Deploy Your Own R Data Science Lab in the Cloud


Dean Marchiori


March 26, 2023

In a previous post I linked to a project that makes it easy to deploy and extend an existing Rocker Project Docker image to quickly set up a fully featured RStudio Server environment locally on your machine.

Here I’ll cover some options to deploy this environment to the cloud so you can access it anywhere.

Option 1: Deploy to a Virtual Machine

A common pattern is to create a Virtual Machine (VM) with a cloud service provider (such as AWS, Azure, GCP) and run your code there. I’ll cover an example using Microsoft Azure.

  1. Deploy a VM with an Ubuntu operating system. Go ahead and choose the compute power you need.

  1. Configure a custom network rule to allow traffic on port 8787 for RStudio

3. Log into your new VM terminal using SSH

  1. Install Docker Engine by following these steps

  2. Clone and Deploy the docker container from Step 2 in my guide.

Option 2: Deploy using Azure App Service

The above is fine, but arguably if you are setting up a VM from scratch for development purposes I’m not sure what benefit there is from using a docker container. You may as well just directly install what you want and consider the VM a ‘container’.

However, if you plan to make this available to other users in your organisation, or to adapt this guide for Shiny App development you may be interested in other features such as TLS/SSL security, scale up, advanced networking, continuous integration, continuous deployment, staging/production deployment slots etc. This represents a shift from development sandpit to ‘web app’. For this case, Azure App Service may be a lower hassle option. This is Microsoft’s enterprise grade, web app deployment managed service.

In the Virtual Machine model you are setting up compute infrastructure, deploying and running containers directly - then fiddling with the infrastructure layer for everything else. In App Service you deploy your custom docker container (here containing RStudio Server) to Azure Container Registry (kind of like DockerHub). Azure App Services then builds and serves your app from there - without you having to stand up and manage an Infra layer directly.

  1. Create Azure Container Registry (ACR) (or some other Docker repository) using this help guide

  2. Run and test your container locally

  3. Deploy your local container to ACR using this help guide

  4. Create a new web app in Azure App Services using this help guide

  5. Configuration:

  • I didn’t have to fiddle with ports, presumably it reads the exposed ports in the docker file and does this magically.
  • For custom environment variables like the RStudio Server password, I had to manually add this in the config section.

and it worked just fine: