1. Get your Credentials
If you haven’t deployed the OpenLIT Platform yet, follow the Installation Guide to set it up. Common OpenLIT Platform endpoints:- Kubernetes cluster:
http://openlit.openlit.svc.cluster.local:4318
- Local development:
http://localhost:4318
(using port-forward) - External/Ingress: Your configured external endpoint
2. Instrument your application
For direct integration into your Python applications:Replace Refer to the OpenLIT Python SDK repository for more advanced configurations and use cases.
http://localhost:4318
with your OpenLIT Platform endpoint:- Local development:
http://localhost:4318
- Kubernetes cluster:
http://openlit.openlit.svc.cluster.local:4318
- External: Your configured external endpoint
3. Access OpenLIT Platform Dashboard
Once your LLM application is instrumented, you can explore the comprehensive observability data in the OpenLIT Platform: Access the Dashboard:- 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
- Vector Database Analytics: Monitor your vector database operations and performance
- GPU Monitoring: Track GPU utilization and performance metrics (if enabled)
- Custom Dashboards: Create tailored views for your specific monitoring needs