Use a Docker Container like a Remote Server

3 minute read


This post describes how to use a Docker container like a single isolated remote server. Some of the content focuses on using NVIDIA GPUs, so you can omit the details if you are not interested in this.


  • In this article, your server will be a remote machine (or host machine) and your laptop will be a local machine.
  • You have to install the Docker first on your remote machine. (Or ask the root to do this).
  • You do not have to be a root of the host machine to follow this post.
  • But you have to know what Docker is and how it works. See overview documentations: [English] [Korean].


Pull an image you want to use in your remote machine. In this post, it is nvidia/cuda:10.2-cudnn8-devel-ubuntu18.0.

# In the remote machine,
docker pull nvidia/cuda:10.2-cudnn8-devel-ubuntu18.04

Create a container based on this image.

# In the remote machine,
docker run -ti \
  --runtime=nvidia \
  --name $container_name \
  -p $ssh_port:22 -p $tensorboard_or_jupyter_port:6006 \
  -v $mount_dir:$mount_dir \
  --ipc=host \
  -d nvidia/cuda:10.2-cudnn8-devel-ubuntu18.04 /bin/bash
  • If you want to use GPUs in the container, you have to specify --runtime=nvidia.
  • You have to forward 22 port (ssh) to your own port.
  • If you want to use a Tensorboard or Jupyter, you have to forward additional ports for these.
  • If you want to use file systems in the host machine, you have to bind mount a volume (-v $mount_dir:$mount_dir) using absolute paths.
  • If you want to use multiple subprocesses (num_workers > 1) in DataLoader, it is recommend to put --ipc=host.
  • If you want to use a specific set of GPUs, use --gpus argument. (e.g., --gpus '"device=0,1,2,3"').

Now attach your container.

# In the remote machine,
docker attach $container_name

In the container, install whatever you need. Below is my preferred list, but do not forget to install the following packages: openssh-server ssh.

# In the container of the remote machine,
apt-get update
apt-get install vim git sudo curl screen software-properties-common
apt-get install openssh-server ssh  # important!

# To install python 3.7. If you do not want to use python3.7, you can skip it, or install other versions.
add-apt-repository ppa:deadsnakes/ppa
apt-get update
apt-get install python3.7 python3-pip python3.7-dev

You might want to login the container with a password, then turn off PubkeyAuthentication. If you skip this step, you cannot log in to your container with your id and password.

# In the container of the remote machine,
sed 's/PubkeyAuthentication/#PubkeyAuthentication/g' /etc/ssh/sshd_config > ~/sshd_config.tmp
cat ~/sshd_config.tmp > /etc/ssh/sshd_config
rm ~/sshd_config.tmp
service ssh restart  # important!

Create a user account and make it a root.

# In the container of the remote machine,
adduser $user_name
usermod -aG sudo $user_name
su $user_name

Configure user-specific settings: git global configuration, shell, bashrc/zshrc, or vimrc.

Turn off the shell you are working on, and turn on a new shell in the local machine. Then access the container you created with the below command.

# In the local machine,
ssh -p $ssh_port $user_name@$host

If you want to use a Tensorboard or Jupyter, please follow my other post.


  • I cannot log in my containers after restarting them: You have to run service ssh restart after restarting containers.

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