What is Openlit?
OpenLIT is an open‑source platform built on OpenTelemetry that enables end‑to‑end observability for large language model applications.
It supplies distributed tracing for real‑time monitoring of request flows, bottlenecks, and full lifecycle events across multiple deployments.
The platform includes AI model evaluation tools that run online or offline tests through a UI or SDK for prompt and model performance comparison.
Prompt Hub lets teams centrally version, deploy, and iterate on prompts, with integrated experiment tracking to accelerate development cycles.
Fleet Hub aggregates telemetry from all LLM workloads, allowing custom SQL queries, dashboard widgets, and cross‑environment comparison in a single view.
A zero‑code Kubernetes Operator automatically instruments applications, requiring only a configuration file for integration with existing observability stacks.
OpenLIT supports major LLM providers and frameworks—including OpenAI, Anthropic, Cohere, LangChain, and LlamaIndex—plus vector database integrations like Pinecone and ChromaDB.
The open‑source nature allows self‑hosting, full data privacy, and community contributions that keep the tool aligned with production requirements.
Openlit pricing Subscription
Verify on the official pricing page.
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Openlit's key features
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Distributed tracing of LLM apps
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Model evaluation via UI and SDK
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Prompt management with version control
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Real-time monitoring dashboards with SQL queries
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Multi-deployment management across environments
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Zero-code Kubernetes observability operator
Openlit use cases
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Deploy an end‑to‑end LLM observability stack with OpenLIT’s zero‑code Kubernetes operator, automatically collecting distributed tracing, model evaluation metrics, and fleet telemetry across all your services
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Easily version, roll back, and audit LLM prompts with OpenLIT’s prompt versioning, ensuring consistent behavior and compliance in production
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Leverage OpenLIT’s real‑time telemetry aggregation dashboard to monitor latency, error rates, and resource usage for each model, enabling proactive scaling and rapid debugging
Who is it for?
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System administrators
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Data visualizers
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Infrastructure architects
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Observability engineers
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Monitoring engineers
