OpenLIT
Open-source LLM observability platform built on OpenTelemetry standards.
About OpenLIT
OpenLIT is an open-source AI engineering platform designed to help teams build, evaluate, and observe LLM applications throughout their entire lifecycle from development to production. It provides comprehensive observability through distributed tracing, evaluation tools, and prompt management capabilities. The platform is built entirely on OpenTelemetry standards, enabling seamless integration with existing observability stacks. OpenLIT distinguishes itself through its zero-code Kubernetes instrumentation, support for 50+ LLM providers and frameworks, and privacy-first architecture where data never leaves user infrastructure. A key limitation is that as an open-source, self-hosted solution, teams must manage their own infrastructure and deployment rather than relying on managed cloud services.
At a glance
- Platforms
- Web, Python SDK, TypeScript SDK, Kubernetes, API
- API
- Available
- Integrations
- OpenAI, Anthropic, Ollama, Deepseek, GPT4All, Cohere, Mistral, GitHub Models
- Last verified
- June 2026
Who It's For
- •LLM application developers
- •AI engineers
- •MLOps teams
- •DevOps engineers
- •Organizations building production AI applications
How It Works
- 1Instruments AI applications using OpenTelemetry standards to capture trace data
- 2Provides automatic code instrumentation via Python/TypeScript SDK requiring just a few lines of code
- 3Offers zero-code Kubernetes observability through the OpenLIT Operator that automatically injects instrumentation without code changes
- 4Collects metrics on token usage, cost, latency, and request flows across LLM interactions
- 5Visualizes complete lifecycle of AI interactions and identifies bottlenecks in real-time
How to Use OpenLIT
- 1Install the SDK via pip (pip install openlit)
- 2Initialize OpenLIT in your application code (import openlit; openlit.init())
- 3For Kubernetes deployments, deploy the OpenLIT Operator and create an AutoInstrumentation CR
- 4Select workloads to instrument - no rebuilds or code changes required
- 5Access dashboards and trace data through the web interface to monitor and debug applications
Key Features
- •Distributed Tracing
- •Evaluation Tools
- •Prompt Hub
- •Experiments
- •Dashboards
- •Fleet Hub
- •GPU Monitoring
- •Vault
- •Zero-Code Kubernetes Observability
- •Automatic Instrumentation
- •OpenTelemetry Native Integration
Use Cases
- •Monitor and debug LLM application performance in production environments
- •Trace AI agent interactions and identify performance bottlenecks
- •Evaluate and optimize prompt performance across different LLM providers
- •Track token usage and costs for AI application infrastructure
- •Implement distributed tracing for complex multi-step AI workflows
Pros & Cons
Advantages
- •Completely open-source and self-hosted with no vendor lock-in, allowing full data privacy and infrastructure control
- •Works with 50+ LLM providers and frameworks with minimal setup - just a few lines of code or zero-code Kubernetes deployment
- •Built on OpenTelemetry standards for seamless integration with existing observability infrastructure
- •Free to use under Apache 2.0 license with active community support and transparent development
Disadvantages
- •Requires self-hosting and infrastructure management, which means teams must handle deployment, scaling, and maintenance costs
- •As an open-source project, support relies on community rather than dedicated enterprise support options
- •Smaller ecosystem compared to commercial alternatives, which may mean fewer pre-built integrations or enterprise features
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Frequently Asked Questions
What is OpenLIT?
OpenLIT is an open-source AI engineering platform designed to help teams build, evaluate, and observe LLM applications throughout their entire lifecycle from development to production. It provides comprehensive observability through distributed tracing, evaluation tools, and prompt management capabilities.
How much does OpenLIT cost?
OpenLIT is free to use.
Is OpenLIT free?
Yes, OpenLIT offers a free plan you can start with.
What are the best OpenLIT alternatives?
Popular OpenLIT alternatives include Gentrace, AirOps, Dify AI.
What is OpenLIT used for?
OpenLIT is commonly used for Monitor and debug LLM application performance in production environments, Trace AI agent interactions and identify performance bottlenecks, Evaluate and optimize prompt performance across different LLM providers.
Does OpenLIT have an API?
Yes, OpenLIT offers an API for developers.
What platforms does OpenLIT support?
OpenLIT is available on Web, Python SDK, TypeScript SDK, Kubernetes, API.
Information Accuracy
Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.