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## What is Langfuse? {#what-is-langfuse}
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Langfuse is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications. It is part of the ClickHouse ecosystem and relies on **ClickHouse** at its core to provide a scalable, high-performance observability backend.
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[Langfuse](https://langfuse.com) is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications. It is part of the ClickHouse ecosystem and relies on **ClickHouse** at its core to provide a scalable, high-performance observability backend.
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By leveraging ClickHouse's columnar storage and fast analytical capabilities, Langfuse can handle billions of traces and events with low latency, making it suitable for high-throughput production workloads.
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## Why Langfuse? {#why-langfuse}
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-**Open source:** Fully open source with public API for custom integrations
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-**Production optimized:** Designed with minimal performance overhead
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-**Best-in-class SDKs:** Native SDKs for Python and JavaScript
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-**Framework support:** Integrated with popular frameworks like OpenAI SDK, LangChain, and LlamaIndex
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-**Multi-modal:** Support for tracing text, images and other modalities
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-**Full platform:** Suite of tools for the complete LLM application development lifecycle
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## Deployment Options {#deployment-options}
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Langfuse offers flexible deployment options to meet different security and infrastructure needs:
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Langfuse offers flexible deployment options to meet different security and infrastructure needs.
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### Langfuse Cloud
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***Managed Service**: Fully managed by the Langfuse team.
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***Powered by ClickHouse**: Runs on a managed ClickHouse cluster for optimal performance.
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***Security & Compliance**: SOC 2 Type II and ISO 27001 certified. GDPR compliant.
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***Data Regions**: Available in US (AWS us-west-2) and EU (AWS eu-west-1).
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**[Langfuse Cloud](https://cloud.langfuse.com)** is a fully managed service powered by a managed ClickHouse cluster for optimal performance. It is SOC 2 Type II and ISO 27001 certified, GDPR compliant, and available in US (AWS us-west-2) and EU (AWS eu-west-1) data regions.
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### Self-Hosted
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***Open Source**: Fully open-source (MIT license) and free to use.
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***Infrastructure**: Deploy on your own infrastructure using Docker or Kubernetes.
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***ClickHouse Integration**: You run your own ClickHouse instance (or use ClickHouse Cloud) to store observability data, ensuring complete control over your data.
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**[Self-hosted](https://langfuse.com/self-hosting)** Langfuse is fully open-source (MIT license) and free to deploy on your own infrastructure using Docker or Kubernetes. You run your own ClickHouse instance (or use ClickHouse Cloud) to store observability data, ensuring complete control over your data.
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## Architecture {#architecture}
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Langfuse uses a decoupled architecture to ensure scalability and reliability.
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Langfuse only depends on open source components and can be deployed locally, on cloud infrastructure, or on-premises:
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***ClickHouse**: Stores high-volume observability data (traces, spans, generations, scores). It enables fast aggregation and analytics for dashboards.
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***Postgres**: Stores transactional data like user accounts, project configurations, and prompt definitions.
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***Redis**: Handles event queuing and caching.
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***S3/Blob Storage**: Stores large payloads and raw event data.
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```mermaid
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flowchart TB
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Worker -..->|"optional for evals"| LLM
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```
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***ClickHouse**: Stores high-volume observability data (traces, spans, generations, scores). It enables fast aggregation and analytics for dashboards.
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***Postgres**: Stores transactional data like user accounts, project configurations, and prompt definitions.
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***Redis**: Handles event queuing and caching.
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***S3/Blob Storage**: Stores large payloads and raw event data.
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## Features {#features}
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### Observability {#observability}
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[Observability](/docs/observability/overview) is essential for understanding and debugging LLM applications. Unlike traditional software, LLM applications involve complex, non-deterministic interactions that can be challenging to monitor and debug. Langfuse provides comprehensive tracing capabilities that help you understand exactly what's happening in your application.
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_📹 Want to learn more? [**Watch end-to-end walkthrough**](https://langfuse.com/watch-demo?tab=observability) of Langfuse Observability and how to integrate it with your application._
Want to learn more? [**Watch end-to-end walkthrough**](https://langfuse.com/watch-demo?tab=observability) of Langfuse Observability and how to integrate it with your application.
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### Prompt Management {#prompt-management}
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[Prompt Management](/docs/prompt-management/overview) is critical in building effective LLM applications. Langfuse provides tools to help you manage, version, and optimize your prompts throughout the development lifecycle.
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_📹 Want to learn more? [**Watch end-to-end walkthrough**](https://langfuse.com/watch-demo?tab=prompt) of Langfuse Prompt Management and how to integrate it with your application._
Want to learn more? [**Watch end-to-end walkthrough**](https://langfuse.com/watch-demo?tab=prompt) of Langfuse Prompt Management and how to integrate it with your application.
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### Evaluation & Datasets {#evaluation}
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[Evaluation](/docs/evaluation/overview) is crucial for ensuring the quality and reliability of your LLM applications. Langfuse provides flexible evaluation tools that adapt to your specific needs, whether you're testing in development or monitoring production performance.
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_📹 Want to learn more? [**Watch end-to-end walkthrough**](https://langfuse.com/watch-demo?tab=evaluation) of Langfuse Evaluation and how to use it to improve your LLM application._
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<TabsgroupId="evaluation">
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<TabItemvalue="analytics"label="Analytics">
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Plot evaluation results in the Langfuse Dashboard.
Collect feedback from your users. Can be captured in the frontend via our Browser SDK, server-side via the SDKs or API. Video includes example application.
Run fully managed LLM-as-a-judge evaluations on production or development traces. Can be applied to any step within your application for step-wise evaluations.
Want to learn more? [**Watch end-to-end walkthrough**](https://langfuse.com/watch-demo?tab=evaluation) of Langfuse Evaluation and how to use it to improve your LLM application.
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## Quickstarts {#quickstarts}
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Get up and running with Langfuse in minutes. Choose the path that best fits your current needs:
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