Technology & Services partners are jumping on the bandwagon of Azure Arc
The Azure Arc partner ecosystem offers customers validated, enterprise grade solutions to run Azure on-premises and at the edge. Launched at Microsoft Ignite 2021 with support from industry-leading OEMs, hardware providers, platform providers, and ISVs, we are happy to announce the expansion of the Azure Arc network of trusted partners and validated platforms to data services.Introducing Azure Local: cloud infrastructure for distributed locations enabled by Azure Arc
Today at Microsoft Ignite 2024 we're introducing Azure Local, cloud-connected infrastructure that can be deployed at your physical locations and under your operational control. With Azure Local, you can run the foundational Azure compute, networking, storage, and application services locally on hardware from your preferred vendor, providing flexibility to meet your requirements and budget.Generally Available: Windows Server 2012 and 2012 R2 Extended Security Updates enabled by Azure Arc
Secure your End-of-Life Windows Server infrastructure on your own terms with Azure Arc. Benefit from the flexibility of a monthly Azure billed service and free access to Azure management services by leveraging Extended Security Updates enabled by Azure Arc for your Windows Server 2012 and 2012 R2 machines.New options for Extended Security Updates enabled by Azure Arc
Today, we’re announcing Extended Security Updates enabled by Azure Arc for Windows Server 2012/R2 and SQL Server 2012 (year 2 onwards), a new and enhanced cloud experience alternative to traditional Extended Security Updates (classic). With this new option, security updates will be natively available in the Azure Portal through Azure Arc for resources for up to 3 .
Announcing General Availability for GitOps with Flux v2 in Azure
This blog has been co-authored by Chris Sanders, Senior Program Manager, Azure Arc at Microsoft. GitOps capabilities have been an integral part of Azure Kubernetes Service (AKS) since its preview in December 2021 and Azure Arc-enabled Kubernetes since it’s launch at Ignite in 2021. Today, we are pleased to announce the General Availability of GitOps with Flux v2 in Azure Kubernetes Service (AKS) and Azure Arc-enabled Kubernetes (Arc K8s). With this release, Azure supports GitOps configuration and workload management for your entire cloud and hybrid Kubernetes estate – clusters in AKS and clusters on-premises or in other public clouds. Flux v2 is a major update bringing a Kubernetes-native architecture, observability, and multi-tenancy among other improvements. With a single tool and process, you can manage your modern applications in Kubernetes everywhere. Deploy modern applications in your cloud and hybrid environments Teams running modern, cloud-native applications need reliable, automated processes for managing Kubernetes cluster configuration and application lifecycle. GitOps is a technique for implementing continuous deployment for these applications and configurations and focuses on using tools and processes developers and cluster admins are familiar with, like Git and pull requests. GitOps enables infrastructure as code, where the state of the environment is declaratively described in Git repositories. Changes to the workload environment, such as an application update, happen via pull request to the Git repository, after which Flux, running in each cluster, automatically syncs the changes and applies them to the cluster. Flux also continuously assures that the cluster remains in the declared state. GitOps enables accurate change management and audit, as cluster state and all changes are fully visible in the Git repository. It also enhances cluster security, as developers and deployment tools don’t need direct access to clusters. In short, GitOps is the modern way to manage continuous deployment for your containerized workloads, and Azure GitOps with Flux brings this capability to you. How does this work? Azure uses open source CNCF Flux to enable GitOps in Azure Kubernetes Service (AKS) or Azure Arc-enabled Kubernetes (Arc K8s) clusters. Azure provides simple install, automatic update, and health reporting to simplify your use of GitOps across one to thousands of clusters. In Azure, GitOps with Flux v2 is enabled as a cluster extension to your AKS or Arc K8s clusters. The Flux extension installs the Flux controllers in the clusters. After Flux is enabled, you can then create one or more GitOps configurations in each cluster which enable the connections to your Git repositories and the deployment of the resources defined in the repositories. Importantly, in Azure you can track the compliance state of the deployments in each cluster to assure that the clusters are in the state you declared in your Git repositories. This gives you the observability you need to assure healthy cluster state. GitOps extension for VS Code We also are happy to announce the release of the new GitOps extension for VS Code. You can manage GitOps with Flux in your AKS, Arc-enabled Kubernetes, or other Kubernetes clusters directly within the VS Code client. This can simplify the developer inner loop when working with clusters managed by GitOps Flux. Some key features are: View list of configured clusters and switch cluster context AKS, Arc K8s, and other clusters are identified View Flux controllers, state, and logs View sources (Git and Helm Repositories, Bucket) and workloads (Kustomization, Helm Release) Create Git Repository source and Kustomization workload on the cluster Reconcile Sources and Workloads on demand Load Kubernetes Object manifest .yaml configs in VS Code editor Pull Git Repository Source to user machine and open it in VS Code Links to GitOps, Flux, and Azure Kubernetes documents This is an open-source project, and your contributions are welcome to improve the GitOps extension. Open-Source Partnerships The work to integrate Flux in Azure GitOps, enhance Flux capabilities, and create the VS Code extension has been done in partnership with Weaveworks and the Flux maintainers. Microsoft is continuing to partner with Weaveworks and participate in advancing the Flux CNCF project and OpenGitOps. Next Steps We are excited for you to start using the new capabilities in GitOps with Flux v2 in Azure Kubernetes Service and Azure Arc-enabled Kubernetes. For details on how you can get started, please see these documents: GitOps in Azure conceptual overview Tutorial: Use GitOps with Flux v2 in Azure Arc-enabled Kubernetes or AKS clusters Leverage the Azure Arc Jumpstart to get started quickly with an AKS cluster Azure Architecture Center GitOps for AKSRealizing Machine Learning anywhere with Azure Kubernetes Service and Arc-enabled Machine Learning
We are thrilled to announce the general availability of Azure Machine Learning (Azure ML) Kubernetes compute, including support of seamless Azure Kubernetes Service (AKS) integration and Azure Arc-enabled Machine Learning. With a simple cluster extension deployment on AKS or Azure Arc-enabled Kubernetes (Arc Kubernetes) cluster, Kubernetes cluster is seamlessly supported in Azure ML to run training or inference workload. In addition, Azure ML service capabilities for streamlining full ML lifecycle and automation with MLOps become instantly available to enterprise teams of professionals. Azure ML Kubernetes compute empowers enterprises ML operationalization at scale across different infrastructures and addresses different needs with seamless experience of Azure ML CLI v2, Python SDK v2 (preview), and Studio UI. Here are some of the capabilities that customers can benefit Deploy ML workload on customer managed AKS cluster and gain more security and controls to meet compliance requirements. Run Azure ML workload on Arc Kubernetes cluster right where data lives and meets data residency, security, and privacy compliance, or harness existing IT investment. Use Arc Kubernetes cluster to deploy ML workload or aspect of ML lifecycle across multiple public clouds. Fully automated hybrid workload in cloud and on-premises to leverage different infrastructure advantages and IT investments. How it works The IT-operations team and data-science team are both integral parts of the broader ML team. By letting the IT-operations team manage Kubernetes compute setup, Azure ML creates a seamless compute experience for data-science team who does not need to learn or use Kubernetes directly. The design for Azure ML Kubernetes compute also helps IT-operations team leverage native Kubernetes concepts such as namespace, node selector, and resource requests/limits for ML compute utilization and optimization. Data-science team now can focus on models and work with productivity tools such as Azure ML CLI v2, Python SDK v2, Studio UI, and Jupyter notebook. It is easy to enable and use an existing Kubernetes cluster for Azure ML workload with the following simple steps: IT-operation team. The IT-operation team is responsible for the first 3 steps above: prepare an AKS or Arc Kubernetes cluster, deploy Azure ML cluster extension, and attach Kubernetes cluster to Azure ML workspace. In addition to these essential compute setup steps, IT-operation team also uses familiar tools such as Azure CLI or kubectl to take care of the following tasks for the data-science team: Network and security configurations, such as outbound proxy server connection or Azure firewall configuration, Azure ML inference router (azureml-fe) setup, SSL/TLS termination, and no-public IP with VNET. Create and manage instance types for different ML workload scenarios and gain efficient compute resource utilization. Trouble shooting workload issues related to Kubernetes cluster. Data-science team. Once the IT-operations team finishes compute setup and compute target(s) creation, data-science team can discover list of available compute targets and instance types in Azure ML workspace to be used for training or inference workload. Data science specifies compute target name and instance type name using their preferred tools or APIs such as Azure ML CLI v2, Python SDK v2, or Studio UI. Recommended best practices Separation of responsibilities between the IT-operations team and data-science team. As we mentioned above, managing your own compute and infrastructure for ML workload is a complicated task and it is best to be done by IT-operations team so data-science team can focus on ML models for organizational efficiency. Create and manage instance types for different ML workload scenarios. Each ML workload uses different amounts of compute resources such as CPU/GPU and memory. Azure ML implements instance type as Kubernetes custom resource definition (CRD) with properties of nodeSelector and resource request/limit. With a carefully curated list of instance types, IT-operations can target ML workload on specific node(s) and manage compute resource utilization efficiently. Multiple Azure ML workspaces share the same Kubernetes cluster. You can attach Kubernetes cluster multiple times to the same Azure ML workspace or different Azure ML workspaces, creating multiple compute targets in one workspace or multiple workspaces. Since many customers organize data science projects around Azure ML workspace, multiple data science projects can now share the same Kubernetes cluster. This significantly reduces ML infrastructure management overheads as well as IT cost saving. Team/project workload isolation using Kubernetes namespace. When you attach Kubernetes cluster to Azure ML workspace, you can specify a Kubernetes namespace for the compute target and all workloads run by the compute target will be placed under the specified namespace. New Azure ML use patterns enabled Azure Arc-enabled ML enables teams of ML professionals to build, train, and deploy models in any infrastructure on-premises and across multi-cloud using Kubernetes. This opens a variety of new use patterns previously unthinkable in cloud setting environment. Below table provides a summary of the new use patterns enabled by Azure ML Kubernetes compute, including where the training data resides in each use pattern, the motivation driving each use pattern, and how the use pattern is realized using Azure ML and infrastructure setup. Get started today To get started with Azure Machine Learning Kubernetes compute, please visit Azure ML documentation and GitHub repo, where you can find detailed instructions to setup Kubernetes cluster for Azure Machine Learning, and train or deploy models with a variety of Azure ML examples. Lastly, visit Azure Hybrid, Multicloud, and Edge Day and watch “Real time insights from edge to cloud” where we announced the GA.Announcing General Availability: Windows Server Management enabled by Azure Arc
Windows Server Management enabled by Azure Arc offers customers with Windows Server licenses that have active Software Assurances or Windows Server licenses that are active subscription licenses the following key benefits: Azure Update Manager Azure Change Tracking and Inventory Azure Machine Configuration Windows Admin Center in Azure for Arc Remote Support Network HUD Best Practices Assessment Azure Site Recovery (Configuration Only) Upon attestation, customers receive access to the following at no additional cost beyond associated networking, compute, storage, and log ingestion charges. These same capabilities are also available for customers enrolled in Windows Server 2025 Pay as you Go licensing enabled by Azure Arc. Learn more at Windows Server Management enabled by Azure Arc - Azure Arc | Microsoft Learn or watch Video: Free Azure Services for Non-Azure Windows Servers Covered by SA Powered by Azure Arc! To get started, connect your servers to Azure Arc, attest for these benefits, and deploy management services as you modernize to Azure's AI-enabled set of server management capabilities across your hybrid, multi-cloud, and edge infrastructure!Microsoft 365 Local is Generally Available
In today’s digital landscape, organizations and governments are prioritizing data sovereignty to comply with local regulations, protect sensitive information, and safeguard national security. This growing demand for robust jurisdictional controls makes the Microsoft Sovereign Cloud offering especially compelling, providing flexibility and assurance for complex requirements. For those with the most stringent needs, Azure Local enables data and workloads to remain within jurisdictional borders, supporting mission-critical workloads and now expanding to include Microsoft’s productivity solutions—so customers can securely collaborate and communicate within a sovereign private cloud environment. Today, we’re excited to announce the general availability of Microsoft 365 Local. Microsoft 365 Local is a deployment framework for enabling core collaboration and communication tools—including Exchange Server, SharePoint Server, and Skype for Business Server—on Azure Local. Built on a validated reference architecture using Azure Local Premier Solutions , it provides compatibility and support for sovereign deployments. Partner-led services provide guidance on sizing and configuration, ensuring a full-stack deployment including best practices for networking and security. Managing infrastructure across a wide range of workloads is simplified with Azure as your control plane, offering cloud-consistent, at-scale management capabilities. In the Azure portal, you get full visibility into your Microsoft 365 Local deployment across the servers and clusters. All hosts and virtual machines (VMs) are Arc-enabled out of the box, providing built-in visibility into connectivity, health, updates, and security alerts and recommendations. Microsoft 365 Local leverages Azure Local’s best-in-class sovereign and security controls, including Network Security Groups managed with Software Defined Networking enabled by Azure Arc, to isolate networks and secure access to infrastructure and workloads. Azure Local also uses a secure by default strategy by applying a security baseline of over 300 settings on both the host infrastructure and the VMs running the productivity workloads. These security baselines incorporate best practices for network security, identity management, privileged access, data protection, and more—helping organizations maintain compliance and reduce risk. Customers who want to take advantage of Azure as the control plane for Microsoft 365 Local can now benefit from a seamless cloud-based infrastructure management experience, including Azure services like Azure Monitor and Microsoft Defender for Cloud—available today with Microsoft 365 Local connected to Azure. For organizations with the most stringent jurisdictional requirements that need to operate Microsoft 365 Local in a fully disconnected environment, support for Azure Local disconnected operations will be available in early 2026. To learn more about Microsoft 365 Local, visit https://aka.ms/M365LocalDocs. If you’d like to connect with an authorized partner for consultation and deployment support, reach out to your Microsoft account team or visit https://aka.ms/M365LocalSignup.
