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

1. DataDog Agent Setup

INFO

Prerequisites: This guide assumes you have a DataDog Agent already installed and configured with OpenTelemetry support. If you need to install the DataDog Agent, please refer to the DataDog Agent Installation Guide.

2. Instrument your application

SDK

For direct integration into your Python applications:

Function Arguments

import elsai_arms

elsai_arms.init(
  otlp_endpoint="http://localhost:4318"
)

INFO

The DataDog Agent handles authentication and forwarding to DataDog. No API key needed in the application configuration.

Environment Variables

import elsai_arms

elsai_arms.init()

Set these environment variables:

export OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4318"

INFO

The DataDog Agent handles authentication and forwarding to DataDog. No API key needed in the application configuration.

See the ARMS SDK configuration docs for more advanced options.

CLI

For zero-code auto-instrumentation via command line:

CLI Arguments

# Using CLI arguments
elsai-arms-instrument \
  --otlp-endpoint "http://localhost:4318" \
  --service-name "my-ai-service" \
  --deployment-environment "production" \
  python app.py

INFO

The DataDog Agent handles authentication and forwarding to DataDog. No API key needed in the CLI configuration.

Environment Variables

# Set environment variables (takes precedence over CLI args)
export OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4318"
export OTEL_SERVICE_NAME="my-ai-service"
export OTEL_DEPLOYMENT_ENVIRONMENT="production"

# Run your application
elsai-arms-instrument python app.py

INFO

The DataDog Agent handles authentication and forwarding to DataDog. No API key needed in the CLI configuration.

See the ARMS SDK configuration docs for more advanced options.

3. Exploring Telemetry in DataDog

Once your AI application is sending telemetry data to DataDog, you can explore and analyze it using DataDog's powerful observability features:

Software Catalog

View all your AI services and their connections:

• Go to APM → Software Catalog
• Select Map to see how services are connected
• Change Map layout to Cluster or Flow for different views
• Select Catalog view, then click a service for performance summary

Trace Explorer

Explore traces from your AI applications:

• Navigate to Performance → Setup Guidance → View Traces
• Select an indexed span to view full trace details
• View correlated data across tabs:
  • Infrastructure metrics for services with Host Metrics
  • Runtime metrics for implemented services
  • Log entries correlated with traces
  • Span links connected to traces

INFO

After your ARMS-instrumented AI application starts sending data, it may take a few minutes for traces and metrics to appear in DataDog. The built-in telemetry generation will begin automatically once your application processes AI requests.