/vertex-workbench-custom-images

Primary LanguageJupyter Notebook

vertex-workbench-custom-images

Steps for using a custom container image for Vertex Workbench instances

This example shows how to build a python 3.9 image from scratch, and derived from an existing container.

  1. Follow instructions in CreateCustomWorkbenchContainers.ipynb to create a custom container image and save it in Artifact Registry

  2. Once the image is built, navigate to Vertex Workbench, select New Notebook, and then Customize...

create-instance

  1. Specify a Notebook name and Region. For Environment, select Custom container

create-instance

  1. When asked to specify the Docker container image, hit the SELECT button

create-instance

  1. A window will open leading to Container Registry and Artifact Registry. Find and select your image

create-instance

  1. Specify desired Machine Configuration

  2. The Networking and Permission fields will likely depend on your org policies. Should be able to use the same values used for non-custom-image Notebook Instances

  3. Under Security, check Enable terminal. Values for the other options may depend on your org policies

create-instance

  1. Select Create and wait for your intance to be provisioned
  • This should only take a few minutes.
  • Note: if your instance continues to spin without reaching a READY state, this could be for several reasons (e.g., your org policies could require additional steps than those outlined above)
  1. When the instance is ready, select Open JupyterLab, and open a Python 3 notebook

create-instance

  1. In the notebook cell, run the code snippet below to confirm the python version
import sys
print("Python version")
print (sys.version)
print("Version info.")
print (sys.version_info)

create-instance