---
display_name: Docker Workspaces with GPU & DooD
description: Provision Docker-based Coder workspaces with GPU support, Docker-out-of-Docker, Go, and Bun.
icon: ../../../site/static/icon/docker.png
maintainer_github: coder
verified: true
tags: [docker, container, gpu, golang, bun, sdkman]
---

# Feature-Rich Docker Workspaces

Provision powerful Docker containers as [Coder workspaces](https://coder.com/docs/workspaces) with this advanced template. It features GPU passthrough, Docker-out-of-Docker (DooD), and automatically installs essential development tools on startup.

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## Prerequisites

### Infrastructure

The VM you run Coder on must have a running Docker socket and the `coder` user must be added to the Docker group:

```sh
# Add coder user to Docker group
sudo adduser coder docker

# Restart Coder server
sudo systemctl restart coder

# Test Docker
sudo -u coder docker ps
```

## Features & Architecture

This template provisions the following resources and features:

- **Base Image**: `codercom/enterprise-base:ubuntu`
- **GPU Support**: Passes all host GPUs to the workspace (`gpus = "all"`) for AI/ML and hardware acceleration.
- **Docker-out-of-Docker (DooD)**: Mounts the host's `/var/run/docker.sock` so you can build and run containers seamlessly from inside your workspace.
- **Auto-Provisioned Tools**: The workspace startup script automatically handles:
  - System package updates (`apt-get update` & `apt-get upgrade`)
  - Docker CLI
  - Nixpacks
  - Bun
  - Golang
  - SDKMAN! & Maven
- **Persistent Storage**: Uses a persistent host directory mapped to `/home/coder` to ensure your files survive workspace restarts.
- **Rich Telemetry**: Displays CPU, RAM, Disk, Load Average, and GPU utilization directly in the Coder UI.
- **IDE Support**: Native integration with code-server (Browser VS Code) and JetBrains IDEs.

> **Note**
> While your `/home/coder` directory is persistent, the container's root filesystem is ephemeral. The startup script handles reinstalling your system-level tools (Go, Bun, SDKMAN!, etc.) on each start. To speed up boot times, you may want to bake these tools into a custom Docker image.