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Autoscale for Azure HDInsight is now generally available across all regions for Apache Spark and Hadoop workloads. This feature makes it possible to operate your big data analytics workloads in a more cost-efficient and productive way, so you can drive higher use of your HDInsight clusters and pay only for what you need.
Target availability: Q4 2019
The accelerated writes feature in the HDInsight HBase cluster attaches a Premium SSD managed disk to every region server (worker node). Write ahead logs are configured to be written to Hadoop Distributed File System (HDFS) mounted on premium managed disks instead of standard Azure page blobs. Premium managed disks are SSD-based and offer excellent I/O performance with fault tolerance. Using premium managed disks for WALs allows us to separate write ahead log storage from Apache HBase data storage.
A new Azure HDInsight capability enables you to customize and upgrade your Azure SQL Database for Apache Ambari during cluster creation.
Target availability: Q4 2019
The integration of Azure HDInsight and Azure Firewall, in order to restrict outbound traffic from the cluster to unauthorized destinations, is now generally available.
Target retirement date: October 31, 2019
Azure HDInsight will deprecate G-series virtual machines (VMs) on October 31, 2019. After this date, you won't be able to create any new clusters using G-series VMs or to scale up clusters having G-series nodes.
Azure CLI support for Azure HDInsight is now generally available. This enables administrators to easily manage their HDInsight clusters using simple Azure CLI commands.
Azure HDInsight now supports Apache Spark 2.4 and Apache Kafka 2.1. You can choose the Spark or the Kafka version that you want during cluster creation in the Azure portal. Both updates come with several new features, hundreds of bug fixes and improvements.
Azure HDInsight has updated against the vulnerabilities that affect the Linux kernel.
We are pleased to announce the integration of VSCode Python extension to handle PySpark interactive for HDInsight in VSCode. The Azure HDInsight Tools for VSCode leverages the Python extension to…
HDInsight for VSCode continues to boost the experience of Hive users with self-service exploratory capabilities. The HDInsight explorer in VSCode not only empowers you to browse Hive databases across…
We’ve corrected billing for Azure SQL Data Warehouse and other Azure services that impacted EA customers only.
HBase accelerated writes significantly improves the value proposition for low-latency, high- throughput NoSQL workloads.
Autoscale which automatically scales your Spark, Hive, or MapReduce HDInsight clusters up or down based on load or a pre-defined schedule, is now in preview.
We are introducing some important changes to support more fine-grained role-based access to sensitive configuration information from HDInsight clusters. As part of these changes, some user action may be required.
Four regions are available in China: China East, China North, China North 2 and China East 2.
New features in Hadoop 3 provide significant improvements to performance, stability, and availability, helping reduce total cost of ownership and accelerating time-to-value.
The networking resources (such as NICs and load balancers) for new Azure HDInsight clusters created in a virtual network are now provisioned in the same HDInsight cluster resource group.
Across the world, Azure HDInsight is available in 29 public regions, including France Central.
Ev3 and ESv3 series VMs are available in Azure HDInsight.
Azure HDInsight is now available in US DoD East, US DoD Central, and US Gov Texas.
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