By Sakura T. Sakura T.
on AI Developer Tools

OpenLIT

Open-source observability and control for your AI stack

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OpenLIT
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Freemium

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What Is OpenLIT?

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OpenLIT is an open-source AI engineering platform that gives teams full-stack observability into LLM and agent-based applications. Using OpenTelemetry, it lets you trace and monitor GPUs, LLMs, vector databases, MCP, and coding agents in one unified view.

Teams can instrument AI apps, manage prompts, compare models, run LLM evaluations, and monitor agents in production. OpenLIT also supports secure API key management with Vault and can be self-hosted under the Apache 2.0 license for unlimited usage via Helm or Docker.

A fully hosted OpenLIT Cloud is planned for teams that prefer managed infrastructure and zero-ops deployment.

Quick Snapshot

OpenLIT centralizes observability, evaluations, and management for LLMs and AI agents so teams can understand performance, quality, and cost in one place. Its open-source, self-hosted model gives you full control over data, infrastructure, and scaling.

Works on
  • Web
  • API
  • Other
Pricing Model
Freemium — OpenLIT OSS is free to self-host under the Apache 2.0 license with unlimited self-hosted usage. A fully hosted OpenLIT Cloud with managed infrastructure and additional features is coming soon, with pricing to be announced.
Fits on
Affiliate Program
We could not identify an affiliate program.
API Availability
OpenLIT has an API available.
Key Features
  1. Full-stack observability for LLMs and agents
  2. OpenTelemetry-native tracing for AI workloads
  3. Open-source, self-hosted control of AI data
Audience
  • developers
  • ML engineers
  • DevOps teams
  • AI platform teams
  • startups
  • enterprise AI teams
URL
https://openlit.io

Screenshot

OpenLIT

Key Features of OpenLIT

OpenTelemetry-based tracing

Provides deep tracing for GPUs, LLMs, vector databases, MCP, and coding agents using OpenTelemetry, integrating AI workloads into existing observability stacks.

LLM evaluations

Lets teams run evaluations on LLM outputs to measure quality and performance and use those insights to improve models and prompts.

Agent monitoring

Monitors AI agents and their workflows in production, giving visibility into steps, actions, and dependencies across the stack.

Prompt management

Centralizes prompt definitions and changes so teams can manage and iterate on prompts while tracking their impact on outcomes.

Model comparison

Enables side-by-side comparison of different models or configurations to inform model selection and optimization decisions.

Self-hosted deployment

Can be self-hosted with Helm or Docker under the Apache 2.0 license, allowing unlimited usage and full data control.

Vault key management

Supports managing API keys via Vault for secure credential handling within AI and LLM applications.

Planned hosted cloud

A fully managed OpenLIT Cloud is planned for teams that prefer hosted infrastructure and zero-ops operations.

Use Cases for OpenLIT

Production LLM monitoring

Monitor LLM behavior, latency, and failures in production using OpenTelemetry traces so teams can quickly detect issues and maintain reliable AI-powered features.

AI agent observability

Trace complex AI agent workflows, including tool calls and external services, to understand decision paths, bottlenecks, and performance at each step.

Model evaluation and comparison

Run LLM evaluations and compare different models or configurations side by side, helping teams choose the best-performing models for their workloads.

Prompt management at scale

Centralize and manage prompts across applications, track changes, and correlate prompt variations with quality metrics and outcomes.

Secure AI platform operations

Manage API keys via Vault and keep all observability data inside your own infrastructure, supporting stricter compliance and data governance requirements.

Frequently Asked Questions

What is OpenLIT used for?

OpenLIT is used to trace, evaluate, and manage LLMs and AI agents with OpenTelemetry, giving teams full-stack observability into GPUs, models, vector databases, and agents across their AI applications.

Is OpenLIT open-source and free to self-host?

Yes, OpenLIT is open-source and can be self-hosted for free under the Apache 2.0 license, with unlimited self-hosted usage.

Does OpenLIT support monitoring AI agents in production?

Yes, OpenLIT is designed to monitor AI agents in production, providing detailed traces of agent workflows, tool calls, and related infrastructure components.

How does OpenLIT integrate with existing observability stacks?

OpenLIT is built on OpenTelemetry, allowing it to integrate into existing observability tools and pipelines that already support OpenTelemetry traces and metrics.

Can I manage prompts and compare models in OpenLIT?

Yes, OpenLIT includes prompt management and model comparison features so you can centralize prompts, run evaluations, and compare models to improve AI quality.

Is there a hosted cloud version of OpenLIT?

A fully hosted OpenLIT Cloud is planned for teams that prefer managed infrastructure and zero-ops operations, with pricing to be announced.

How do I deploy OpenLIT?

You can deploy OpenLIT in your own environment using Helm or Docker, then instrument your AI applications with its OpenTelemetry-based integrations.

Does OpenLIT support secure API key management?

Yes, OpenLIT supports managing API keys via Vault so teams can handle credentials securely within their AI and LLM workflows.

OpenLIT · Our Verdict

OpenLIT brings modern observability practices to LLMs and AI agents by building directly on OpenTelemetry, which makes it easier for engineering and platform teams to integrate into existing monitoring stacks. Its open-source, self-hosted approach and Apache 2.0 licensing are particularly attractive for organizations that need full control over data and infrastructure while still getting enterprise-grade tracing, evaluation, and prompt management capabilities.

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