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.
- 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.
- Runtime environment based on Spark 3.4 and Python 3.10 (
Default Spark 3.4 & Python 3.10
) is deprecated and will be removed in a future release.
~ Indicates that the environment includes libraries from a 22.2 Runtime release.
Name | Hardware configuration |
---|---|
JupyterLab with Runtime 24.1 on Python 3.11 |
1 vCPU and 2 GB RAM |
From release 5.1.2: Default Spark 3.5 & Python 3.11 |
1 vCPU and 4 GB RAM |
Default Spark 3.4 & Python 3.11 |
1 vCPU and 4 GB RAM |
Default Spark 3.4 & Python 3.10 (deprecated) |
1 vCPU and 4 GB RAM |
Default Spark 3.3 & Python 3.10 (deprecated) ~ |
1 vCPU and 4 GB RAM |
Python with GPU
Service This service is not available by default. An administrator must install the service. To determine whether the service is installed, click on your avatar and then click About > Version details. If the service is installed and ready to use, it is marked as Deployed
.
You must create your own environment template because 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 versionJuypterLab
.
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