- Updated: March 14, 2026
- 3 min read
Observability and Debugging OpenClaw on UBOS: Metrics, Tracing, Logging, and Alerting
# Observability and Debugging OpenClaw on UBOS: Metrics, Tracing, Logging, and Alerting
Operators deploying **OpenClaw** on UBOS need deep visibility into the system to ensure reliability and fast issue resolution. This guide walks through a complete observability stack built on Prometheus, OpenTelemetry, Grafana, centralized logging, and alerting rules.
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## 1. Metrics with Prometheus
1. **Expose OpenClaw metrics** – Enable the `/metrics` endpoint in the OpenClaw configuration. UBOS ships a Prometheus exporter that scrapes this endpoint automatically.
2. **Configure UBOS Prometheus** – Add a scrape job in the `prometheus.yml` located at `/etc/ubos/prometheus`:
yaml
– job_name: ‘openclaw’
static_configs:
– targets: [‘localhost:9090’]
3. **Validate** – Visit `http:///prometheus/targets` and ensure the OpenClaw target is **UP**.
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## 2. Distributed Tracing with OpenTelemetry
1. **Instrument OpenClaw** – Include the OpenTelemetry SDK in the OpenClaw runtime and configure an exporter (e.g., Jaeger or OTLP).
2. **UBOS collector** – UBOS runs an OpenTelemetry Collector that receives traces on port `4317`. Add the collector endpoint to OpenClaw’s config:
{
“otel”: {
“endpoint”: “http://localhost:4317″
}
}
3. **View traces** – Use the built‑in Jaeger UI at `http:///jaeger` to explore request flows across the OpenClaw services.
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## 3. Visualisation with Grafana Dashboards
UBOS provides a pre‑configured Grafana instance. Import the **OpenClaw Observability** dashboard (ID: `12345`) or create a custom one:
– **CPU & Memory** – `node_cpu_seconds_total`, `node_memory_MemAvailable_bytes`
– **OpenClaw request latency** – `histogram_quantile(0.95, sum(rate(openclaw_http_request_duration_seconds_bucket[5m])) by (le))`
– **Error rate** – `rate(openclaw_http_requests_total{status=~”5..”}[5m])`
The dashboard automatically picks up metrics from the Prometheus data source configured by UBOS.
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## 4. Centralised Logging
1. **Log forwarder** – UBOS runs a Fluent Bit agent that tails `/var/log/openclaw/*.log` and forwards logs to an Elasticsearch cluster.
2. **Kibana** – Access logs via Kibana at `http:///kibana`. Create a saved search for `source:openclaw` and add it to a dashboard.
3. **Log enrichment** – Enable JSON logging in OpenClaw to capture structured fields like `request_id`, `user`, and `error_code`.
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## 5. Alerting Rules
Define Prometheus alerting rules in `/etc/ubos/alertmanager/rules.yml`:
yaml
groups:
– name: openclaw-alerts
rules:
– alert: OpenClawHighErrorRate
expr: rate(openclaw_http_requests_total{status=~”5..”}[5m]) > 0.05
for: 2m
labels:
severity: critical
annotations:
summary: “High error rate on OpenClaw”
description: “Error rate > 5% for the last 5 minutes.”
The UBOS Alertmanager routes alerts to Slack, email, or PagerDuty based on severity.
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## 6. One‑click Deployment Reference
For a complete, production‑ready deployment of OpenClaw with the observability stack, follow the official guide: [Host OpenClaw on UBOS](https://ubos.tech/host-openclaw/)
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### Summary
– **Prometheus** scrapes OpenClaw metrics.
– **OpenTelemetry** provides end‑to‑end tracing.
– **Grafana** visualises key performance indicators.
– **Fluent Bit + Elasticsearch** centralises logs.
– **Alertmanager** notifies operators on critical conditions.
With these components in place, operators gain full visibility into OpenClaw’s health and can quickly debug issues, ensuring a reliable service for end users.