OpenLIT is an open-source AI engineering platform that helps teams build, evaluate and observe AI applications across the entire lifecycle from development to production. OpenLIT provides the following OSS tools to support this goal:
  • OpenLIT - Open-source platform for tracing, prompt management, evaluations, and scalable AI observability with dashboards, metrics, logs, and remote collectors.
  • OpenLIT SDKs - OpenTelemetry-native auto-instrumentation to trace LLMs, agents, vector databases and GPUs with zero-code
  • OpenLIT Operator - Kubernetes operator that automatically injects instrumentation into AI applications without requiring code or image changes.
The project proudly follows OpenTelemetry Semantic Conventions for AI observability standards.

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Features

OpenLIT provides distributed tracing capabilities for understanding and debugging AI applications:
  • OpenTelemetry-native SDKs - Automatic instrumentation for LLMs, agents, frameworks, Vector databases, MCP and GPUs.
  • Exceptions Monitoring - Track and debug application errors with detailed stack traces.
  • Universal Compatibility - View traces from any OpenTelemetry-instrumented tool or LLM instrumentation frameworks like OpenInference, OpenLLMetry.

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Getting Started

Choose your path to start building better AI applications with OpenLIT:

Quickstart: LLM Observability

Production-ready AI monitoring setup in 2 simple steps with zero code changes

Deploy OpenLIT

Deployment options for scalable LLM monitoring infrastructure

Create a dashboard

Create custom visualizations with flexible widgets, queries, and real-time AI monitoring

Manage prompts

Version, deploy, and collaborate on prompts with centralized management and tracking
Kubernetes

Running in Kubernetes? Try the OpenLIT Operator

Automatically inject instrumentation into existing workloads without modifying pod specs, container images, or application code.