Distributed Tracing with Tempo #

Overview #

Dynamo supports OpenTelemetry-based distributed tracing for visualizing request flows across Frontend and Worker components. Traces are exported to Tempo via OTLP (OpenTelemetry Protocol) and visualized in Grafana.

Requirements: Set DYN_LOGGING_JSONL=true and OTEL_EXPORT_ENABLED=true to export traces to Tempo.

This guide covers single GPU demo setup using Docker Compose. For Kubernetes deployments, see Kubernetes Deployment.

Note: This section has overlap with Logging of OpenTelemetry Tracing since OpenTelemetry has aspects of both logging and tracing. The tracing approach documented here is for persistent trace visualization and analysis. For short debugging sessions examining trace context directly in logs, see the Logging guide.

Environment Variables #

Getting Started Quickly #

1. Start Observability Stack #

Start the observability stack (Prometheus, Grafana, Tempo, exporters). See Observability Getting Started for instructions.

2. Set Environment Variables #

Configure Dynamo components to export traces:

# Enable JSONL logging and tracing export DYN_LOGGING_JSONL=true export OTEL_EXPORT_ENABLED=true export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=http://localhost:4317

Copy to clipboard

3. Start Dynamo Components (Single GPU) #

For a simple single-GPU deployment, start the frontend and a single vLLM worker:

# Start the frontend with tracing enabled (default port 8000, override with --http-port or DYN_HTTP_PORT env var) export OTEL_SERVICE_NAME=dynamo-frontend python -m dynamo.frontend --router-mode kv & # Start a single vLLM worker (aggregated prefill and decode) export OTEL_SERVICE_NAME=dynamo-worker-vllm python -m dynamo.vllm --model Qwen/Qwen3-0.6B --enforce-eager \ --otlp-traces-endpoint="$OTEL_EXPORTER_OTLP_TRACES_ENDPOINT" & wait

Copy to clipboard

This runs both prefill and decode on the same GPU, providing a simpler setup for testing tracing.

Alternative: Disaggregated Deployment (2 GPUs) #

Run the vLLM disaggregated script with tracing enabled:

# Navigate to vLLM launch directory cd examples/backends/vllm/launch # Export tracing env vars, then run the disaggregated deployment script. ./disagg.sh

Copy to clipboard

Note:disagg.sh sets additional per-worker port environment variables (e.g., DYN_VLLM_KV_EVENT_PORT, VLLM_NIXL_SIDE_CHANNEL_PORT) to avoid ZMQ “Address already in use” conflicts when multiple workers run on the same host. If you run the components manually, make sure you mirror those port settings.

#!/bin/bash set -e trap 'echo Cleaning up...; kill 0' EXIT # Enable tracing export DYN_LOGGING_JSONL=true export OTEL_EXPORT_ENABLED=true export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=http://localhost:4317 # Run frontend (default port 8000, override with --http-port or DYN_HTTP_PORT env var) export OTEL_SERVICE_NAME=dynamo-frontend python -m dynamo.frontend --router-mode kv & # Run decode/ingress worker (make sure to wait for start up) export OTEL_SERVICE_NAME=dynamo-worker-decode DYN_SYSTEM_PORT=8081 CUDA_VISIBLE_DEVICES=0 python3 -m dynamo.vllm \ --model Qwen/Qwen3-0.6B \ --enforce-eager \ --otlp-traces-endpoint="$OTEL_EXPORTER_OTLP_TRACES_ENDPOINT" & # Run prefill worker, make sure to wait for start up export OTEL_SERVICE_NAME=dynamo-worker-prefill DYN_SYSTEM_PORT=8082 \ DYN_VLLM_KV_EVENT_PORT=20081 \ VLLM_NIXL_SIDE_CHANNEL_PORT=20097 \ CUDA_VISIBLE_DEVICES=1 python3 -m dynamo.vllm \ --model Qwen/Qwen3-0.6B \ --enforce-eager \ --otlp-traces-endpoint="$OTEL_EXPORTER_OTLP_TRACES_ENDPOINT" \ --is-prefill-worker &

Copy to clipboard

For disaggregated deployments, this separates prefill and decode onto different GPUs for better resource utilization.

4. Generate Traces #

Send requests to the frontend to generate traces (works for both aggregated and disaggregated deployments). Note the x-request-id header, which allows you to easily search for and correlate this specific trace in Grafana:

curl -H 'Content-Type: application/json' \ -H 'x-request-id: test-trace-001' \ -d '{ "model": "Qwen/Qwen3-0.6B", "max_completion_tokens": 100, "messages": [\ {"role": "user", "content": "What is the capital of France?"}\ ] }' \ http://localhost:8000/v1/chat/completions

Copy to clipboard

5. View Traces in Grafana Tempo #

1. Open Grafana at http://localhost:3000

2. Login with username dynamo and password dynamo

3. Navigate to Explore (compass icon in the left sidebar)

4. Select Tempo as the data source (should be selected by default)

5. In the query type, select “Search” (not TraceQL, not Service Graph)

6. Use the Search tab to find traces:

   • Search by Service Name (e.g., dynamo-frontend)

   • Search by Span Name (e.g., http-request, handle_payload)

   • Search by Tags (e.g., x_request_id=test-trace-001)

7. Click on a trace to view the detailed flame graph

Example Trace View #

Below is an example of what a trace looks like in Grafana Tempo:

6. Stop Services #

When done, stop the observability stack. See Observability Getting Started for Docker Compose commands.

---

Kubernetes Deployment #

For Kubernetes deployments, ensure you have a Tempo instance deployed and accessible (e.g., http://tempo.observability.svc.cluster.local:4317).

Modify DynamoGraphDeployment for Tracing #

Add common tracing environment variables at the top level and service-specific names in each component in your DynamoGraphDeployment (e.g., examples/backends/vllm/deploy/disagg.yaml):

apiVersion: nvidia.com/v1alpha1 kind: DynamoGraphDeployment metadata: name: vllm-disagg spec: # Common environment variables for all services env: - name: DYN_LOGGING_JSONL value: "true" - name: OTEL_EXPORT_ENABLED value: "true" - name: OTEL_EXPORTER_OTLP_TRACES_ENDPOINT value: "http://tempo.observability.svc.cluster.local:4317" services: Frontend: # ... existing configuration ... extraPodSpec: mainContainer: # ... existing configuration ... env: - name: OTEL_SERVICE_NAME value: "dynamo-frontend" VllmDecodeWorker: # ... existing configuration ... extraPodSpec: mainContainer: # ... existing configuration ... env: - name: OTEL_SERVICE_NAME value: "dynamo-worker-decode" VllmPrefillWorker: # ... existing configuration ... extraPodSpec: mainContainer: # ... existing configuration ... env: - name: OTEL_SERVICE_NAME value: "dynamo-worker-prefill"

Copy to clipboard

Apply the updated DynamoGraphDeployment:

kubectl apply -f examples/backends/vllm/deploy/disagg.yaml

Copy to clipboard

Traces will now be exported to Tempo and can be viewed in Grafana.

Related Articles

• Metrics Visualization with Prometheus and Grafana — NVIDIA Dynamo Documentation
• Log Aggregation in Dynamo on Kubernetes — NVIDIA Dynamo Documentation
• Dynamo Observability — NVIDIA Dynamo Documentation