AzureDSVM is an R package that offers convenient harness of Azure DSVM, remote execution of scalable and elastic data science work, and monitoring of on-demand resource consumption.
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The AzureDSVM (Azure Data Science Virtual Machine) is an R Package for Data Scientists working with the Azure compute platform as a complement to the underlying AzureSMR for controlling Azure Data Science Virtual Machines.

Azure Data Science Virtual Machine (DSVM) is a powerful data science development environment with pre-installed tools and packages that empower data scientists for convenient data wrangling, model building, and service deployment.

The R package of AzureDSVM aims at offering functions that can be conveniently used by R data scientists for operating and using Azure Data Science Virtual Machine (DSVM) elastically and economically within local R session.

To install the package from github:


Help pages are also provided for all functions within the package. With RStudio for example type AzureDSVM into search when the package is loaded to see a list of functions/help pages or else


Note: The package will work with any open source R Session or with Microsoft R extensions.


  • Elasiticity

    • Deployment of a DSVM with customized information such as machine name, machine size (with compute/memory optimized general-purpose CPU, Nvidia K80/M60 GPU, etc.), operating system (Windows Server 2016, Ubunbut 16.04, and CentOS), authentication method (public key based or password based), etc.
    • Enjoy all benefits of a Windows/Linux DSVM. E.g., all tools for data science work such as R/Python/Julia programming languages, SQL Server, Visual Studio with RTVS, etc., remote working environment via RStudio Server or Jupyter Notebook interface, and machine learning & artificial intelligence packages such as Microsoft CNTK, MXNet, and XGBoost.
    • Execution of R analytics on DSVM(s) with various Microsoft R Server computing contexts such as "local parallel" and "cluster parallel".
    • Seamless interaction with remote R Server session with mrsdeploy functions.
    • Post-deployment installation of extension for customizing system environment, reinstalling/uninstalling software, etc.
  • Scalability

    • Deployment of a collection of heterogeneous DSVMs for a group of data scientists.
    • Scale up DSVM and form them into a cluster for parallel/distributed computation with Microsoft R Server backend.
  • Usability

    • Deploy, start, stop, and delete DSVM(s) on demand.
    • Monitor data consumption and estimate expense of using DSVM(s) with hourly aggregation granularity.


To get started with this package, see the Vignettes:

Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact with any additional questions or comments.