To send OpenTelemetry traces generated by OpenLIT from your AI Application to Murnitur.ai, follow the below steps.

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1. Get your Credentials

  1. Visit Murnitur.ai: Go to Murnitur.ai to create your account
  2. Generate API Key: Navigate to your dashboard and generate your API key
  3. Save your credentials:
    • API Key: Your Murnitur trace token for authentication
    • Endpoint: https://middleware.murnitur.ai
Murnitur.ai is optimized for trace data. The integration automatically disables metrics to focus on trace observability.

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2. Instrument your application

For direct integration into your Python applications:
import openlit

openlit.init(
  otlp_endpoint="https://middleware.murnitur.ai",
  otlp_headers="x-murnix-trace-token=YOUR_MURNITUR_API_KEY",
  disable_metrics=True  # Murnitur focuses on trace data
)
Replace:
  1. YOUR_MURNITUR_API_KEY with your Murnitur API key from Step 1.
Refer to the OpenLIT Python SDK repository for more advanced configurations and use cases.

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3. Visualize in Murnitur.ai

Once your LLM application is instrumented, you can explore the telemetry data in Murnitur.ai:
  1. Navigate to Murnitur.ai: Go to your Murnitur.ai Dashboard
  2. Explore Traces: View your AI application traces including:
    • LLM request traces with detailed timing and execution flow
    • Model performance analytics and latency metrics
    • Request/response data for debugging and optimization
    • Token usage and cost tracking information
    • Complete trace hierarchy showing the full request lifecycle
  3. Trace Analytics: Analyze patterns, performance bottlenecks, and usage trends
  4. Performance Monitoring: Monitor latency, throughput, and error rates
  5. Debugging Tools: Use detailed trace data to debug and optimize your AI applications
Your OpenLIT-instrumented AI applications will appear automatically in Murnitur.ai with comprehensive trace observability focused on LLM performance, execution flow, and detailed debugging capabilities optimized for AI workloads.