> ## Documentation Index
> Fetch the complete documentation index at: https://www.thundercompute.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Using Docker

> Containerize applications using Docker on Thunder Compute. Manage images, deploy containers, and optimize Docker environments on cloud GPU instances.

## Disclaimer: Docker support is experimental

Docker has experimental support inside Thunder Compute instances. Because Thunder Compute instances
are themselves containers, running Docker on Thunder Compute is like running Docker inside of
Docker. To get this to work, our instances come with a modified version of `dockerd`, and there are
certain situations when it might not work exactly like the official Docker (eg, advanced
networking features).

## Running Docker

Start your container with the `--device nvidia.com/gpu=all` flag in order to expose GPUs. For example: `docker run -it --rm --device nvidia.com/gpu=all ubuntu:latest`.

Some tutorials will tell you to use `--runtime=nvidia` or `--gpus=all`. These are outdated options and are not supported in Thunder Compute. `--device nvidia.com/gpu=all` is the only supported way to add a GPU to a docker container.

## Known issues

* Docker Compose does not work.
* The container network is not isolated. This means that even ports you don't list with `-p` will be available, and could potentially conflict with other processes or containers.
* Sometimes when the container is destroyed, the processes in it will not be properly killed. This can cause e.g. port conflicts if you then try to start the same container again. You can use standard tools like `ps aux` and `kill` to find and stop any remaining container processes.

If you run into issues, please [contact us](https://www.thundercompute.com/contact).