RStudio Server on Azure
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RStudio Server Pro is now available on the Azure Marketplace, the company announced on the RStudio Blog earlier this month. This means you can launch RStudio Server Pro on an virtual machine with the memory, disk, and CPU configuration of your choice, and pay by the minute for the VM instance plus a the RStudio software charge. Then, you can use a browser to access the remote RStudio Server (the interface is nigh-indistinguishable from the desktop version), with access to the commercial features of RStudio including support for multiple R version and concurrent R sessions, load-balancing and high availability instances, and enhanced security.
If you don't want or need those capabilities, you can use the open-source version of RStudio Server as well. The easiest way is simply to launch an instance of the Azure Data Science Virtual Machine, which comes pre-installed with the open-source RStudio Server. It also comes pre-installed with dozens of data science tools you can use with R and RStudio, including Jupyter Notebooks, Python (check out the reticulate package), Keras and Tensorflow, and much more. All of the tools are free and/or open-source, so you only pay the base virtual machine charge (which depends on your region and the size and power of the instance you select). Once you've launched the Ubuntu DSVM, simply log in and use systemctl to start the RStudio Server service, and then use your browser to access RStudio remotely.
If you don't need a server with all the tools the DSVM provides, you can configure your own VM with just RStudio Server and anything else you need, too. This handy blog post by Scott James Bell takes you through the steps. This includes setting up an Azure account (if you don't have one yet, click here for $200 in Azure Credits to get started), creating a virtual machine instance, and installing R, RStudio, and Shiny Server (for hosting Shiny applications) on it. Follow the link below for the complete details, and enjoy using RStudio on Azure!
My Year in Data: Running a Shiny Server on Microsoft Azure
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