{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "langfuse-langfuse--self-host-llm-tracing-in-five-minutes",
 "repo": "langfuse/langfuse",
 "repo_url": "https://github.com/langfuse/langfuse",
 "repo_slug": "langfuse-langfuse",
 "title": "Self-host LLM tracing in five minutes",
 "page_title": "How to self-host LLM tracing in five minutes with Langfuse",
 "summary": "Run Langfuse locally with Docker Compose and start sending traces from your app.",
 "who": "A developer whose agent gives odd answers and who cannot see which prompt, retrieval or tool call went wrong.",
 "problem": "Without tracing, debugging an LLM app means print statements and guesswork.",
 "outcome": "A local Langfuse instance showing each LLM call, retrieval step and agent action in your app.",
 "steps": [
  "Clone the repo with `git clone --depth=1 https://github.com/langfuse/langfuse.git` and `cd langfuse`",
  "Start it with `docker compose up`",
  "Instrument your app with the Python or JS/TS SDK, or a drop-in integration such as OpenAI, Langchain or LlamaIndex",
  "Open the Langfuse UI and inspect the traces for a request that went wrong",
  "Configure Docker log rotation, since the default json-file driver does not rotate logs"
 ],
 "agent_prompt": "Self-host langfuse/langfuse locally with Docker Compose, then add tracing to my <app> using the <OpenAI or Langchain> integration. Send a few test requests and show me the trace for the slowest one.",
 "agents": [
  "claude-code",
  "codex",
  "cursor"
 ],
 "difficulty": "Beginner",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "The local Docker Compose setup is for trying it out; the README recommends Kubernetes with Helm for production.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "typescript",
 "requirements": [
  "Docker and Docker Compose for local self-hosting, or a Langfuse Cloud account",
  "The Python or JS/TS SDK, or a supported framework integration",
  "For production: a VM, Kubernetes with Helm, or Terraform on AWS, Azure or GCP"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [
  {
   "tag": "disk",
   "notice": "Docker's default json-file logging does not rotate, so a long-running instance can fill the disk unless you configure log rotation."
  }
 ],
 "best": true,
 "score": 1.0,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/langfuse-langfuse/self-host-llm-tracing-in-five-minutes/",
 "md": "https://dedupedai.com/use-cases/langfuse-langfuse/self-host-llm-tracing-in-five-minutes/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/langfuse-langfuse--self-host-llm-tracing-in-five-minutes.json",
 "api_version": "v1"
}