Add new repo

apt-get install \
    apt-transport-https \
    ca-certificates \
    curl \

curl -fsSL | sudo apt-key add -   

apt-key fingerprint 0EBFCD88

add-apt-repository \
   "deb [arch=amd64] \
   $(lsb_release -cs) \

Install docker CE

apt-get update
apt-get install docker-ce

Test docker

docker run hello-world

Docker Nvidia

If you have nvidia-docker 1.0 installed: we need to remove it and all existing GPU containers

docker volume ls -q -f driver=nvidia-docker | xargs -r -I{} -n1 docker ps -q -a -f volume={} | xargs -r docker rm -f
sudo apt-get purge -y nvidia-docker

Add the package repositories

curl -s -L | \
  sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L$distribution/nvidia-docker.list | \
  sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update

Install nvidia-docker2 and reload the Docker daemon configuration

sudo apt-get install -y nvidia-docker2
sudo pkill -SIGHUP dockerd

Test nvidia-smi with the latest official CUDA image

docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi
nvidia-docker run --rm nvidia/cuda nvidia-smi

Set docker run default with Nvidia

Set nvidia as default runtime to be used by eclipse che

cat << EOF > /etc/docker/daemon.json
    "default-runtime": "nvidia",
    "runtimes": {
        "nvidia": {
            "path": "/usr/bin/nvidia-container-runtime",
            "runtimeArgs": []

Restart docker daemon

systemctl restart docker.service

Eclipse che


docker run -ti -v /var/run/docker.sock:/var/run/docker.sock -v /local/path:/data eclipse/che start


docker run -it -e CHE_MULTIUSER=true -e CHE_HOST=${EXTERNAL_IP} -v /var/run/docker.sock:/var/run/docker.sock -v /local/path:/data eclipse/che start

Eclipse will listen on port 8080, Keycloak on 5050 if any.

Create Tensorflow Stack

Docker image tensorflow/tensorflow:latest-devel-gpu-py3 with Python language server enabled