OpenLIT

OpenLIT is an open-source platform focused on the observability of generative AI and large language model applications. It helps developers track requests, response times, and costs, with native OpenTelemetry support so it fits into existing tracing setups. It also offers exception monitoring through Python and TypeScript SDKs, prompt management with version control, secure key management, and Openground testing to compare different LLMs on performance and cost. Because it is open source, you can self-host it to keep your data private. The core is free to use and aimed at AI developers, data scientists, and enterprises.

- Trace AI application requests, response times, and costs

- Monitor exceptions with Python and TypeScript SDKs

- Manage prompts with version control in one place

- Compare LLMs on performance and cost with Openground

- AI developers building LLM applications

- Data scientists comparing models and costs

- Enterprises that need to self-host for privacy

- Teams that want OpenTelemetry-based monitoring

Self-hosting gives you control but also means you maintain the infrastructure, updates, and security yourself, which takes time and skill. It is a developer tool, so there is a setup learning curve, and you should expect to read the docs before it works well. As an open-source project, availability and features can change between versions, so pin what you use and test upgrades. Monitor any keys and data you route through it carefully, since you are responsible for your own deployment. For team use, agree on naming and editing conventions in advance to avoid version conflicts or duplicated work. Name and archive exported files consistently so you can find and reuse them, and keep a backup copy of key data.