---
title: Ten Reasons to Use Langfuse for LLM Observability, Evaluations and Prompt Management
seoTitle: "Ten Reasons to Use Langfuse"
description: "Ten reasons teams pick Langfuse for LLM observability, evaluation, and prompt management, from open source and self-hosting to framework coverage."
tags: [product]
---

# Ten Reasons to Use Langfuse

Langfuse is a powerful tool designed to enhance LLM observability, evaluations, and prompt management.

## Ten reasons why you should consider using it:

1. **Open Source**: Langfuse is [open source](/open-source). You can customize and self-host it. You can trust for it to be around for the long-haul.

2. **Platform Agnostic**: Langfuse works seamlessly with any model and [integrates](/integrations) with frameworks like Llama Index and LangChain.

3. **Detailed Metrics**: Langfuse provides in-depth [insights and metrics](/docs/metrics/overview) to improve your LLM applications.

4. **Real-time Monitoring and Evals**: Langfuse enables real-time monitoring and [evaluation](/docs/evaluation/overview) to keep track of your models' performance.

5. **Flexible Deployment**: Whether [on-premise](/self-hosting) or in the cloud, Langfuse adapts to your deployment needs.

6. **Scalable**: Built to scale with your projects, Langfuse handles projects of all sizes: from small to enterprise-level needs.

7. **Compliance Ready**: Langfuse is ISO27001 and SOC2 Type 2 certified, GDPR compliant, and offers a HIPAA-ready region. Learn more in our [Security Center](/security).

8. **Customizable Dashboards**: Langfuse lets you create dashboards that suit your requirements.

9. **Easy Integration**: Langfuse is simple to integrate to your existing applications through its large number of [integrations](/integrations).

10. **Community Support**: You will benefit from Langfuse's supportive [open-source community](/support) and continuous updates.

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## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/faq/all/ten-reasons-to-use-langfuse.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.