Check out the below recap of this week’s open source related community news, product announcements, popular docs, and demos from around Microsoft.
Anything else you’d like to hear about? Let us know in the comments.
Get your speaker proposal in for OSCON 2018: OSCON returns to Portland this summer and we hope to see you there. The call for speakers is still open until next Tuesday, January 30. Regardless of origin or community, all innovative and emerging open source projects, from blockchain to machine learning frameworks, will be at the center of OSCON 2018. Submit your proposal here.
H20.ai on Azure HDInsight: Azure HDInsight is a Hadoop-based fully-managed cloud service that makes it easy, fast, and cost-effective to process massive amounts of data. H2O’s machine learning platform is open source and works with Spark 2.0+, sparklyr, and PySpark. In this video, you’ll learn on how you can install H20.ai on Azure HDInsight to build a big data application.
Improved GitHub builds in Visual Studio Team Services: Did you know that Visual Studio Team Services (VSTS) now supports building from GitHub forks? The VSTS team strengthened integration with GitHub by enabling you to build pull requests from repository forks on GitHub.com and continuously integrate from GitHub Enterprise through an official build source. Check out the docs here.
Deploy Azure Functions as an IoT Edge module: You can use Azure Functions to deploy code that implements your business logic directly to your IoT Edge devices. This tutorial walks you through creating and deploying an Azure Function that filters sensor data on the simulated IoT Edge device that you created in the Deploy Azure IoT Edge on a simulated device on Windows or Linux tutorials. In this tutorial, you learn how to use Visual Studio Code (VSCode) to create an Azure Function, use VSCode and Docker to create a Docker image, and publish it to your registry. Read more.
Accelerated Spark on GPU-enabled clusters in Azure: Along with the recent release of the latest GPU SKUs, the Azure team expanded support running Spark on a GPU-enabled cluster using the Azure Distributed Data Engineering Toolkit (AZTK). In a single command, AZTK allows you to provision on demand GPU-enabled Spark clusters on top of Azure Batch’s infrastructure, helping you take your high performance implementations that are usually single-node only and distribute it across your Spark cluster. Check out the Azure blog for more.
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