open-webui-docs/docs/getting-started/advanced-topics/observability.md

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7	📊 Observability & OpenTelemetry

📊 Observability with OpenTelemetry

Open WebUI (v0.4.0+) supports distributed tracing and metrics export via the OpenTelemetry (OTel) protocol (OTLP). This enables integration with monitoring systems like Grafana LGTM Stack, Jaeger, Tempo, and Prometheus to monitor request flows, database/Redis queries, response times, and more in real-time.

🚀 Quick Start with Docker Compose

The fastest way to get started with observability is using the pre-configured Docker Compose setup:

# Minimal setup: WebUI + Grafana LGTM all-in-one
docker compose -f docker-compose.otel.yaml up -d

The docker-compose.otel.yaml file starts the following services:

Service	Port	Description
grafana/otel-lgtm	3000 (UI), 4317 (OTLP gRPC), 4318 (OTLP HTTP)	Loki + Grafana + Tempo + Mimir all-in-one
open-webui	8080 → 8080	WebUI with OTEL environment variables configured

After startup, visit http://localhost:3000 and log in with admin / admin to access the Grafana dashboard.

⚙️ Environment Variables

Configure OpenTelemetry using these environment variables:

Variable	Default	Description
ENABLE_OTEL	false	Set to true to enable trace export
OTEL_EXPORTER_OTLP_ENDPOINT	http://localhost:4317	OTLP gRPC/HTTP Collector URL
OTEL_EXPORTER_OTLP_INSECURE	true	Disable TLS (for local testing)
OTEL_SERVICE_NAME	open-webui	Service name tag in resource attributes
OTEL_BASIC_AUTH_USERNAME / OTEL_BASIC_AUTH_PASSWORD	(empty)	Basic Auth credentials for Collector if required
ENABLE_OTEL_METRICS	true	Enable FastAPI HTTP metrics export

You can override these in your .env file or docker-compose.*.yaml configuration.

📊 Data Collection

Distributed Tracing

The utils/telemetry/instrumentors.py module automatically instruments the following libraries:

• FastAPI (request routes) · SQLAlchemy · Redis · External calls via requests / httpx / aiohttp
• Span attributes include:
  • db.instance, db.statement, redis.args
  • http.url, http.method, http.status_code
  • Error details: error.message, error.kind when exceptions occur

Open WebUI creates worker threads only when needed, minimizing overhead while providing efficient trace export.

Metrics Collection

The utils/telemetry/metrics.py module exports the following metrics:

Instrument	Type	Unit	Labels
http.server.requests	Counter	1	http.method, http.route, http.status_code
http.server.duration	Histogram	ms	Same as above

Metrics are pushed to the Collector (OTLP) every 10 seconds and can be visualized in Prometheus → Grafana.

📈 Grafana Dashboard Setup

The example LGTM image has pre-configured data source UIDs: tempo, prometheus, and loki.

Importing Dashboard Configuration

1. Dashboards → Import → Upload JSON
2. Paste the provided JSON configuration (docs/dashboards/ollama.json) → Import
3. An "Ollama" dashboard will be created in the Open WebUI folder

For persistent dashboard provisioning, mount the provisioning directories:

grafana:
  volumes:
    - ./grafana/dashboards:/etc/grafana/dashboards:ro
    - ./grafana/provisioning/dashboards:/etc/grafana/provisioning/dashboards:ro

Exploring Metrics with Prometheus

You can explore and query metrics directly using Grafana's Explore feature:

This allows you to:

• Run custom PromQL queries to analyze API call patterns
• Monitor request rates, error rates, and response times
• Create custom visualizations for specific metrics

🔧 Custom Collector Setup

If you're running your own OpenTelemetry Collector instead of the provided docker-compose.otel.yaml:

# Set your collector endpoint
export OTEL_EXPORTER_OTLP_ENDPOINT=http://your-collector:4317
export ENABLE_OTEL=true

# Start Open WebUI
docker run -d --name open-webui \
  -p 8080:8080 \
  -e ENABLE_OTEL=true \
  -e OTEL_EXPORTER_OTLP_ENDPOINT=http://your-collector:4317 \
  -v open-webui:/app/backend/data \
  ghcr.io/open-webui/open-webui:main

🚨 Troubleshooting

Common Issues

Traces not appearing in Grafana:

• Verify ENABLE_OTEL=true is set
• Check collector connectivity: curl http://localhost:4317
• Review Open WebUI logs for OTLP export errors

High overhead:

• Reduce sampling rate using OTEL_TRACES_SAMPLER_ARG
• Disable metrics with ENABLE_OTEL_METRICS=false if not needed

Authentication issues:

• Set OTEL_BASIC_AUTH_USERNAME and OTEL_BASIC_AUTH_PASSWORD for authenticated collectors
• Verify TLS settings with OTEL_EXPORTER_OTLP_INSECURE

🌟 Best Practices

1. Start Simple: Use the provided docker-compose.otel.yaml for initial setup
2. Monitor Resource Usage: Track CPU and memory impact of telemetry
3. Adjust Sampling: Reduce sampling in high-traffic production environments
4. Custom Dashboards: Create application-specific dashboards for your use cases
5. Alert Setup: Configure alerts for error rates and response time thresholds

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