If you want to run R in the cloud, you can of course run it in a virtual machine in the cloud provider of your choice. And you can do that in Azure too. But Azure provides seven dedicated services that provide the ability to run R code, and you can learn all about them in the new R Developer's Guide to Azure at Microsoft Docs. The services include:
- Data Science Virtual Machine: a customized VM to use as a data science workstation or as a custom compute target. This includes Microsoft R Open, Microsoft Machine Learning Server, and Microsoft ML Services in SQL Server, which can also be run locally.
- ML Services on HDInsight: a cluster-based system for running R analyses on large datasets across many nodes.
- Azure Databricks: a collaborative Spark environment that supports R and other languages.
- Azure Machine Learning Studio: a drag-and-drop app for Azure's machine learning experiments, that supports custom R scripts.
- Azure Batch: a variety of options for economically running R code across many nodes in a cluster.
- Azure Notebooks: a no-cost (but limited) cloud-based version of Jupyter notebooks.
- Azure SQL Database: to run R scripts inside of the SQL Server database engine.
Click on the links above for detailed documentation on how to run R in each of these services. Like all Microsoft Docs this guide is hosted in Github, so if you have suggestions for modifications or additions to this document, you can use the “Content Feedback” link to provide suggestions directly in the repository.
Microsoft Docs: R developer's guide to Azure