Carlos

• Updated: March 18, 2026
• 6 min read

Building a Unified Grafana Dashboard for OpenClaw Traces, Metrics, and Logs

You can build a single Grafana dashboard that correlates OpenClaw traces, metrics, and logs by configuring Grafana Tempo and Loki as data sources, exposing OpenClaw’s telemetry, and then designing panels that share variables and templating for seamless cross‑correlation.

1. Introduction

The current AI‑agent hype has developers racing to embed intelligent observability into their stacks. UBOS homepage showcases how AI agents like OpenClaw can automatically surface performance anomalies, security incidents, and business‑level insights.

OpenClaw started as a niche tracing library for micro‑services, but after a strategic re‑branding effort—driven by community feedback and the desire to align with the broader AI‑agent ecosystem—it adopted the name OpenClaw. The transition story is documented in the host OpenClaw on UBOS page, where you’ll also find deployment options.

Alongside OpenClaw, Moltbook emerged as a companion knowledge‑base that stores model prompts, versioned datasets, and evaluation metrics. Together they form a powerful observability‑AI duo that can be visualized in Grafana.

2. Prerequisites

Before diving into the dashboard, ensure you have the following tools installed and configured:

• Grafana ≥ 9.0 (Docker or native install)
• Grafana Tempo (for distributed tracing)
• Grafana Loki (for log aggregation)
• OpenClaw agent (compatible with your services)
• Docker‑Compose (optional but recommended for local labs)

All components can be orchestrated via the UBOS platform overview, which provides pre‑built containers and CI/CD pipelines.

2.1 Environment Setup

Use the following docker‑compose.yml snippet to spin up Grafana, Tempo, and Loki together:

version: '3.8'
services:
  grafana:
    image: grafana/grafana:9.5.2
    ports:
      - "3000:3000"
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=admin
    volumes:
      - ./grafana:/var/lib/grafana

  tempo:
    image: grafana/tempo:2.2.1
    ports:
      - "3200:3200"
    command: ["-config.file=/etc/tempo.yaml"]
    volumes:
      - ./tempo:/etc

  loki:
    image: grafana/loki:2.8.2
    ports:
      - "3100:3100"
    command: ["-config.file=/etc/loki/local-config.yaml"]
    volumes:
      - ./loki:/etc/loki

After saving the file, run docker‑compose up -d. Grafana will be reachable at http://localhost:3000.

3. Setting up OpenClaw

3.1 Installation Steps

OpenClaw can be added to any Java, Node.js, or Python service via its SDK. Below is a quick Node.js example:

// Install the OpenClaw SDK
npm install @openclaw/sdk

// Initialize the agent
const { OpenClaw } = require('@openclaw/sdk');
const oc = new OpenClaw({
  serviceName: 'order‑service',
  tempoEndpoint: 'http://localhost:3200/api/traces',
  lokiEndpoint: 'http://localhost:3100/loki/api/v1/push',
  enableMetrics: true
});

// Wrap an async function
async function createOrder(order) {
  const span = oc.startSpan('createOrder');
  try {
    // Business logic here
    await db.save(order);
    span.setStatus('OK');
  } catch (err) {
    span.setStatus('ERROR');
    throw err;
  } finally {
    span.end();
  }
}

For Python and Java, refer to the OpenAI ChatGPT integration page, which shares similar initialization patterns.

3.2 Configuring Traces, Metrics, and Logs

OpenClaw automatically emits:

• Traces – Sent to Tempo via OTLP over HTTP.
• Metrics – Exported in Prometheus format; scrape with prometheus.yml.
• Logs – Pushed to Loki in JSON format.

Example prometheus.yml snippet for metrics:

scrape_configs:
  - job_name: 'openclaw-metrics'
    static_configs:
      - targets: ['localhost:9100']

4. Configuring Grafana Tempo and Loki

4.1 Adding Data Sources

Log in to Grafana (admin / admin) and navigate to Configuration → Data Sources → Add data source. Choose Tempo and fill in:

• URL: http://tempo:3200
• Trace to logs correlation: trace_id

Repeat the process for Loki with URL http://loki:3100. Enable the “Search” and “Explore” features for fast log queries.

4.2 Connecting to OpenClaw

OpenClaw’s telemetry endpoints are already pointing to the containers defined in docker‑compose.yml. Verify connectivity by opening Grafana’s Explore panel, selecting the Tempo data source, and searching for a recent trace ID (e.g., trace_id=12345).

If you encounter CORS issues, add the following to tempo.yaml:

server:
  http_listen_port: 3200
  cors_allowed_origins:
    - http://localhost:3000

5. Building the Unified Dashboard

5.1 Creating Panels for Traces, Metrics, and Logs

Start a new dashboard (+ → Dashboard → Add new panel) and follow these steps:

1. Trace Panel: Choose the Tempo data source, set the query to {trace_id="$trace"}, and enable the “Trace to logs” toggle.
2. Metrics Panel: Switch to the Prometheus data source, use a query like rate(openclaw_requests_total[1m]), and apply the $service variable.
3. Log Panel: Select Loki, query {trace_id="$trace"}, and enable “Live tail” for real‑time debugging.

Below is a screenshot of the three panels aligned side‑by‑side (placeholder image):

5.2 Correlating Data Across Panels

Grafana’s templating engine lets you propagate a single $trace variable across all panels. Create a Dashboard variable:

• Name: trace
• Type: Query
• Data source: Tempo
• Query: label_values(trace_id)

Now, selecting a trace ID from the dropdown instantly updates the trace, metric, and log panels, giving you a holistic view of the request lifecycle.

5.3 Using Variables and Templating for Multi‑Service Views

To monitor multiple micro‑services, add a $service variable that pulls from the service_name label:

label_values(service_name)

Then, adjust each panel’s query to include service_name="$service". This pattern scales effortlessly as you add new services to OpenClaw.

6. Advanced Tips

6.1 Alerting, Annotations, and AI‑Agent Insights

Grafana’s alerting engine can trigger notifications when latency exceeds a threshold. Example rule for a 95th‑percentile latency:

avg_over_time(openclaw_request_latency_seconds{service_name="$service"}[5m]) > 0.5

For AI‑driven insights, integrate the Chroma DB integration to store embeddings of log messages. Then, use a custom Grafana panel that queries the vector store for “similar incidents” and surfaces them alongside the raw logs.

6.2 Performance Tuning

• Enable compression on Loki (compression: gzip) to reduce storage.
• Set trace retention in Tempo to 7 days for production, 30 days for dev.
• Use sharding in Prometheus for high‑cardinality metrics.

7. Publishing and Sharing the Dashboard

Once satisfied, click Share → Snapshot to generate a read‑only URL. For team collaboration, add the dashboard to a Grafana folder with appropriate permissions (e.g., Developers role).

Consider embedding the dashboard in a custom portal built with the Web app editor on UBOS. This allows you to combine the observability view with the AI marketing agents that can automatically generate incident reports.

8. Conclusion

By following the steps above, you now have a single, cohesive Grafana dashboard that correlates OpenClaw traces, metrics, and logs. This unified view empowers developers to pinpoint issues faster, leverage AI‑agent insights, and maintain a scalable observability stack.

Ready to try it yourself? Host OpenClaw on UBOS today and explore the UBOS partner program for additional support.

For more hands‑on templates, check out the UBOS templates for quick start. The AI SEO Analyzer and AI Article Copywriter can help you document your observability findings.

Explore further:

• AI Video Generator – turn dashboard walkthroughs into shareable videos.
• GPT‑Powered Telegram Bot – receive alerts directly in Slack or Telegram.
• Talk with Claude AI app – ask Claude to explain a trace in natural language.
• AI Chatbot template – embed a help‑desk bot into your monitoring portal.
• AI Email Marketing – automatically email post‑mortem reports.

“Observability is no longer a passive data dump; with AI agents like OpenClaw, it becomes an active partner that predicts failures before they happen.” – UBOS Engineering Lead

Stay tuned for our next guide on integrating ElevenLabs AI voice integration to add spoken alerts to your Grafana dashboards.

For the original announcement, see the original news article.

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.