Kategorie: Microsoft Azure

Extending the power of Azure AI to Microsoft 365 users

Today, Yusuf Mehdi, Corporate Vice President of Modern Life and Devices, announced the availability of new Microsoft 365 Personal and Family subscriptions. In his blog, he shared a few examples of how Microsoft 365 is innovating to deliver experiences powered by artificial intelligence (AI) to billions of users every day. Whether through familiar products like Outlook and PowerPoint, or through new offerings such as Presenter Coach and Microsoft Editor across Word, Outlook, and the web, Microsoft 365 relies on Azure AI to offer new capabilities that make their users even more productive.

What is Azure AI?

Azure AI is a set of AI services built on Microsoft’s breakthrough innovation from decades of world-class research in vision, speech, language processing, and custom machine learning. What is particularly exciting is that Azure AI provides our customers with access to the same proven AI capabilities that power Microsoft 365, Xbox, HoloLens, and Bing. In fact, there are more than 20,000 active paying customers—and more than 85 percent of the Fortune 100 companies have used Azure AI in the last 12 months.

Azure AI helps organizations:

Develop machine learning models that can help with scenarios such as demand forecasting, recommendations, or fraud detection using Azure Machine Learning.
Incorporate vision, speech, and language understanding capabilities into AI applications and bots, with Azure Cognitive Services and Azure Bot Service.
Build knowledge-mining solutions to make better use of untapped information in their content and documents using Azure Search.

Microsoft 365 provides innovative product experiences with Azure AI

The announcement of Microsoft Editor is one example of innovation. Editor, your personal intelligent writing assistant is available across Word, Outlook.com, and browser extensions for Edge and Chrome. Editor is an AI-powered service available in more than 20 languages that has traditionally helped writers with spell check and grammar recommendations. Powered by AI models built with Azure Machine Learning, Editor can now recommend clear and concise phrasing, suggest more formal language, and provide citation recommendations.

Additionally, Microsoft PowerPoint utilizes Azure AI in multiple ways. PowerPoint Designer uses Azure Machine Learning to recommend design layouts to users based on the content on the slide. In the example image below, Designer made the design recommendation based on the context in the slide. It can also can intelligently crop objects and people in images and place them in optimal layout on a slide. Since its launch, PowerPoint Designer users have kept nearly two billion Designer slides in their presentation.

You can take a closer look at how the PowerPoint team built this feature with Azure Machine Learning in this blog.

PowerPoint also uses Azure Cognitive Services such as the Speech service to power live captions and subtitles for presentations in real-time, making it easier for all audience members to follow along. Additionally, PowerPoint also uses Translator Text to provide live translations into over 60 languages to reach an even wider audience. These AI-powered capabilities in PowerPoint are providing new experiences for users, allowing them to connect with diverse audiences they were unable to reach before.

These same innovations can also be found in Microsoft Teams. As we look to stay connected with co-workers, Teams has some helpful capabilities intended to make it easier to collaborate and communicate while working remotely. For example, Teams offers the ability of live captioning meetings, which leverages the Speech API for speech transcription. But it doesn’t stop there. As you saw with PowerPoint, Teams also uses Azure AI for live translations when you set up Live Events. This functionality is particularly useful for company town hall meetings or even for any virtual event with up to ten thousand attendees, allowing presenters to reach audiences worldwide

These are just a few of the ways Microsoft 365 applications utilize Azure AI to deliver industry-leading experiences to billions of users. When you consider the fact that other Microsoft products such as Microsoft 365, Xbox, HoloLens 2, Dynamics 365, and Power Platform all rely on Azure AI, you begin to see the massive scale and the breadth of scenarios that only Azure can offer. Best of all, these same capabilities are available to anyone in Azure AI. 
Quelle: Azure

How Azure Machine Learning enables PowerPoint Designer

If you use Office 365, you have likely seen the Microsoft PowerPoint Designer appear to offer helpful ideas when you insert a picture into a PowerPoint slide. You may also have found it under the Home tab in the ribbon. In either case, Designer provides users with redesigned slides to maximize their engagement and visual appeal. These designs include different ways to represent your text as diagrams, layouts to make your images pop, and now it can even surface relevant icons and images to bring your slides to the next level. Ultimately, it saves users time while enhancing their slides to create stunning, memorable, and effective presentations.

Designer uses artificial intelligence (AI) capabilities in Office 365 to enable users to be more productive and unlock greater value from PowerPoint. It applies AI technologies and machine learning based techniques to suggest high-quality professional slide designs. Content on slides such as images, text, and tables are analyzed by Designer and formatted based on professionally designed templates for enhanced effectiveness and visual appeal.

The data science team, working to grow and improve Designer, is comprised of five data scientists with diverse backgrounds in applied machine learning and software engineering. They strive to continue pushing barriers in the AI space, delivering tools that make everyone’s presentation designs more impactful and effortless. They’ve shared some of the efforts behind PowerPoint Designer, just so we can get a peek under the hood of this powerful capability.

PowerPoint Designer capabilities

Designer has been processing user requests in the production environment for several years and uses machine learning models for problems such as image categorization, content recommendation, text analysis, slide structure analysis, suggestion ranking, and more. Since its launch, Designer users have kept 1.7 billion Designer slides in their presentations. This means the team needs a platform to run their models at a large scale. Plus, the Designer team is regularly retraining models in production and driving model experimentation to provide optimized content recommendations.

Recently, the data analysis and machine learning team within PowerPoint started leveraging Azure Machine Learning and its robust MLOps capabilities to build models faster and at scale, replacing local development. Moving toward content suggestions, like background images, videos, and more, requires a highly performant platform, further necessitating the shift towards Azure Machine Learning.

The team uses Azure Machine Learning and its MLOps capabilities to create automated pipelines that can be iterated on, without disrupting the user experience. The pipeline starts at the Azure Data Lake, where the data is stored. From there, the team gathers data and preprocesses it—merging data from different sources and transforming raw data into a format that models can understand. Utilizing the Azure Machine Learning distributed training, they retrain their current models weekly or monthly. Distributed training allows the team to train models in parallel across multiple virtual machines (VMs) and GPUs (graphic processing units). This saves the team considerable time to ensure the model training doesn’t disrupt the user experience for the data science team, so they can focus on other objectives like experimentation.

The team does experimentation in parallel as well—trying variants, or hyperparameters, and comparing results. The final model is then put back into Azure Data Lake and downloaded to Azure Machine Learning.

The following diagram shows the conceptualized, high-level architecture of data being used from local caches in Azure Data Lake to develop machine learning models on the Azure Machine Learning. These models are then integrated into the micro-service architecture of the Designer backend service that presents PowerPoint users with intelligent slide suggestions.

Benefits of Azure Machine Learning for the PowerPoint team

The PowerPoint team decided to move its workloads over to the Azure Machine Learning based on the following capabilities:

Supports Python notebooks which can be accessed on any machine through the browser.
Natively supports running the latest TensorFlow and PyTorch-based algorithms and pre-trained models.
Experimentation is very easy to set up with minimal ramp-up time It allows execution locally or on the cloud seamlessly thereby presenting developers with a hybrid environment.
Azure Machine Learning is one of Microsoft’s key AI investments.

Follow the Azure blog to be the first to know when features leveraging new models that recommend more types of content, such as image classification and content recommendations, are released.

Azure Machine Learning | Azure Data Lake | Azure Machine Learning pipelines

Learn more

Learn more about Azure Machine Learning.

Get started with a free trial of Azure Machine Learning.
Quelle: Azure

Announcing general availability of incremental snapshots of Managed Disks

We're announcing the general availability of incremental snapshots of Azure Managed Disks. Incremental snapshots are a cost-effective, point-in-time backup of managed disks. Unlike current snapshots, which are billed for the full size, incremental snapshots are billed for the delta changes to disks since the last snapshot and are always stored on the most cost-effective storage, Standard HDD storage irrespective of the storage type of the parent disks. For additional reliability, Managed Disks are also stored on Zone Redundant Storage (ZRS) by default in regions that support ZRS.

Incremental snapshots provide differential capability, enabling customers and independent solution vendors (ISVs) to build backup and disaster recovery solutions for Managed Disks. It allows you to get the changes between two snapshots of the same disk, thus copying only changed data between two snapshots across regions, reducing time and cost for backup and disaster recovery. Incremental snapshots are accessible instantaneously; you can read the underlying data of incremental snapshots or restore disks from them as soon as they are created. Azure Managed Disk inherit all the compelling capabilities of current snapshots and have a lifetime independent from their parent managed disks and independent of each other.

Examples of incremental snapshots

Let’s look at a few examples to understand how the incremental snapshots help you reduce cost.

If you were using a disk with 100 GiB already occupied and added 20 GiB of data to the disk, you took the first incremental snapshot before 20 GiB of data was added to the disk, making the first copy occupy 100 GiB of data. Then 20 GiB of data was added on the disk before you created the second incremental snapshot. Now with incremental snapshots, the second snapshot occupies only 20 GiB and you’re billed for only 20 GiB compared to the current full snapshots that would have occupied 120 GiB and billed for 120 GiB of data, reducing your cost.

The second incremental snapshot references 100 GiB of data from the first snapshot. When you restore the disk from the second incremental snapshot, the system can restore 120 GiB of data by copying 100 GiB of data from the first snapshot and 20 GiB of data from the second snapshot.

Let's now understand what happens when 5 GiB of data was modified on the disk before you took the third incremental snapshot. The third snapshot then occupies only 5 GiB of data, references 95 GiB of data from the first snapshot, and references 20 GiB of data from the second snapshot.

Now, if you deleted the first incremental snapshot the second and the third snapshots continue to function normally as incremental snapshots are independent of each other. The system merges the data occupied by the first snapshot with the second snapshot under the hood to ensure that the second and the third snapshots are not impacted due to the deletion of the first snapshot. The second snapshot now occupies 120 GiB of data.  Since we launched the preview for incremental snapshot in September 2019, our ISVs have used this capability on a wide range of workloads to reduce the cost and time for backup and disaster recovery.

Below are some quotes from partners in our preview program:

“Zerto has been helping enterprise customers who leverage Microsoft Azure become IT Resilient for years. Extending Azure Managed Disks with the incremental snapshots API has enabled Zerto to improve upon industry-best RTOs and RPOs in Azure. The powerful capabilities of Azure Managed Disks enable Zerto to meet the scale and performance requirements of a modern enterprise. With Zerto and Microsoft’s continued collaboration and integration, we’ll continue to pave the way for IT Resilience in the public cloud.” – Michael Khusid, Director of Product Management, Zerto, Inc.

“Combining Rubrik Azure data protection with the latest Microsoft API delivering incremental snapshots, we reduce the time and cost for backup and recovery, and help our joint customers achieve 18x lower costs, high storage efficiency, reduced network traffic, and hourly RPOs. Together, Rubrik and Microsoft enable our enterprise customers to accelerate their cloud journey while unlocking productivity and better cloud economics.” – Shay Mowlem, Senior Vice President of Product & Strategy, Rubrik

“With incremental snapshots of Azure managed disks, Dell EMC PowerProtect Cloud Snapshot Manager (CSM) customers will be able to reduce their backup times and storage costs significantly. Also, they’ll be able to achieve much shorter recovery time objectives with instant access to their data from snapshots. Designed for any-size cloud infrastructure, CSM provides global visibility and control to gain insights into data protection activities across Azure subscriptions, making CSM a great solution for protecting customer workloads in public cloud environments.” – Laura Dubois, vice president, product management, Dell Technologies Data Protection

Availability and pricing

You can now create incremental snapshots in all regions, including sovereign regions.

Incremental snapshots are charged per GiB of the storage occupied by the delta changes since the last snapshot. For example, if you're using a managed disk with a provisioned size of 128 GiB, with 100 GiB used, the first incremental snapshot is billed only for the used size of 100 GiB. 20 GiB of data is added on the disk before you create the second snapshot. Now, the second incremental snapshot is billed for only 20 GiB.

Incremental snapshots are always stored on standard storage irrespective of the storage type of parent managed disks and charged as per the pricing of standard storage. For example, incremental snapshots of a Premium SSD Managed Disk are stored on standard storage. They are stored on ZRS by default in regions that support ZRS. Otherwise, they are stored on locally redundant storage (LRS). The per GB pricing of both the LRS and ZRS options is the same.

Incremental snapshots cannot be stored on premium storage. If you are using current snapshots on premium storage to scale up virtual machine deployments, we recommend you use custom images on standard storage in Shared Image Gallery. This will help you to achieve higher scale with lower cost.

You can visit the Managed Disk Pricing for more details about the snapshot pricing.

Getting started

Create an incremental snapshot using CLI.
Create an incremental snapshot using PowerShell.

Quelle: Azure

Azure Container Registry Private Link support preview for virtual networks

Azure Container Registry announces preview support for Azure Private Link, a means to limit network traffic of resources within the Azure network.

With Private Link, the registry endpoints are assigned private IP addresses, routing traffic within a customer-defined virtual network. Private network support has been one of the top customer asks, allowing customers to benefit from the Azure management of their registry while benefiting from tightly controlled network ingress and egress.
  

Private Links are available across a wide range of Azure resources with more coming soon, allowing a wide range of container workloads with the security of a private virtual network.

Private Endpoints and Public Endpoints

Private Link provides private endpoints to be available through private IPs. In the above case, the contoso.azurecr.io registry has a private IP of 10.0.0.6 which is only available to resources in contoso-aks-eastus-vnet. This allows the resources in this VNet to securely communicate. The other resources may be restricted to resources only within the VNet.

At the same time, the public endpoint for the contoso.azurecr.io registry may still be public for the development team. In a coming release, Azure Container Registry (ACR) Private Link will support disabling the public endpoint, limiting access to only private endpoints, configured under private link.

Cross tenant manual approval support

Customers looking to establish a private link between two Azure tenants, where an Azure container registry is in one tenant and while container hosts are in other tenants can use the Private Link Manual Approval workflow. This workflow enables many Azure services, including Azure Machine Learning, to securely interact with your registry. Development teams working in different subscriptions and tenants may also utilize private link manual approval to grant access.

Service Endpoints and Private Links

ACR Service Endpoint preview support was released in March 2019. Service Endpoints provide access from Azure VNets through IP tagging. All traffic to the service endpoint is limited to the Azure backbone network through routing. The public endpoint still exists; however, firewall rules limit public access. Private Link capabilities take this a step further by providing a private endpoint (IP address). As Private Links are more secure and a superset of capabilities of Service Endpoints, Private link support will replace Azure Container Registry Service Endpoint support. While both Service Endpoints and Private Link are currently in preview, we plan to release Private Link capabilities as generally available shortly. We encourage Service Endpoint customers to evaluate ACR Private Link capabilities.

Preview support and limitations

During the preview period, private link support is limited to registries that are not geo-replicated. The feature will move to general availability as we assess feedback and geo-replication support is complete.

We’ve heard clearly that customers requiring private networks also require production support. As such, all support requests will be honored through standard support channels.

Regional support and pricing

Azure Container Registry Private Link support is available across 28 regions through the premium tier.

Additional links:

Learn more about Azure Container Registry.
Azure Container Registry pricing.
Configure Azure Private Link for an Azure Container Registry.

Quelle: Azure

Azure Government Secret accredited at DoD IL6, ICD 503 with IaaS and PaaS

Accelerate classified missions with unparalleled connectivity, high availability, and resiliency across three regions with more than 35 services

Azure Government Secret recently achieved Provisional Authorization (PA) at Department of Defense Impact Level 6 (IL6) and Intelligence Community Directive (ICD) 503 with facilities at ICD 705. We’re also announcing a third region to enable even higher availability for national security missions to stay ahead of their unique threats.

Built exclusively for the needs of US government and operated by cleared US citizens, Azure Government Secret delivers dedicated regions to maintain the security and integrity of classified Secret workloads while enabling reliable access to critical data. The first cloud natively connected to classified networks; Azure Government Secret enables customers to leverage options for private, resilient, high-bandwidth connectivity.

Protect national security production workloads with geodiversity across three regions

Azure Government Secret is designed for the unique requirements of critical national security workloads that cannot be served out of a single geographic location. To provide the geodiversity required, Azure Government Secret delivers across three dedicated regions for US Federal Civilian, Department of Defense (DoD), Intelligence Community (IC), and US government partners working within Secret enclaves. These dedicated Azure regions are located over 500 miles apart to enable applications to stay running in the face of a disaster without a break in continuity of operations.

In addition, these regions provide greater choice when working across multiple locations and delivering cloud-to-edge scenarios. With comprehensive cloud services Azure Government Secret enables faster innovation for the mission from cloud to tactical edge meeting the critical availability needs of the warfighter.

Enabling classified missions at scale with more than 35 services

Designed and built for Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) and Marketplace solutions, Azure Government Secret provides a broad range of commercial innovation for classified workloads.­ Some of the services include: identity, analytics, security, and high performance computing to support advanced artificial intelligence (AI) and machine learning.

Operated by cleared US citizens, these new regions are part of Azure Government, delivering a familiar, consistent experience and alignment with existing resellers and programs. Eligible customers can also leverage cleared Microsoft cloud support for their workloads.

Gain speed by connecting directly or extending on-premises networks

With Azure Government Secret, customers can connect natively to classified networks or leverage options for private, resilient, high-bandwidth connectivity using ExpressRoute and ExpressRoute Direct:

Native connection: Agencies with direct connections through US government classified networks can connect natively to Azure Government Secret.
ExpressRoute: Extend on-premises networks into Azure Government Secret regions over a private connection facilitated by a connectivity provider with ExpressRoute.
ExpressRoute Direct: Get the ability to connect directly into Azure Government Secret locations using ExpressRoute Direct.

Continued investments in commercial parity across data classifications

In addition to serving mission customers at DoD IL6 and ICD 503, we continue to invest in rapidly delivering new Azure Government capabilities to support mission needs across all data classifications for any US government customer. In the last six months we’ve continued our drive toward commercial parity, adding hundreds of features and launching 40+ new services and 101 total services in FedRAMP High, with more to come across Azure commercial, Azure Government and Azure Government Secret.

These continued investments enable customers across the full spectrum of government, including departments in every state, all the federal cabinet agencies, and each military branch, modernize their IT to better achieve their missions.

To learn more about Azure Government Secret contact us or visit Azure Government for national security.
Quelle: Azure

Azure Dedicated Host: New capabilities and benefits

Late last year, we’ve announced the general availability of Azure Dedicated Hosts. This blog provides an update regarding the new and recently added capabilities since we introduced Azure Dedicated Hosts in preview.

Azure Dedicated Host provides a single-tenant physical server to run your Azure Virtual Machines for Windows Server and Linux. With Azure Dedicated Host, you can address specific compliance requirements while increasing visibility and control over your underlying infrastructure.

What’s new

Save costs with Azure Dedicated Hosts reservations

We recently introduced the ability for you to purchase Azure reservations for Dedicated Hosts. You are now able to reduce costs by buying Azure Dedicated Hosts reservations. The reservation discount is applied automatically to the number of running dedicated hosts that match the reservation scope and attributes. You don't need to assign a reservation to a specific dedicated host to get the discounts. You may also delete and create hosts and have the reservation apply to the hosts already deployed at any given time.

The Azure Dedicated Hosts pricing page contains the complete list of Dedicated Hosts SKUs, their CPU information, and various pricing options including Azure reservations discounts.

Azure Dedicated Host SKUs, unlike Azure Virtual Machines, are defined based on the virtual machine (VM) series and hardware generation. With Azure Dedicated Hosts, your reservation will automatically apply to any host SKUs supporting the same VM series. For example, if you acquired a reservation for Dsv3_Type1 dedicated host, you would be able to use it with Dsv3_Type2 dedicated hosts.

Maintenance control for platform updates supports Azure Dedicated Hosts

The maintenance control feature for Azure Dedicated Hosts gives control over platform maintenance operations to customers with highly sensitive workloads. Using this feature, customers can manage platform updates that don’t require a reboot. Maintenance control batch updates into one update package and gives you the option to delay platform updates and apply them within a 35-day rolling window.

You can take advantage of this new capability, by creating a maintenance configuration object and then apply it to your dedicated hosts. Then, you can check for pending updates and apply them at the host level. All VMs assigned to the host will be impacted at the same time.

Prior to applying the maintenance, you can check the impact type and expected duration of the impact

To learn more, refer to our documentation Control updates with Maintenance Control.

More options with new SKUs

Since the preview was announced, we have added support for additional VM series and host types. We’re currently supporting both Intel and AMD SKUs with a variety of VM series: Dsv3, Esv3, Dasv4, Easv4, Fsv2, Lsv2, and Msv2. This will enable our customers to run a broad range of workloads on Dedicated Hosts including and not limited to general purpose or memory, storage, and compute intensive applications. 

Visit the Azure Dedicated Host pricing page to learn more about these new SKUs and the options available to you.

Resource Health Activity Log Alerts for Dedicated Hosts

Azure Resource Health alerts can notify you in near real-time when your dedicated hosts experience a change with respect to their health status. Creating Resource Health alerts programmatically let users create and customize alerts in bulk. You can create an action group and specify the steps to take once an alert is triggered. Follow the steps to create activity log alerts using Azure Resource Manager Template and remember to modify the template to include resources of type dedicated hosts.

Get started

Start by visiting the Azure Dedicated Host page, read more in the documentation page, or watch a video introduction to Azure Dedicated Host.

Deploy Dedicated Host using Azure CLI, the Azure portal, Azure REST API, or Azure PowerShell.
Quelle: Azure

Keeping your cloud deployments secure during challenging times

As the world comes together to combat COVID-19, and remote work becomes a critical capability for many companies, customers have asked us how to best maintain the security posture of their cloud assets while enabling more remote workers to access them.

Misconfiguration of cloud security controls has been at the root of several recent data breaches, so it’s extremely important to continue monitoring your security posture as usage of cloud assets increases.

To help you prioritize the actions that you need to take, we are listing three common scenarios for remote workers and how to leverage Azure Security Center security controls to prioritize relevant recommendations for these scenarios:

1. As more users need to access resources remotely, you need to ensure that Multi-Factor Authentication (MFA) is enabled to enhance their identity protection.

Azure Security Center has a security control called Enable MFA, ideally you should remediate all recommendations that are part of this security control, as shown below:

2. Some users might need remote access via RDP or SSH to servers that are in your Azure infrastructure.

Instead of allowing full 24 x 7 access to those servers, ensure that you are using Just-In-Time (JIT) VM access to those servers. Make sure to review the Secure management ports control in Azure Security Center and remediate the recommendations that are relevant for this scenario.

3. Some of the workloads (servers, containers, databases) that will be accessed remotely by users might be missing critical security updates.

Review the Remediate vulnerabilities control in Azure Security Center to prioritize the updates that must be installed. Make sure to review the result of all recommendations in built-in vulnerability assessment and remediate those items.

Security posture management is an ongoing process. Review your secure score to understand your progress towards a fully compliant environment.

Users of Azure are likely just a portion of your user base. Below is additional guidance on enabling and securing remote work for the rest of your organization:

The top 9 ways Microsoft IT is enabling remote work for its employees
Staying productive while working remotely with Microsoft Teams
Working remotely during challenging times
Work remotely, stay secure—guidance for CISOs

Quelle: Azure

Microsoft powers transformation at NVIDIA’s GTC Digital Conference

The world of supercomputing is evolving. Work once limited to high-performance computing (HPC) on-premises clusters and traditional HPC scenarios, is now being performed at the edge, on-premises, in the cloud, and everywhere in between. Whether it’s a manufacturer running advanced simulations, an energy company optimizing drilling through real-time well monitoring, an architecture firm providing professional virtual graphics workstations to employees who need to work remotely, or a financial services company using AI to navigate market risk, Microsoft’s collaboration with NVIDIA makes access to NVIDIA graphics processing units (GPU) platforms easier than ever.

These modern needs require advanced solutions that were traditionally limited to a few organizations because they were hard to scale and took a long time to deliver. Today, Microsoft Azure delivers HPC capabilities, a comprehensive AI platform, and the Azure Stack family of hybrid and edge offerings that directly address these challenges.

This year during GTC Digital, we’re spotlighting some of the most transformational applications powered by NVIDIA GPU acceleration that highlight our commitment to edge, on-prem, and cloud computing. Registration is free, so sign up to learn how Microsoft is powering transformation.

Visualization and GPU workstations

Azure enables a wide range of visualization workloads, which are critical for desktop virtualization as well as professional graphics such as computer-aided design, content creation, and interactive rendering. Visualization workloads on Azure are powered by NVIDIA’s world-class GPUs and Quadro technology, the world’s preeminent visual computing platform. With access to graphics workstations on Azure cloud, artists, designers, and technical professionals can work remotely, from anywhere, and from any connected device. See our NV-Series virtual machines (VMs) for Windows and Linux.

Artificial intelligence

We’re sharing the release of the updated execution provider in ONNX Runtime with integration for NVIDIA TensorRT 7. With this update, ONNX Runtime can execute open Open Neural Network Exchange (ONNX) models on NVIDIA GPUs on Azure cloud and at the edge using the Azure Stack Edge, taking advantage of the new features in TensorRT 7 like dynamic shape, mixed precision optimizations, and INT8 execution.

Dynamic shape support enables users to run variable batch size, which is used by ONNX Runtime to process recurrent neural network (RNN) and bit error test rate (BERT) models. Mixed precision and INT8 execution are used to speed up execution on the GPU, which enables ONNX Runtime to better balance the performance across CPU and GPU. Originally released in March 2019, TensorRT with ONNX Runtime delivers better inferencing performance on the same hardware when compared to generic GPU acceleration.

Additionally, the Azure Machine Learning service now supports RAPIDS, a high-performance GPU execution accelerator for data science framework using the NVIDIA CUDA platform. Azure developers can use RAPIDS in the same way they currently use other machine learning frameworks, and in conjunction with Pandas, Scikit-learn, PyTorch, and TensorFlow. These two developments represent major milestones towards a truly open and interoperable ecosystem for AI. We’re working to ensure these platform additions will simplify and enrich those developer experiences.

Edge

Microsoft provides various solutions in the Intelligent Edge portfolio to empower customers to make sure that machine learning not only happens in the cloud but also at the edge. The solutions include Azure Stack Hub, Azure Stack Edge, and IoT Edge.

Whether you are capturing sensor data and inferencing at the Edge or performing end-to-end processing with model training in Azure and leveraging the trained models at the edge for enhanced inferencing operations Microsoft can support your needs however and wherever you need to.

Supercomputing scale

Time-to-decision is incredibly important with a global economy that is constantly on the move. With the accelerated pace of change, companies are looking for new ways to gather vast amounts of data, train models, and perform real-time inferencing in the cloud and at the edge. The Azure HPC portfolio consists of purpose-built computing, networking, storage, and application services to help you seamlessly connect your data and processing needs with infrastructure options optimized for various workload characteristics.

Azure Stack Hub announced preview

Microsoft, in collaboration with NVIDIA, is announcing that Azure Stack Hub with Azure NC-Series Virtual Machine (VM) support is now in preview. Azure NC-Series VMs are GPU-enabled Azure Virtual Machines available on the edge. GPU support in Azure Stack Hub unlocks a variety of new solution opportunities. With our Azure Stack Hub hardware partners, customers can choose the appropriate GPU for their workloads to enable Artificial Intelligence, training, inference, and visualization scenarios.

Azure Stack Hub brings together the full capabilities of the cloud to effectively deploy and manage workloads that otherwise are not possible to bring into a single solution. We are offering two NVIDIA enabled GPU models during the preview period. They are available in both NVIDIA V100 Tensor Core and NVIDIA T4 Tensor Core GPUs. These physical GPUs align with the following Azure N-Series VM types as follows:

NCv3 (NVIDIA V100 Tensor Core GPU): These enable learning, inference and visualization scenarios. See Standard_NC6s_v3 for a similar configuration.
TBD (NVIDIA T4 Tensor Core GPU): This new VM size (available only on Azure Stack Hub) enables light learning, inference, and visualization scenarios.

Hewlett Packard Enterprise is supporting the Microsoft GPU preview program as part of its HPE ProLiant for Microsoft Azure Stack Hub solution.“The HPE ProLiant for Microsoft Azure Stack Hub solution with the HPE ProLiant DL380 server nodes are GPU-enabled to support the maximum CPU, RAM, and all-flash storage configurations for GPU workloads,” said Mark Evans, WW product manager, HPE ProLiant for Microsoft Azure Stack Hub, at HPE. “We look forward to this collaboration that will help customers explore new workload options enabled by GPU capabilities.” 

As the leading cloud infrastructure provider1, Dell Technologies helps organizations remove cloud complexity and extend a consistent operating model across clouds. Working closely with Microsoft, the Dell EMC Integrated System for Azure Stack Hub will support additional GPU configurations, which include NVIDIA V100 Tensor Core GPUs, in a 2U form factor. This will provide customers increased performance density and workload flexibility for the growing predictive analytics and AI/ML markets. These new configurations also come with automated lifecycle management capabilities and exceptional support.

To participate in the Azure Stack Hub GPU preview, please send us an email today. 

Azure Stack Edge preview

We also announced the expansion of our Microsoft Azure Stack Edge preview with the NVIDIA T4 Tensor Core GPU. Azure Stack Edge is a cloud managed appliance that provides processing for fast local analysis and insights to the data. With the addition of an NVIDIA GPU, you’re able to build in the cloud then run at the edge. For more information about this exciting release please see the detailed blog.

GTC Digital

Microsoft session recordings will be available on the GTC Digital site starting March 26. You can find a list of the Microsoft digital sessions along with corresponding links in the Microsoft Tech Community blog here.

1 IDC WW Quarterly Cloud IT Infrastructure Tracker, Q3 2019, January 2020, Vendor Revenue
Quelle: Azure