Docker Installation Guide

Install to Existing Docker Image

You can choose between HPE Machine Learning Data Management’s pre-built image (a custom version of jupyter/scipy-notebook) or add the extension to your own image.

Option 1: Pre-Built Image

  1. Open your terminal.

  2. Run the following:

    docker run -it -p 8888:8888 --entrypoint /opt/conda/bin/jupyter pachyderm/notebooks-user:v2.10.6 lab
  3. Open the UI using the link provided in the terminal following:

    [I 2023-01-26 19:07:00.245 ServerApp] Jupyter Server 1.16.0 is running at:
    [I 2023-01-26 19:07:00.245 ServerApp] http://fb66b212ca13:8888/lab?token=013dbb47fc32c0f1ec8277a399e8ccf0e4eb87055942a21d
    [I 2023-01-26 19:07:00.245 ServerApp]  or
  4. Navigate to the connection tab. You will need to provide a link formatted like the following:

  5. Select Set Address.

  6. Navigate to the Launcher view in Jupyter and select Terminal.

  7. Input the following command:

    pachctl version
  8. If you see a pachctl and pachd version, you are good to go.

Option 2: Custom Dockerfile

Replace the following ${PACHCTL_VERSION} with the version of pachctl that matches your cluster’s, and update <version> with the release number of the extension.

You can find the latest available version of our HPE Machine Learning Data Management Mount Extension in PyPi.

# This runs the following section as root; if adding to an existing Dockerfile, set the user back to whatever you need.
USER root

# This is the directory files will be mounted to, mirroring how pipelines are run.
RUN mkdir -p /pfs

# If you are not using "jovyan" as your notebook user, replace the user here.
RUN chown $NB_USER /pfs

# Optionally Install Pachctl - Set the version of Pachctl that matches your cluster deployment.
RUN curl -f -o pachctl.deb -L${PACHCTL_VERSION}/pachctl_${PACHCTL_VERSION}_amd64.deb
RUN dpkg -i pachctl.deb

# This sets the user back to the notebook user account (i.e., Jovyan)

# Replace the version here with the version of the extension you would like to install from
RUN pip install jupyterlab-pachyderm==<version>

Then, build, tag, and push your image.