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Docker Deployment

Deploy Obot using Docker for local development, testing, and proof-of-concept scenarios.

Overview​

Docker deployment is the fastest way to get Obot running. It's ideal for:

  • Local development and testing
  • Single-machine deployments
  • Proof-of-concept and evaluation
  • Small team usage

For production deployments, see Kubernetes Deployment.

Prerequisites​

  • Docker installed
  • 2+ CPU cores and 4GB RAM available
  • 10GB disk space

Quick Start​

Basic Deployment (Built-in PostgreSQL)​

Run Obot with the built-in PostgreSQL instance (suitable for development and testing):

docker run -d \
  --name obot \
  -v obot-data:/data \
  -v /var/run/docker.sock:/var/run/docker.sock \
  -p 8080:8080 \
  -e OPENAI_API_KEY=your-openai-key \
  ghcr.io/obot-platform/obot:latest

With Authentication​

docker run -d \
  --name obot \
  -v obot-data:/data \
  -v /var/run/docker.sock:/var/run/docker.sock \
  -p 8080:8080 \
  -e OPENAI_API_KEY=your-openai-key \
  -e OBOT_SERVER_ENABLE_AUTHENTICATION=true \
  -e OBOT_BOOTSTRAP_TOKEN=your-bootstrap-token \
  ghcr.io/obot-platform/obot:latest

Accessing Obot​

Once started, access Obot at http://localhost:8080.

If you enabled authentication, use your bootstrap token to log in as the owner and set up an authentication provider. If you didn't supply a bootstrap token, a random one will be generated and can be found in the container's logs by searching for "Bootstrap token".

Next Steps​

  1. Configure Authentication: Set up auth providers for secure access
  2. Configure Model Providers: Configure model providers (OpenAI, Anthropic, etc.)
  3. Set Up MCP Servers: Configure MCP servers for extended functionality