Layer 4 · self-hosting reality check
What it actually takes to self-host Langfuse
The docs say 2 GB. In practice you want 4 GB. Here is the honest version — real requirements, real monthly cost, what you will be maintaining, and the one thing that catches people out.
Usually reached from LangSmith alternatives, where Langfuse is one of the picks.
| RAM — documented minimum | 2 GB |
|---|---|
| RAM — what it really needs | 4 GB |
| CPU | 2 vCPU |
| Disk | Trace volume × retention — LLM traces are large because they contain full prompts |
| Monthly cost | $24–40/mo plus Postgres and ClickHouse, against per-trace observability pricing |
| Setup time | 2 hours |
| How you install it | docker compose — web, worker, PostgreSQL, ClickHouse, Redis, and S3-compatible storage |
| Ongoing maintenance | Moderate. Five components, and trace volume grows faster than teams expect. |
| Where it stops scaling | High trace volume once ClickHouse is doing the storage. Postgres-only mode is for evaluation, not production. |
The thing that catches people out
Traces contain your full prompts and completions, which means your observability database now holds every piece of customer data that ever passed through a model. That is a data-retention and compliance question, not just a disk one. Set retention deliberately and decide what to redact before you instrument production, not after a subject-access request.
When not to self-host Langfuse
You need one dashboard covering both application and LLM observability. Langfuse is LLM-specific by design.
Every guide here carries this section. A site that only ever tells you to self-host is selling something — the useful answer is sometimes no.
Other Layer 4 self-hosting guides
- Self-hosting Ollama8 GB VRAM for a 7B model at usable speed; 24 GB for 30B-class
- Self-hosting vLLM24 GB VRAM minimum for useful production serving
- Self-hosting QdrantVectors × dimensions × 4 bytes, in RAM, plus overhead — 1M × 768d is roughly 3 GB
- Self-hosting pgvector8 GB — the HNSW index wants to be resident
- Self-hosting LlamaIndex4 GB for the app; your vector store is the real cost
- Self-hosting faster-whisper5 GB VRAM for large-v3 in float16; 2 GB with int8
Common questions
- How much RAM does Langfuse actually need?
- 4 GB in practice. The documented minimum is 2 GB, which is the figure at which the process starts rather than the figure at which it works under real use. 2 vCPU alongside it.
- What does self-hosting Langfuse cost per month?
- $24–40/mo plus Postgres and ClickHouse, against per-trace observability pricing This is commodity VPS pricing and excludes your time, which is the larger cost for most people — budget for moderate. Five components, and trace volume grows faster than teams expect.
- How long does it take to set up Langfuse?
- 2 hours, via docker compose — web, worker, PostgreSQL, ClickHouse, Redis, and S3-compatible storage.
- When should I NOT self-host Langfuse?
- You need one dashboard covering both application and LLM observability. Langfuse is LLM-specific by design.
- What is the most common mistake when self-hosting Langfuse?
- Traces contain your full prompts and completions, which means your observability database now holds every piece of customer data that ever passed through a model. That is a data-retention and compliance question, not just a disk one. Set retention deliberately and decide what to redact before you instrument production, not after a subject-access request.