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Automated R Deployments in Azure

by Jess Panni

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It’s been great to see Microsoft embracing the R language on Azure, being able to easily operationalize R assets is changing the way organisations think about their analytical workloads.

While it is trivial to publish an R model as a web service in Azure Machine Learning, there is still no easy way to integrate this within standard ALM processes and tooling. For one of our customers this was a big issue. They use Visual Studio Team Services (VSTS) and wanted a solution that would allow them to version their R models and deploy them across dev, test and production environments.

We recently solved this problem by creating a set of reusable scripts, designed to be plugged in to VSTS or any similar automated deployment tooling, that can deploy R models to Azure ML.

The video below shows the end to end developer experience in action. In the video we use the recently released R Tools for Visual Studio, but you use any R development environment such as R Studio.

Automated R Deployments to Azure ML from endjin on Vimeo.

About the author

Jess has over 18 years’ experience helping companies succeed through the smart use of technology. He has spent most of his career working for leading Microsoft partners across the UK and Australia and is now Principal at endjin, working with clients to envision and execute disciplined innovation programmes. You can follow Jess on twitter.