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

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1. Get your Credentials

  1. Sign in to your Middleware account: Go to Middleware Dashboard
  2. Navigate to API Keys: Go to Settings → API Keys (Direct Link)
  3. Copy your credentials:
    • MW_API_KEY: Your Middleware API key for authentication
    • MW_TARGET: Your Middleware target URL endpoint Save these values - you’ll need them for configuration.

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2. Instrument your application

For direct integration into your Python applications:
import openlit

openlit.init(
  otlp_endpoint="MW_TARGET",
  application_name="YOUR_APPLICATION_NAME",
  otlp_headers={
      "Authorization": "MW_API_KEY",
      "X-Trace-Source": "openlit",
  }
)
Replace:
  1. MW_TARGET with your Middleware target URL from Step 1.
    • Example: https://abcd.middleware.io:443
  2. MW_API_KEY with your Middleware API key from Step 1.
    • Example: dxyxsdojzrgpsvizzzcsvhrwnmzqdsdsd
  3. YOUR_APPLICATION_NAME with your application name.
Refer to the OpenLIT Python SDK repository for more advanced configurations and use cases.

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3. Visualize in Middleware

Once your LLM application is instrumented, you can explore the telemetry data in Middleware:
  1. Navigate to LLM Observability: Go to your Middleware Dashboard and click on LLM Observability in the sidebar
  2. Explore AI Operations: View your AI application traces including:
    • LLM request traces with detailed timing
    • Token usage and cost information
    • Vector database operations
    • Model performance analytics
    • Request/response payloads (if enabled)
  3. Custom Dashboards: Create custom dashboards for your specific LLM metrics
  4. Alerting: Set up alerts for LLM performance anomalies and cost thresholds
  5. Performance Analysis: Analyze latency, throughput, and resource usage patterns
For detailed information on LLM Observability features, consult the Middleware LLM Observability Documentation.