OpenLIT

Documentation Index

Fetch the complete documentation index at: https://docs.openlit.io/llms.txt

Use this file to discover all available pages before exploring further.

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1. Get your Credentials

• Kubernetes cluster: http://openlit.openlit.svc.cluster.local:4318
• Local development: http://localhost:4318 (using port-forward)
• External/Ingress: Your configured external endpoint

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2. Instrument your application

import openlit

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

import openlit

openlit.init()

export OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4318"
export OTEL_SERVICE_NAME="my-ai-service"
export OTEL_DEPLOYMENT_ENVIRONMENT="production"

# Using CLI arguments
openlit-instrument \
  --otlp-endpoint "YOUR_OPENLIT_PLATFORM_ENDPOINT" \
  --service-name "my-ai-service" \
  --deployment-environment "production" \
  python app.py

# Set environment variables (takes precedence over CLI args)
export OTEL_EXPORTER_OTLP_ENDPOINT="YOUR_OPENLIT_PLATFORM_ENDPOINT"
export OTEL_SERVICE_NAME="my-ai-service"
export OTEL_DEPLOYMENT_ENVIRONMENT="production"

# Run your application
openlit-instrument python app.py

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3. Access OpenLIT Platform Dashboard

# Get the external service details
kubectl get svc -n openlit openlit

# For local access via port-forwarding:
kubectl port-forward -n openlit svc/openlit 3000:3000
# Then visit: http://localhost:3000

1. LLM Observability Dashboard: Comprehensive view of your AI applications including:
   • Real-time Metrics: Request rates, latency, and error rates
   • Cost Tracking: Token usage and cost breakdown by model and application
   • Performance Analytics: Response times, throughput, and model performance
   • Trace Visualization: Detailed execution flow with full request/response context
2. Vector Database Analytics: Monitor your vector database operations and performance
3. GPU Monitoring: Track GPU utilization and performance metrics (if enabled)
4. Custom Dashboards: Create tailored views for your specific monitoring needs