JupyterLab environments (Watson Studio)

JupyterLab can be launched in a Python environment, a Python with Spark environment, and a Python with GPU environment.

Included environment templates

Watson Studio offers the following JupyterLab environment templates with Python. The included environment templates are listed under Templates on the Environments page on the Manage tab of your project.

If you use the Watson Studio extension for Visual Studio Code, All JupyterLab default environments are supported, except for Spark-based environments and custom environments based on Spark.

Note: Spark 3.3 in Notebooks and JupyterLab is deprecated. Although you can still use Spark 3.3 to run your notebooks and scripts, you should consider moving to Spark 3.4.

~ Indicates that the environment includes libraries from a 22.2 Runtime release.

Table 1. Environment templates available in JupyterLab
Name	Hardware configuration
`JupyterLab with Runtime 24.1 on Python 3.11`	1 vCPU and 2 GB RAM
`JupyterLab with Runtime 23.1 on Python 3.10`	1 vCPU and 2 GB RAM
`Default Spark 3.4 & Python 3.11`	1 vCPU and 4 GB RAM
`Default Spark 3.4 & Python 3.10`	1 vCPU and 4 GB RAM
`Default Spark 3.3 & Python 3.10` ~	1 vCPU and 4 GB RAM

Python with GPU

Service GPU environments are not available by default. An administrator must install the Jupyter notebooks with Python for GPU service on the IBM Cloud Pak for Data platform. To determine whether the service is installed, open the Services catalog and check whether the service is enabled.

You need to create your own environment template as Watson Studio does not include a default Python with GPU environment template that you can select.

To create an environment template:

Ensure that the Jupyter Notebooks with Python with GPU service was installed.
Create an environment template from the Manage tab of your project. Select the Environments page, click New template under Templates, then select type GPU and Software version JuypterLab.

Viewing JupyterLab environments

The JupyterLab environments are listed under Templates on the Environments page on the Manage tab of your project. Click the environment to see the environment details. If you created your own environment template with the software version JupyterLab, you can add a software customization.

After you start JupyterLab, the runtime that becomes active for your session is listed under Tool runtimes on the Environments page on the Manage tab of your project. You can stop the runtime from this page.

Runtime scope

A JupyterLab environment runtime is always scoped to a project and a user. Each user can only have one active JupyterLab session per project at one time.

Learn more

Parent topic: Environments