AzureR packages now on CRAN

This article is originally published at https://blog.revolutionanalytics.com/

The suite of AzureR packages for interfacing with Azure services from R is now available on CRAN. If you missed the earlier announcements, this means you can now use the install.packages function in R to install these packages, rather than having to install from the Github repositories. Updated versions of these packages will also be posted to CRAN, so you can get the latest versions simply by running update.packages.

The packages are:

• AzureVM (CRAN): a package for working with virtual machines and virtual machine clusters. It allows you to easily deploy, manage and delete a VM from R. A number of templates are provided based on the Data Science Virtual Machine, or you can also supply your own template. Introductory vignette.
• AzureStor: a package for working with storage accounts. In addition to a Resource Manager interface for creating and deleting storage accounts, it also provides a client interface for working with the storage itself. You can upload and download files and blobs, list file shares and containers, list files within a share, and so on. It supports authenticated access to storage via either a key or a shared access signature (SAS). Introductory vignette.
• AzureContainers: a package for working with containers in Azure: specifically, it provides an interface to Azure Container Instances, Azure Container Registry and Azure Kubernetes Service. You can easily create an image, push it to an ACR repo, and then deploy it as a service to AKS. It also provides lightweight shells to docker, kubectl and helm (assuming these are installed). Vignettes on deploying with the plumber package and with Microsoft ML Server. 
• AzureRMR: the base package of the AzureR family for interfacing with the Azure Resource Manager and which can be extended to interface with other services. There's an introductory vignette, and another on extending AzureRMR.

Click on the first links in each bullet above for a blog post introducing each package. The introductory vignette listed with each package provides further details, and will be up-to-date for the latest version of the package.

Feedback is welcome on all of these packages, which can be found as part of the cloudyr project on Github.

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This article is originally published at https://blog.revolutionanalytics.com/
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