Azure Stack Announcements at Build 2020
Although Microsoft Build 2020 is a virtual event, we’ve got lots of new announcements and features we can’t wait to get into your hands: New Container related Services on Azure Stack Hub New Development empowerment tools New Management & Operation functionality Hardware innovation New Ecosystem & Industry Solutions Here’s a peek at what we’ve talked about this week: New Container related Services on Azure Stack Hub We’re constantly working to bring Azure services on-premises via Azure Stack Hub. As we strive to enable cloud-first technologies in our customer’s datacenters, we’ve been focused on providing seamless deployment and management of container-based applications at the edge. Expanded Azure Kubernetes Service on Azure Stack Hub We’re excited to announce that we’re starting to recruit customers for the private preview of the Azure Kubernetes Service resource provider on Azure Stack Hub. If you need Kubernetes clusters in production today, you can use the AKS engine which is already generally available. But preview we are recruiting customers for is for the AKS resource provider. This is the same resource provider that enables seamless deployment and management of Kubernetes clusters in Azure today. The AKS resource provider builds on the AKS engine to further simplify the creation and maintenance of Kubernetes clusters and provide the same user experience, CLI and APIs across public cloud and private cloud environments. Users can sign up for the private preview here: https://aka.ms/ash-aks-private-preview. Azure Container Registry on Azure Stack Hub Private Preview Azure Container Registry (ACR) enables our customers to create secure, private container registries in Azure, allowing them to store and receive Open Container Initiative (OCI) compliant artifacts on Azure’s resilient infrastructure. We’re bringing this capability to Azure Stack Hub. With the private preview of ACR on Azure Stack Hub, customers will be able to use ACR to create private container registries on-premises, in connected or disconnected modes. We are recruiting customers for an upcoming private preview. Users can sign up for the private preview here: https://aka.ms/ash-acr-private-preview New Developer empowerment tools An important pillar of the Azure Stack family is developer consistency. Ensuring that developers can use the same tools to develop and deploy code in Azure and on-premises increases developer efficiency and allows developers to spend more time tackling problems relevant to their business. New Az PowerShell Modules for Azure Stack Hub Azure Stack Hub now supports the use of the Az PowerShell modules for Azure. This release enables cross-platform connectivity via PowerShell to Azure Stack Hub instances, while ensuring hybrid consistency with Azure. Azure Stack Hub will utilize the Az modules moving forward. We’re also introducing support for new resource providers on Azure Stack Hub. Users can now use PowerShell to interact with the Azure Stack Edge, Event Hub, and IoT Hub resource providers on their properly configured Azure Stack Hub deployments. This is available through the Az PowerShell installer. Users can follow the instructions at https://aka.ms/InstallPowerShell. New Support for Windows Containers & Azure CNI on Hub The Azure Containers team is always innovating to bring the latest in container technology to Azure and Azure Stack Hub. We’re enabling support for Windows containers in the Azure Kubernetes Service engine, which uses automation to deploy Kubernetes clusters into Azure and Azure Stack Hub. In keeping with our promises of Azure compatibility, we’re also releasing the Azure Container Networking Interface plug-in, enabling customers to deploy and manage their own Kubernetes clusters with native Azure networking capability by default. This release, which will come as an update to the Azure Kubernetes Service engine, expands the capabilities of Kubernetes clusters on Azure Stack Hub. New Management & Operation functionality As the number of Azure Stack Hub and Azure Stack Edge deployments grow, Microsoft and our ecosystem partners have created tools that allow centralized management of Azure Stack Hub instances from a single portal, centralized management of multiple Azure Stack-deployed Kubernetes clusters from Azure using Arc, and other on-premises cloud resources. Azure Stack Hub Administration experience from Azure Preview Initially announced at Ignite 2019 as part of the Edge Manager solution, we’re starting a preview program of our Azure Stack Hub Admin experience from Azure at the end of the summer. Azure Stack Hub Administration from Azure gives Azure Stack Hub administrators the ability to view operations data about one or more Azure Stack Hub deployments through a central interface running in Azure. Administrators will soon be able to use a single pane of glass to view alerts and take actions such as rolling out software updates across their Azure Stack Hub fleet directly from a central location in the cloud. CloudAssert Multi Stamp and Multi Cloud Management Solution for Azure Stack Hub Cloud Assert, an ISV partner, is announcing the availability of their Multi-Cloud Management toolset that runs in disconnected mode. Their solution allows Azure Stack operators to manage multiple Azure Stack Hubs through a single pane of glass either directly from the Azure Stack Hub portal or through their standalone interfaces. The offering also provides functionality for tenant users to deploy and manage resources on different Azure Stack Hubs from a single location. In addition to these management features, Cloud Assert's existing solutions such as Usage and Billing for Azure Stack Hub now support collecting usage from multiple instances and generating aggregated reports and invoices. You can read more about their offering here: https://www.cloudassert.com/Product/Microsoft-Azure-Stack-Hub/Multi-Stamp-Management Azure Arc Support for AKS Engine Clusters Today, Microsoft is bringing new capabilities to Azure Arc to help customers simplify and streamline their on-premises, edge and multi-cloud investments. Beginning in summer 2020, Azure customers using Arc will be able to manage Kubernetes clusters deployed through the Azure Kubernetes Service engine on Azure Stack Hub. This enables central management of an organization’s Kubernetes clusters from Azure using Arc, no matter where they’re hosted. ManageIQ (CloudForms) Public Preview IBM and Microsoft are excited to announce a preview of ManageIQ, formerly known as Red Hat CloudForms, for Azure Stack Hub. ManageIQ is an IBM platform that allows cloud operators to manage their resources on Azure Stack Hub platforms, such as virtual machines, and track usage data. In addition, ManageIQ enables Azure Stack Hub to be managed by IBM’s robust technical tooling. Since our partnership announcement four years ago, Red Hat, IBM and Microsoft have seen immense value delivered to our customers, from co-support of hybrid cloud deployments to waves of upstream innovation for expanded Linux capabilities. Hardware Innovation Our Azure Stack Hub hardware and system integrator partners continue to up the ante with new form factors and hardware options for Azure Stack Hub. Soon, customers will be able to select Azure Stack Hub deployments with GPUs for machine learning, and remote desktop visualization. Azure Stack Hub is also expanding beyond the datacenter, with new form factors for deployment in unconventional environments. Avanade/HPE Edgeline Small Form Factor Azure Stack Hub Avanade, a valued cloud services partner, is offering customers a way to easily deploy and manage Azure Stack in remote locations like factories, oil rigs, retail locations warehouses, and all edges in between. Avanade offers Azure Stack Hub deployments using HPE’s Edgeline EL8000, a small form factor hub which does not require external cooling, making it ideal for locations like retail or manufacturing where a data center may not be available on site. Pairing Azure Stack Hub and HPE’s Edgeline EL8000 enables Azure services to transform businesses in new and exciting locations. GPU Hardware Previews Our customers have been asking for a way to supercharge their on-premises machine learning training and inferencing workloads. We announced at NVIDIAs GPU Technology conference a private preview for GPU-accelerated ML scenarios using Nvidia GPUs on Azure Stack Hub. Enabling rapid machine learning training and inferencing on Azure Stack Hub. The NVIDIA GPUs are the NVIDIA V100 and NVIDIA T4. The GPU will be available through an Azure Stack update for systems that have compatible hardware and are enrolled in the preview. In addition to machine learning, there is a demand for Azure Stack Hub deployments that enable graphics-intensive applications in a virtual environment. We’re also announcing a private preview for AMD GPU-based Azure Stack Hub systems, designed for remote visualization. This is the AMD Mi25 GPU. We are working closely with our hardware partners to bring these new capabilities to our customers. 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.” With Dell, we’re working on the Dell EMC Integrated System for Azure Stack Hub https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fblog.dellemc.com%2Fen-us%2Funlock-real-time-gpu-driven-insights-with-azure-stack-hub%2F&data=02%7C01%7CAnjay.Ajodha%40microsoft.com%7C36bef8f4695b49815abc08d7fb5f2314%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637254258336132767&sdata=glasEWDRly%2BnpQ6dfNjgWF6HJiH5LXngvKdRfGz6%2BLM%3D&reserved=0 - NVIDIA V100 Tensor Core and AMD Mi25 GPU’s. As a leading cloud infrastructure provider, Dell Technologies helps organizations remove cloud complexity and extend a consistent operating model across clouds. These new configurations will provide customers increased performance density and workload flexibility for the growing predictive analytics and AI/ML markets. They will also come with automated lifecycle management capabilities and exceptional support. To participate in the Azure Stack Hub GPU preview, go to https://aka.ms/azurestackhubgpupreview today. New Ecosystem & Industry Solutions The Azure Stack family boasts an ever-growing independent software vendor (ISV) and partner ecosystem. Below are just a few of the many partners who have selected the Azure Stack family as the premier edge deployment platform for their solutions. Many of these partners have developed offerings targeted at a specific industry vertical and have a substantial knowledge of their selected industries. In addition to our partner and ISV solutions, Microsoft has developed a few first-party solutions designed to illustrate what’s possible with the Azure Stack family. Manufacturing Solution for AI in Factories As customers have become interested in edge computing, we’ve used several open-source projects to demonstrate the value of the Azure Stack family. Our latest release in this series of projects is a solution that brings low-cost computer vision to any manufacturing facility. Our solution, available on GitHub, guides customers with no data science practice or machine learning experience through the training and deployment of a machine learning model using an IP camera and objects of their choosing. Designed to run on Azure Stack Edge and Azure Stack Hub, and using Customvision.ai, Microsoft’s easy-to-use vision model training service, our customers can get up and running in hours. Our partner https://www.linkernetworks.com/blog-1 can help customers interested in deploying this solution at scale in production. We plan to add several other features and enhancements to the product over the coming weeks, so stay tuned. To try this solution, go to: https://aka.ms/factoryai Aware Group Solutions – Solutions for AI and IoT at the edge The Aware Group, an Azure Edge ISV partner based in New Zealand, is https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Faware.to%2Fpopulace&data=02%7C01%7Cchasat%40exchange.microsoft.com%7C10a7dfb6b4924f9f5e1308d7eb3c7245%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C637236517163992087&sdata=K9qwBEBwv8EJAXCxMNaHSx0hmBgJ2k8%2Fgi1Fqzj0hmE%3D&reserved=0 for the Azure Stack family that extends the power of their current offerings to the edge. Their current offerings include IoT Edge modules that use AI to detect anomalies and perform noise classification. They’ll soon begin offering products and solutions that integrate their technology into vertical-specific scenarios. FHIR Server on Azure Stack Hub and Azure Stack Edge With the renewed focus on healthcare scenarios, we’re announcing a non-production version of Microsoft’s Fast Healthcare Interoperability Resources (FHIR) server designed to be deployed at the edge, on Azure Stack Edge and Azure Stack Hub. Deploying a FHIR server at the edge enables healthcare providers to securely cache and share patient data between their facilities and make de-identified data available to other groups. These new scenarios help the healthcare community collect, aggregate, and managed data where it’s generated. For more information, go to: https://aka.ms/azshealthcare Microsoft Research Project InnerEye – Coming Soon to Azure Stack Hub Microsoft Research, Microsoft Healthcare Next, and the Azure Stack teams are collaborating to bring https://www.microsoft.com/en-us/research/project/medical-image-analysis/ to Azure Stack Hub, enabling machine learning and analysis of medical scans at the edge. This summer, a solution will be made available that allows healthcare providers to easily train machine learning models on their on-premises data, building on model architectures developed by Microsoft Research Cambridge. Project InnerEye at the edge will allow healthcare providers and ISVs to provide low latency medical image analysis and comply with data handling regulations. Knowledgepark GmbH Selects Azure Stack Hub for German Healthcare Solution Knowledgepark GmbH, an Azure Stack ISV partner, in collaboration with Akquinet AG and Cloudian Inc. are announcing a healthcare-oriented cloud services platform for the German market, based on Azure Stack Hub integrated with Cloudian’s HyperStore ObjectStorage. Planned offerings based on this platform include electronic health record systems, and healthcare billing solutions. To learn more about Knowledgepark’s offering, go here: https://aka.ms/azshealthcare_partnerstory_Kpark Neal Analytics, with Microsoft and Intel, Unveils StockView Neal Analytics, in partnership with Microsoft and Intel, is taking the wraps off StockView, its new out-of-stock detection solution for medical supplies. StockView leverages Microsoft’s Azure Stack Edge devices, vision-based AI, and the Azure platform to automatically detect medical supply shortages and notify hospitals. To learn more about StockView, go here: https://aka.ms/azshealthcare_partnerstory_NealAnalytics We hope that you have a great virtual Build! Let us know what you think in the comments below. To learn more about the Azure Stack family, go here: https://azure.microsoft.com/en-us/overview/azure-stack/
AKS and NVIDIA A100 GPU support with Azure NDasrv4 Series
Hi there, We are using Azure's Standard_ND96asr_v4 instance types for our ML workloads and would love to use AKS images, instead of custom VM images to make it work. We ran into issues migrating from V100 to A100 GPUs, which could be addressed by installing the drivers and fabric managers mentioned in this help page: https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/reference-known-issues#fix-gpu-on-nvidia-a100-gpu-chip---azure-ndasrv4-series Is there any plan to fix the AKS VM images with those packages so we don't have to maintain a separate image?
Anyone else having issues with NVs_v3 GPU focused series and the Multi-Session Image
Hey y'all. Trying to test out the usage of NVs_v3 series machines with Virtual Desktop preview. Seems like the NVIDIA GPU extension causes machines to become completely useless. I can replicate with regular Windows images as well. Opened a ticket with azure support about being unable to provision these but ....well. Was wondering if the community had any ideas. I have also tried manual installs of the Tesla M60 and GRID drivers. Both using the microsoft provided .exe's located here: https://docs.microsoft.com/en-us/azure/virtual-machines/windows/n-series-driver-setup and by going directly through NVIDIA. The .exe files cause the same black screen of death with no way to run anything, and going through NVIDIA the GRID install doesn't detect hardware (but M60 works) Know isn't directly related to this forum, but trying to architect a solution between Virtual Desktop and these machines. One other thought I had was around trying a newer build of Windows. Does anyone know if there is an image available somewhere for the Windows 10 for Multi-Desktop that uses build 1803? 1809 and 1903 are in the public gallery and I have read in some documentation that there are issues with both as far as virtualizing GPU resources on Windows. Any help would be amazing! Thanks! Mitch
NV Series - WDDM vs TCC
According to the Azure GPU VM size guide (https://docs.microsoft.com/en-us/azure/virtual-machines/windows/sizes-gpu): NC, NCv2, and ND sizes are optimized for compute-intensive and network-intensive applications and algorithms, including CUDA- and OpenCL-based applications and simulations, AI, and Deep Learning. NV sizes are optimized and designed for remote visualization, streaming, gaming, encoding, and VDI scenarios utilizing frameworks such as OpenGL and DirectX. When I deploy a NV instance, the M60 GPU defaults to TCC mode when I think that it should be in WDDM mode: TCC being useful for compute workloads (NC or ND size) vs WDDM being appropriate for graphics workloads (NV size). In my experience, when the GPU is in TCC mode, RDP sessions are not able to leverage the GPU. Using the nvidia-smi tool to change the mode to WDDM: nvidia-smi -g {GPU_ID} -dm 0 and then rebooting the VM allows the RDP session to leverage the GPU. However, this setting does not persist. If the VM is shutdown/de-provisioned, when it is next started, the GPU is back in TCC mode and has to be switched to WDDM mode again. My research suggests that this is due to a setting stored in the EEPROM of the GPU. Am I missing something from a configuration standpoint to either get an RDP session to use the GPU in TCC mode or to always start the VM in WDDM mode?