Openlit

Overview

Monitor and optimize LLM infrastructure usage.

OpenLit is an open-source application observability tool designed specifically for LLM and GenAI infrastructures. It integrates seamlessly with OpenTelemetry, allowing users to initiate data collection effortlessly through simple command setups like `openlit.

init()` and `docker-compose -d`. The tool provides granular insights on resource usage, enabling the analysis of LLM, vector database, and GPU performance for improved operational efficiency. With real-time data streaming capabilities, OpenLit allows for immediate data visualization, facilitating quick decision-making and modifications.

The user-friendly interface aids in exploring costs, token consumption, and performance metrics in a straightforward manner. OpenLit connects with popular observability platforms such as Datadog and Grafana, streamlining the data export process for enhanced monitoring and analysis.

Use Cases

• Monitor and analyze GPU performance in LLM applications using OpenLit to optimize resource allocation and enhance operational efficiency.
• Utilize OpenLit to visualize cost and token consumption in real-time, enabling quick adjustments to improve budget management for GenAI projects.
• Integrate OpenLit with Datadog and Grafana for seamless data export, allowing teams to leverage existing observability platforms for comprehensive monitoring and analysis of their AI infrastructure.

Who Is It For

• System administrators
• Data visualizers
• Infrastructure architects
• Observability engineers
• Monitoring specialists