Announcements

Azure HC-series Virtual Machines are now generally available in the West US 2 and East US regions. HC-series virtual machines (VMs) are optimized for the most at-scale, computationally intensive HPC applications.

We’re excited to share that Forrester has named Microsoft as a leader in The Forrester Wave™: Database-as-a-service, Q2 2019. This decision is based on their evaluation of Azure relational and non-relational databases.

For many customers around the world, securely connecting from the outside to workloads and virtual machines on private networks can be challenging.

At Microsoft Build 2019, we announced the general availability of Azure Shared Image Gallery, making it easier to manage, share, and distribute custom virtual machine (VM) images in Azure.

For businesses today, data is indispensable. Innovative ideas in manufacturing, health care, transportation, and financial industries are often the result of capturing and correlating data from multiple sources.

Azure Deployment Manager is a new set of features for Azure Resource Manager that greatly expands your deployment capabilities.

Calico policies lets you define filtering rules to control flow of traffic to and from Kubernetes Pods.

One of the biggest attack surfaces for workloads running in the public cloud is connections to and from the public internet.

Innovation at scale is a common challenge facing large organizations. A key contributor to the challenge is the complexity in coordinating the sheer number of apps and environments.

We’re excited to announce the public preview of Azure App Configuration, a new service aimed at simplifying the management of application configuration and feature flighting for developers and IT.

Today, I’m excited to announce the general availability of Azure NetApp Files, the industry’s first bare-metal cloud file storage and data management service.

We are excited to announce the General Availability of the autoscale feature for Azure HDInsight. This feature enables enterprises to become more productive and cost-efficient by automatically scaling clusters up or down based on the load or a customized schedule.