Render Templates | How to Deploy Apps, Frameworks & AI Agents

Render Templates

Get started with templates and guides for deploying apps, frameworks, and AI agents on Render.

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Architecture

flowchart LR
classDef default fill:#1a1a2e,stroke:#a78bfa,color:#fff

User([User])
Web[langfuse]
Worker[[langfuse-worker]]
Minio[langfuse-minio]

Postgres[(langfuse-postgres)]
KeyValue[(langfuse-key-value)]
ClickHouse((langfuse-clickhouse))

User -->|HTTPS| Web
User -->|presigned URLs| Minio

Web -->|queries| Postgres
Web -->|queue| KeyValue
Web -->|analytics| ClickHouse
Web -->|S3 storage| Minio

Worker -->|queries| Postgres
Worker -->|queue| KeyValue
Worker -->|analytics| ClickHouse
Worker -->|S3 storage| Minio

What you can build

After deploying, you'll have a self-hosted Langfuse v4 instance running in your own Render project, with the web app, background worker, and all its data stores (PostgreSQL, ClickHouse, MinIO, and a key-value store) provisioned and connected. You can start tracing and evaluating your LLM applications, capturing prompts, model calls, and their metadata, without sending that data to a third-party service. The default plans are sized for evaluation rather than production traffic, so you'll need to scale up the instance types, storage, and recovery settings before handling real workloads.

Key features

Use cases

What's included

Service Type Purpose
langfuse Web Service
langfuse-worker Background Worker
langfuse-clickhouse Private Service
langfuse-minio Web Service
langfuse-key-value Key Value
langfuse-postgres Primary database

Next steps

  1. Open the Langfuse web service URL and complete the initial sign-up form to create your first user and organization. You should land on the Langfuse dashboard, and the account you just created becomes the instance owner since this is the first sign-up on a fresh PostgreSQL database.
  2. Create a project in the Langfuse dashboard and generate an API key pair, then send a test trace using the Langfuse SDK with those keys. You should see the trace appear under the project's Tracing view within a few seconds, confirming the web service, worker, ClickHouse, and Key Value queue are all connected.
  3. Upload or attach media to a trace and open its presigned URL from the trace detail view. The media should load in your browser from the public MinIO service URL, confirming the langfuse bucket and signed-request object storage path work end to end.

Resources