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Integrating RStudio Workbench with Jupyter Notebooks, Launcher, and Kubernetes#


These steps describe how to integrate RStudio Workbench, formerly RStudio Server Pro1, with Jupyter Notebooks running with Launcher and Kubernetes.

The most recent rstudio/r-session-complete Docker images referenced in these steps include Python and Jupyter.


Launcher is a new feature of RStudio Server Pro 1.22 that is only available under named user licensing. RStudio Server Pro 1.2 without Launcher is available under existing server-based licensing.

For questions about using Launcher with RStudio Workbench, please contact


This integration is intended to be performed on top of an installation of RStudio Workbench that has already been configured with Launcher and Kubernetes.

Step 1. Configure Launcher with Jupyter Notebooks#

  • Add the following lines to the Launcher Jupyter configuration file:

    File: /etc/rstudio/jupyter.conf

Step 2. Restart RStudio Workbench and Launcher Services#

  • Restart the services:

    $ sudo rstudio-server restart
    $ sudo rstudio-launcher restart

Step 3. Test RStudio Workbench with Launcher and Jupyter Notebooks#

Additional Documentation#

For more information on RStudio Workbench and Launcher, refer to the following reference documentation:

  1. We have renamed RStudio Server Pro to RStudio Workbench. This change reflects the product’s growing support for a wide range of different development environments. RStudio Workbench enables R and Python data scientists to use their preferred IDE in a secure, scalable, and collaborative environment -- whether that is the RStudio IDE, JupyterLab, Jupyter Notebooks, or VS Code. We want RStudio Workbench to be the best single platform to support open source, code-first data science, whether your team is using R or Python. Please see our official Announcement and review our FAQ regarding the name change from RStudio Server Pro to RStudio Workbench. 

  2. We will continue to use the RStudio Server Pro name for references to versions prior to 1.4.