Integrating RStudio Workbench with Jupyter Notebooks on a Load-balanced Cluster#

Overview#

These steps describe how to integrate RStudio Workbench, formerly RStudio Server Pro¹, with Jupyter Notebooks running on a load-balanced cluster using local launcher.

This integration makes use of the Local Launcher in RStudio Workbench to spawn Jupyter Notebook and JupyterLab sessions on a load-balanced cluster without the use of an external resource manager.

Step 1. Configure RStudio Workbench with Launcher and Jupyter Notebooks#

For each node in the cluster, complete all the instructions mentioned in the guide below:

Integrating RStudio Workbench with Jupyter Notebooks on a Single Server

Step 2. Configure Local Launcher Load Balancing#

Next, complete all of the instructions mentioned in the guide below to load balance the RStudio Workbench cluster:

Configuring Local Launcher Load Balancing in RStudio Workbench

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. ↩