Microsoft Azure is getting new capabilities to handle big data workloads. The company announced a host of new features in a blog post today that are all targeted at organizations that need to handle large amounts of data in the cloud.
First off, the cloud platform’s Machine Learning service, which launched in a preview last year, has now entered general availability. The service is designed to make it easier for people to use machine learning techniques to analyze large sets of data in the cloud, without requiring the help of specially-trained data scientists. It’s an important part of Microsoft’s overall cloud strategy, since higher level services like this one fetch a higher price than Azure’s lower level infrastructure and platform services.
In addition, organizations that bring machine learning workloads to Azure may be more likely to use Microsoft’s other cloud services, rather than turn to a competitor like Amazon Web Services or Google Cloud Platform.
HDInsight, Microsoft’s cloud-hosted version of Apache Hadoop, got an update today as well. Microsoft launched a preview of HDInsight on Linux, following its expansion last year of the flavors of Linux available through Azure. In addition, today’s update brings the general availability of Apache Storm on HDInsight, along with support for Hadoop 2.6. Microsoft also opened up general availability for scaling a HDInsight cluster while it’s running, so users don’t have to spin up a new instance in order to change the number of nodes in a cluster.
Finally, Microsoft is partnering with Informatica to bring its Informatica Cloud agent for Linux and Windows virtual machines to the Azure Marketplace. Informatica’s tools are designed to help businesses integrate cloud data from a variety of sources including on-premise data centers and other cloud providers.