To send OpenTelemetry metrics and traces generated by OpenLIT from your AI Application to Dash0, follow the below steps.
1. Dash0 Setup
Prerequisites: You’ll need a Dash0 account and authorization token. Sign up at dash0.com for a 14-days free trial, if you don’t have an account yet. Get your Dash0 credentials
- Log into your Dash0 account
- Navigate to Organization Settings → Auth Tokens
- Create a new token or copy an existing one
- Note your Dash0 OTLP ingestion endpoint (e.g.,
ingress.eu-west-1.aws.dash0.com:4318 for HTTP or :4317 for gRPC)
- Your token will be in the format
Bearer auth_xxxxx...
You can send telemetry directly to Dash0’s OTLP endpoint, or route it through an OpenTelemetry Collector for additional processing and filtering.
2. Instrument your application
For direct integration into your Python applications: Function Arguments
Environment Variables
import openlit
openlit.init(
otlp_endpoint="https://ingress.eu-west-1.aws.dash0.com:4318",
otlp_headers={"Authorization": "Bearer auth_your_token_here"}
)
ingress.eu-west-1.aws.dash0.com:4318 with your Dash0 ingestion endpointauth_your_token_here with your Dash0 authorization token
import openlit
openlit.init()
export OTEL_EXPORTER_OTLP_ENDPOINT="https://ingress.eu-west-1.aws.dash0.com:4318"
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer auth_your_token_here"
ingress.eu-west-1.aws.dash0.com:4318 with your Dash0 ingestion endpointauth_your_token_here with your Dash0 authorization token
For zero-code auto-instrumentation via command line: CLI Arguments
Environment Variables
# Using CLI arguments
openlit-instrument \
--otlp-endpoint "https://ingress.eu-west-1.aws.dash0.com:4318" \
--otlp-headers "Authorization=Bearer auth_your_token_here" \
--service-name "my-ai-service" \
--deployment-environment "production" \
python app.py
ingress.eu-west-1.aws.dash0.com:4318 with your Dash0 ingestion endpointauth_your_token_here with your Dash0 authorization token
# Set environment variables (takes precedence over CLI args)
export OTEL_EXPORTER_OTLP_ENDPOINT="https://ingress.eu-west-1.aws.dash0.com:4318"
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer auth_your_token_here"
export OTEL_SERVICE_NAME="my-ai-service"
export OTEL_DEPLOYMENT_ENVIRONMENT="production"
# Run your application
openlit-instrument python app.py
ingress.eu-west-1.aws.dash0.com:4318 with your Dash0 ingestion endpointauth_your_token_here with your Dash0 authorization token
3. View your telemetry in Dash0
Once your AI application starts sending telemetry data, you can explore it in Dash0:
- Traces: Navigate to Traces to view your AI application traces with LLM calls, prompts, completions, and token usage
- Services: Check Services to monitor your AI service performance, error rates, and latency
- Metrics: Explore metrics for token usage, costs, and AI-specific KPIs
- Dashboards: Create custom dashboards to track token consumption, model performance, and business metrics
- Query: Use PromQL-based queries to filter and analyze telemetry by model, token usage, or errors
Your OpenLIT-instrumented AI applications will appear automatically in Dash0 with comprehensive observability including LLM costs, token usage, model performance, and GPU metrics. 
