Microsoft today announced expanded hybrid cloud offerings, unveiling Azure Stack HCI solutions for customers that want to run virtualized applications on hyperconverged infrastructure, and signaling the general availability of Azure Data Box Edge and Dell EMC Tactical Microsoft Azure Stack.
“Customers who are taking a hybrid cloud approach are seeing real business value – I see this in organizations across the globe,” Julia White, Microsoft Azure’s corporate vice president, said in a blog post touting the new offerings. “The ability for customers to embrace both public cloud and local data center, plus edge capability, is enabling customers to improve their IT agility and maximize efficiency.”
Microsoft Azure also announced the preview of Anomaly Detector, a new Azure Cognitive Services offering, and the availability of Azure Custom Vision.
Here's more detail on the new products.
Azure Stack HCI solutions incorporates Microsoft’s existing hyperconverged infrastructure technology into the Azure Stack to allow customers to run virtualized applications on-premises, with direct access to Azure management services including cloud-based backup, disaster recovery and monitoring.
Azure Stack HCI provides the same Hyper-V-based, software-defined compute, storage and networking technologies as Azure Stack – introduced in 2017 to build and run cloud-native applications with Azure services on-premises, including disconnected locations. Azure Stack HCI includes simplified cloud access via the Azure hybrid services in Windows Admin Center.
“With Azure Stack, you can run Azure (infrastructure-as-a-service) and (platform-as-a-service) services on-premises to consistently build and run cloud applications anywhere,” Arpan Shah, Microsoft Azure’s general manager, wrote in a blog post today. “Azure Stack HCI is a better solution to run virtualized workloads in a familiar way – but with hyperconverged efficiency – and connect to Azure for hybrid scenarios such as cloud backup, cloud-based monitoring, etc.”
Azure Stack HCI solutions include support for hardware technologies such as non-volatile memory express drives, persistent memory and remote-direct memory access networking.
They’re available from 15 partners offering Microsoft-validated hardware systems: ASUS, Axellio, bluechip, DataON, Dell EMC, Fujitsu, HPE, Hitachi, Huawei, Lenovo, NEC, primeLine Solutions, QCT, SecureGUARD and Supermicro.
Azure Data Box Edge
Microsoft announced the general availability of Azure Data Box Edge, following a preview of the appliance -- an on-premises anchor point for Azure with edge compute and network data transfer capabilities -- at Microsoft Ignite in September.
Azure Data Box Edge provides a cloud-managed compute platform for containers at the edge. It lets customers process data at the edge and expedite machine learning workloads through a field programmable gate array powered by Azure Machine Learning and Intel Arria 10. It allows for the transfer of data via the internet to Azure in real-time for deeper analytics or model retraining at cloud scale -- or for long-term storage -- as does the Azure Data Box Gateway virtual appliance, which also was previewed in September and now is available through the Azure portal.
“Hybrid cloud is evolving from being only the integration of a data center with the public cloud, to becoming units of computing available at the edge, including even the world’s most remote destinations, working in concert with public cloud,” White said. “What’s compelling about the intelligent edge is many of the same patterns and principles for hybrid applications apply to edge applications.”
Data Box Edge can be racked alongside existing enterprise hardware or live in non-traditional environments from factory floors to retail aisles, according to Dean Paron, Microsoft’s Azure Data Box general manager.
“With Data Box Edge, there's no hardware to buy,” he said. “You sign up and pay as you go just like any other Azure service, and the hardware is included. If you don’t need the Data Box Edge hardware or edge compute, then the Data Box Gateway is also available as a standalone virtual appliance that can be deployed anywhere within your infrastructure.”
Dell EMC Tactical Microsoft Azure Stack also now is available in Australia and New Zealand.
The “ruggedized” and field-deployable product provides Azure-consistent cloud to tactical edge environments with limited or no network connectivity, fully mobile or high portability requirements, harsh conditions and high security requirements, according to Janaka Rangama, senior principal product technologist at Dell EMC.
Microsoft Azure announced the preview of Anomaly Detector, a new Azure Cognitive Services offering that uses artificial intelligence to detect unusual patterns or rare events in data that could translate to identifying problems like credit card fraud.
It helps developers, through a single application programming interface, to easily embed anomaly-detection capabilities into applications, to ensure high accuracy of data and allow users to identify problems in real-time and correct them to minimize loss and customer impact.
“Common use-case scenarios include identifying business incidents and text errors, monitoring (internet of things) device traffic, detecting fraud, responding to changing markets and more,” Microsoft chief of staff Anand Raman said. “Content providers can use Anomaly Detector to automatically scan video performance data specific to a customer’s (key performance indicators), helping to identify problems in an instant.”
Azure Custom Vision
Azure Custom Vision, another cognitive service to more accurately identify objects in images, also is available.
It allows developers to build, deploy and improve their image classifiers -- an Azure artificial intelligence service that apply labels to images according to their visual characteristics.
Custom Vision uses a machine learning algorithm that can be trained and, over time, used to classify new images according to the needs of an application. “Developers can train their own classifier to recognize what matters most in their scenarios or export these custom classifiers to run them offline and in real time on iOS (in CoreML), Android (in TensorFlow), and many other devices on the edge,” Raman said. “The exported models are optimized for the constraints of a mobile device providing incredible throughput while still maintaining high accuracy.