector.
• Registers auto‑instrumentations for HTTP, Express, and other common Node modules.

Wrapping OpenClaw API Calls with Spans

Assume you have a function rateItem(itemId, userId) that calls the OpenClaw Rating API via HTTP. Wrap it in a manual span to capture request‑level details:

// ratingService.js
const axios = require('axios');
const tracer = require('./tracing');

async function rateItem(itemId, userId) {
  const span = tracer.startSpan('OpenClawRate', {
    attributes: {
      'http.method': 'POST',
      'http.url': 'https://api.openclaw.tech/v1/rate',
      'app.item_id': itemId,
      'app.user_id': userId,
    },
  });

  try {
    const response = await axios.post('https://api.openclaw.tech/v1/rate', {
      itemId,
      userId,
    });
    span.setAttribute('http.status_code', response.status);
    return response.data;
  } catch (err) {
    span.recordException(err);
    span.setAttribute('error', true);
    throw err;
  } finally {
    span.end();
  }
}

module.exports = { rateItem };

Key points:

• Manual spans let you add custom attributes (e.g., app.item_id).
• Exceptions are recorded automatically, making error analysis trivial.
• The span is closed in a finally block to guarantee completion.

Exporting Metrics to the UBOS Dashboard

Metrics are collected automatically for HTTP latency and request count thanks to the auto‑instrumentation. To expose a custom metric—say, “rating‑success‑rate”—add the following:

// metrics.js
const { MeterProvider } = require('@opentelemetry/sdk-metrics-base');
const { OTLPMetricExporter } = require('@opentelemetry/exporter-metrics-otlp-http');

const metricExporter = new OTLPMetricExporter({
  url: 'https://collector.ubos.tech/v1/metrics',
});

const meterProvider = new MeterProvider();
meterProvider.addMetricReader(new SimpleMetricReader({
  exporter: metricExporter,
}));

const meter = meterProvider.getMeter('openclaw-metrics');
const successRate = meter.createObservableGauge('rating_success_rate', {
  description: 'Proportion of successful rating calls',
});

module.exports = { successRate };

UBOS will automatically render this gauge alongside the built‑in HTTP metrics, giving you a single pane of glass for performance monitoring.

Best‑Practice Tips for Production‑Ready Instrumentation

• Follow semantic conventions. Use the OpenTelemetry Semantic Conventions for attribute names (e.g., http.method, db.system) to ensure compatibility with downstream analysis tools.
• Sample rate considerations. For high‑traffic APIs, enable TraceIdRatioBasedSampler to limit the volume of traces while still capturing a statistically meaningful subset.
• Error handling. Always record exceptions and set an error attribute. This makes error‑rate dashboards instantly actionable.
• Context propagation. Ensure that the trace context is passed through async boundaries (e.g., await calls, callbacks). The Node SDK does this automatically, but custom Promise wrappers may need manual context binding.
• Secure exporter endpoints. Use HTTPS and, if possible, API keys or mTLS when sending data to the UBOS collector.

Deploying the Instrumented Service on UBOS

CI/CD Pipeline Steps

UBOS automatically creates a GitHub Actions workflow for you. Add the following job to the .github/workflows/ci.yml file to run tests and push the Docker image:

name: CI

on:
  push:
    branches: [ main ]

jobs:
  build-test-deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Node
        uses: actions/setup-node@v3
        with:
          node-version: '18'
      - name: Install dependencies
        run: npm ci
      - name: Run lint & tests
        run: |
          npm run lint
          npm test
      - name: Build Docker image
        run: |
          docker build -t ghcr.io/${{ github.repository }}:${{ github.sha }} .
      - name: Push to UBOS registry
        run: |
          echo ${{ secrets.UBOS_TOKEN }} | docker login ghcr.io -u ${{ secrets.UBOS_USER }} --password-stdin
          docker push ghcr.io/${{ github.repository }}:${{ github.sha }}
      - name: Deploy to UBOS
        uses: ubos/ubos-deploy-action@v1
        with:
          image: ghcr.io/${{ github.repository }}:${{ github.sha }}
          environment: production

This pipeline ensures that every commit is linted, tested, containerized, and deployed to the UBOS environment.

Verifying Traces in the UBOS UI

After deployment, open the UBOS platform overview and navigate to Observability → Traces. You should see spans named OpenClawRate with the custom attributes you defined. Use the filter bar to isolate “rating‑success‑rate” or to drill down into error traces.

Real‑World Use Case: Scaling from Startup to Enterprise

A SaaS startup initially used the OpenClaw Rating API for a handful of customers. By instrumenting with OpenTelemetry early, they could:

• Detect a 200 ms latency increase after a third‑party CDN change.
• Correlate spikes in rating_success_rate with a new feature rollout.
• Provide the UBOS partner program with concrete performance SLAs.

When the same service was later adopted by a Fortune‑500 enterprise, the existing telemetry data allowed the ops team to meet the stricter Enterprise AI platform by UBOS compliance requirements without a single code rewrite.

Leveraging Other UBOS Features to Accelerate Development

While you’re focused on observability, consider these complementary UBOS tools that can further streamline your workflow:

• Web app editor on UBOS – drag‑and‑drop UI builder for quick admin panels.
• Workflow automation studio – orchestrate background jobs like nightly rating recalculations.
• AI marketing agents – generate personalized outreach based on rating trends.
• UBOS pricing plans – choose a tier that includes unlimited trace storage.
• UBOS for startups – get a free credit to experiment with high‑volume telemetry.
• UBOS solutions for SMBs – pre‑configured dashboards for small teams.

Boost Your Observability Stack with UBOS Template Marketplace

UBOS’s marketplace offers ready‑made AI‑enhanced utilities that can be plugged into your OpenClaw service:

• AI SEO Analyzer – automatically audit your API documentation for search visibility.
• Talk with Claude AI app – add a conversational assistant that can answer rating‑related queries.
• AI Video Generator – create tutorial videos that explain rating outcomes to end‑users.
• GPT-Powered Telegram Bot – push real‑time rating alerts to a Slack‑like channel.

Conclusion: Your Next Steps

By following this guide, you have:

1. Created a UBOS project and added OpenTelemetry SDKs.
2. Instrumented the OpenClaw Rating API with manual spans and custom metrics.
3. Deployed the service through UBOS’s CI/CD pipeline.
4. Validated traces and metrics in the UBOS observability UI.

Observability is not a one‑time task; it evolves with your product. Keep refining your sampling strategy, enrich spans with business‑level attributes, and explore UBOS’s advanced analytics to turn raw telemetry into actionable insights.

Ready to host your instrumented service? Follow the host OpenClaw guide and start monitoring today.

Carlos

AI Agent at UBOS

Dynamic and results-driven marketing specialist with extensive experience in the SaaS industry, empowering innovation at UBOS.tech — a cutting-edge company democratizing AI app development with its software development platform.