--- title: "Doubling Down on Open Source" date: 2025/06/04 description: "Open Sourcing all Product Features in Langfuse under the MIT license" tag: announcement ogImage: /images/blog/2025-06-04-open-sourcing-langfuse-product/langfuse-open-source-og.png author: Clemens, Marc, Max --- The LLM landscape is changing rapidly and so are the workflows used to build and improve LLM apps. Today, **we are open sourcing all Product Features in Langfuse** to enable our community to iterate on their applications faster and provide our project with feedback on where to go next. Newly open sourced features include managed [LLM-as-a-judge evaluations](/docs/scores/model-based-evals), [annotation queues](/docs/scores/annotation), [prompt experiments](/docs/datasets/prompt-experiments) and [the playground](/docs/playground), all of which are now freely available to self-host under the MIT license. ![OSS Change Comparison](/images/blog/2025-06-04-open-sourcing-langfuse-product/change-visual.png) _If you are self-hosting Langfuse already today, **upgrade your deployment to the [latest version](/self-hosting/upgrade)**. You will find a more powerful version of Langfuse._ ## Why are we doing this? Langfuse is building the **open source AI Engineering Platform**. We are building _the_ platform to observe and improve LLM applications. We are constantly shipping to be the technology of choice for our community. This requires trust, feedback and buy-in from our community. We re-visited the gated features in our Enterprise Edition. If we want to be the first choice in the market, we need to allow our community to **cover the entire dev cycle in our FOSS version**. Features like LLM-as-a-Judge, Evals, or our Playground are market standard at this point and should be freely available. **But why stop there?** The best platform for developers has to be open at its core. By **removing commercial barriers from our product features**, we're fostering deeper trust, collaborating on contributions, accelerating adoption, gathering richer community feedback, and iterating faster than ever. ## Our Open Source Journey **Langfuse was [launched](/blog/product-analytics-for-LLM-apps) as an open source project.** This was based on a few [core beliefs](/why): - Data captured by Langfuse should be freely accessible - The AI landscape changes every week – Langfuse must integrate agnostically with all models and application stacks - Great teams deserve the flexibility to extend the platform to support custom workflows **This positioning resonates and today we are doubling down on it.** Langfuse has been an open core company from the start. **Our core just expanded significantly** and our periphery shrunk. Commercially licensed code is now limited to features for Enterprise Security and Platform Teams (e.g. SCIM, Audit Logs, Data Retention Policies – regular [SSO](/self-hosting/security/authentication-and-sso) is and continues to be MIT licensed). ### Langfuse's Open Core Model | Area | Then | Now | | -------------------------- | ---------- | ------------- | | Core Platform | OSS (MIT) | OSS (MIT) ✅ | | LLM-as-a-Judge Evaluations | Commercial | OSS (MIT) ✅ | | Playground | Commercial | OSS (MIT) ✅ | | Prompt Experiments | Commercial | OSS (MIT) ✅ | | Annotation/Data Labeling | Commercial | OSS (MIT) ✅ | | Enterprise Security | Commercial | Commercial 🔒 | | Enterprise Support | Commercial | Commercial 🔒 | As we open source previously commercial features, we are fully investing our commercial focus in Langfuse Cloud and Enterprise platform teams in self-hosting. ## Thousands of Langfuse Deployments Besides >7,000,000 monthly SDK installs and >5,500,000 Docker pulls, there are >8,000 monthly active self-hosted instances of Langfuse out in the wild. This boggles our minds. We expect that today's changes solidify Langfuse as the first choice for a powerful and truly open source platform in LLMOps. Today is the day to start self-hosting Langfuse. Head over to [our self hosting docs](/self-hosting) and use the new [terraform modules](/changelog/2025-05-22-terraform-modules) for deploying Langfuse at production-scale. **Some additional public metrics:** [View the Langfuse public metrics dashboard](https://app.hex.tech/clickhouse-analytics/app/0349rZiOtG8QDXATQrRCSI/latest). ## How can you follow and contribute to Langfuse? - [🤩 Star us on Github](https://github.com/langfuse/langfuse) - [🙋 Upvote or Contribute requests/feedback on Github Discussions](/ideas) - [🚗 Langfuse Roadmap](/roadmap) --- ## 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/blog/2025-06-04-open-sourcing-langfuse-product.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**: , 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 `) to read or write traces, prompts, datasets, and scores from the terminal. 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