OpenLIT
Open-source observability platform for GenAI and LLM applications, built on OpenTelemetry.
github.com
TL;DR
- What it does: Open-source observability platform for GenAI and LLM applications, built on OpenTelemetry.
- Best for: Monitoring LLM inference performance.
- Pricing: Open Source — see latest tiers.
What is OpenLIT?
OpenLIT provides open-source observability specifically for Generative AI (GenAI) and Large Language Model (LLM) applications. It integrates directly with OpenTelemetry, allowing it to collect traces and metrics from your AI systems without requiring significant changes to your existing infrastructure. This means you can start monitoring your LLM workflows using familiar tools and standards.
The platform focuses on providing visibility into the performance and behavior of your AI models. You can track key metrics related to model inference, data processing, and overall application health. This visibility helps in identifying performance bottlenecks, understanding resource utilization, and debugging issues that arise during the development and deployment of AI applications. By analyzing traces, developers can pinpoint exactly where delays or errors occur within complex LLM pipelines.
OpenLIT is designed for developers and MLOps engineers working with LLMs. Its open-source nature encourages community contributions and allows for customization to fit specific project needs. Use cases include monitoring prompt engineering effectiveness, tracking token usage, analyzing response times, and ensuring the stability of AI-powered services. It aims to simplify the process of understanding and managing the operational aspects of AI systems.
Key features
- OpenTelemetry native
- LLM observability
- GenAI monitoring
- Trace collection
- Metrics collection
- Open-source platform
- Developer focused
Use cases
- Monitoring LLM inference performance.
- Debugging GenAI application errors.
- Tracking token usage and costs.
- Observing prompt engineering effectiveness.
- Analyzing AI model response times.
Pros & cons
Pros
- Open-source and free to use.
- Native integration with OpenTelemetry.
- Observability for GenAI and LLM applications.
- Collects traces and metrics.
- Community-driven development.
Cons
- Requires OpenTelemetry setup.
- Learning curve for new users.
- May lack advanced features of commercial tools.
- Relies on community support.
- Limited support for non-OpenTelemetry systems.
FAQ
What is OpenLIT?
OpenLIT is an open-source observability platform designed for Generative AI and LLM applications, built using OpenTelemetry standards.
What is the pricing for OpenLIT?
OpenLIT is open-source, meaning it is free to use. Costs would be associated with your infrastructure and OpenTelemetry deployment.
Who is OpenLIT intended for?
It is intended for developers, MLOps engineers, and teams building or deploying AI applications that utilize LLMs.
Are there alternatives to OpenLIT?
Yes, alternatives include commercial observability platforms with AI monitoring capabilities and other open-source solutions focused on LLM observability.
What are the technical limitations of OpenLIT?
It relies on OpenTelemetry for data collection, so users need to have OpenTelemetry instrumentation in place. Specific performance limits depend on the underlying infrastructure.
OpenLIT alternatives
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Helicone AI
Open-source LLM observability platform for logging, monitoring, and debugging AI applications.
LLM
A CLI utility and Python library for interacting with Large Language Models, remote and local.
Tabnine
AI code completion assistant for software developers, supporting multiple languages and IDEs.
agenta
An open-source end-to-end LLMOps platform for prompt engineering, evaluation, and deployment.