Skip to content

To send OpenTelemetry metrics and traces generated by ARMS from your AI Application to Dash0, follow the below steps.

1. Dash0 Setup ​

INFO

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 ​

  1. Log into your Dash0 account
  2. Navigate to Organization Settings → Auth Tokens
  3. Create a new token or copy an existing one
  4. Note your Dash0 OTLP ingestion endpoint (e.g., ingress.eu-west-1.aws.dash0.com:4318 for HTTP or :4317 for gRPC)
  5. Your token will be in the format Bearer auth_xxxxx...

INFO

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 ​

SDK ​

For direct integration into your Python applications:

Function Arguments ​
python
import elsai_arms

elsai_arms.init(
  otlp_endpoint="https://ingress.eu-west-1.aws.dash0.com:4318",
  otlp_headers={"Authorization": "Bearer auth_your_token_here"}
)

Replace:

  1. ingress.eu-west-1.aws.dash0.com:4318 with your Dash0 ingestion endpoint
  2. auth_your_token_here with your Dash0 authorization token
Environment Variables ​
python
import elsai_arms

elsai_arms.init()

Set these environment variables:

shell
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"

Replace:

  1. ingress.eu-west-1.aws.dash0.com:4318 with your Dash0 ingestion endpoint
  2. auth_your_token_here with your Dash0 authorization token

See the ARMS SDK configuration docs for more advanced options.

CLI ​

For zero-code auto-instrumentation via command line:

CLI Arguments ​
shell
# Using CLI arguments
elsai-arms-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

Replace:

  1. ingress.eu-west-1.aws.dash0.com:4318 with your Dash0 ingestion endpoint
  2. auth_your_token_here with your Dash0 authorization token
Environment Variables ​
shell
# 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
elsai-arms-instrument python app.py

Replace:

  1. ingress.eu-west-1.aws.dash0.com:4318 with your Dash0 ingestion endpoint
  2. auth_your_token_here with your Dash0 authorization token

See the ARMS SDK configuration docs for more advanced options.

3. View your telemetry in Dash0 ​

Once your AI application starts sending telemetry data, you can explore it in Dash0:

  1. Traces: Navigate to Traces to view your AI application traces with LLM calls, prompts, completions, and token usage
  2. Services: Check Services to monitor your AI service performance, error rates, and latency
  3. Metrics: Explore metrics for token usage, costs, and AI-specific KPIs
  4. Dashboards: Create custom dashboards to track token consumption, model performance, and business metrics
  5. Query: Use PromQL-based queries to filter and analyze telemetry by model, token usage, or errors

Your ARMS-instrumented AI applications will appear automatically in Dash0 with comprehensive observability including LLM costs, token usage, model performance, and GPU metrics.

Copyright © 2026 elsai foundry.