Build a custom image

Create your own custom image in Workspace on VESSL

Requirements

To use custom images to run a workspace, your custom images have to satisfy below requirements.

• Jupyterlab
  • VESSL runs Jupyterlab and expose port 8888. Jupyterlab should be pre-installed in the container image.
  • Jupyterlab daemon must be located in /usr/local/bin/jupyter.
• sshd
  • VESSL runs sshd and expose port 22 as NodePort. sshd package should be pre-installed in the container image.
• Persistent Volume Claim (PVC) mountable at /root
  • VESSL mounts a PVC at /root to keep state across Pod restarts.
• curl
  • VESSL verifies workspace status. curl package should be pre-installed in the container image.

Building from VESSL’s pre-built images

VESSL offers pre-built images to run workspaces directly. You can use these images to build your own images. These images already have pre-installed Jupyterlab and sshd. The list of images is in the following table.

CPU pre-built images

Python	Tensorflow	PyTorch	Torchvision	Image
3.8	2.12.0	1.13.1	0.14.1	quay.io/vessl-ai/python:3.8
3.9	2.12.0	1.13.1	0.14.1	quay.io/vessl-ai/python:3.9
3.10	2.12.0	1.13.1	0.14.1	quay.io/vessl-ai/python:3.10
3.11	2.12.0	2.0.1	0.15.2	quay.io/vessl-ai/python:3.11

GPU pre-built images

Python	CUDA	TensorFlow	PyTorch	Image
3.10	12.1	-	2.3.1	quay.io/vessl-ai/torch:2.3.1-cuda12.1
3.10	11.8	-	2.2.2	quay.io/vessl-ai/torch:2.2.2-cuda11.8
3.10	12.2	-	2.1.0	quay.io/vessl-ai/torch:2.1.0-cuda12.2
3.8	12.0	-	1.14.0	quay.io/vessl-ai/torch:1.14.0-cuda12.0
3.10	12.3	2.14.0	-	quay.io/vessl-ai/tensorflow:2.14.0-cuda12.3
3.10	12.4	-	-	quay.io/vessl-ai/cuda:12.4
3.10	12.1	-	-	quay.io/vessl-ai/cuda:12.1
3.10	11.8	-	-	quay.io/vessl-ai/cuda:11.8

Example

# Use CUDA 12.1, PyTorch 2.3.1 base image
FROM quay.io/vessl-ai/torch:2.3.1-cuda12.1

# Install custom Python dependencies
RUN pip install transformers
...

Building from community-maintained images

You can make your own images from any community-maintained Docker images. Make sure that your image meet our requirements.

Example

FROM nvidia/cuda:11.2.2-devel-ubuntu20.04

RUN apt-get update
RUN DEBIAN_FRONTEND=noninteractive \
    apt-get install -y \
    software-properties-common curl openssh-server

# Install Python 3.9
# Note that base image has python3.8 (3.8.10) installed
RUN add-apt-repository ppa:deadsnakes/ppa
RUN apt-get install -y python3.9 python3.9-distutils
# Add symbolic links
RUN update-alternatives --install /usr/bin/python3 python3 $(which python3.9) 1
RUN update-alternatives --install /usr/bin/python python /usr/bin/python3 1

# Install pip
RUN curl https://bootstrap.pypa.io/get-pip.py | python
RUN pip install -U pip

# Install Jupyterlab
RUN pip install jupyterlab

FAQ

If you use conda to install JupyterLab, the JupyterLab executable is generally located at /opt/conda/bin/jupyter. In this case, you should create a symbolic link at usr/local/bin/jupyter.

# In Dockerfile,
RUN ln -s /opt/conda/bin/jupyter /usr/local/bin/jupyter