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‎AKS-Arc/aks-vmware-quickstart-deploy.md

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ms.author: sethm
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ms.topic: quickstart
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ms.custom: devx-track-azurecli
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ms.date: 03/22/2024
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ms.lastreviewed: 03/22/2024
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ms.date: 03/19/2025
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ms.lastreviewed: 03/19/2025
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ms.reviewer: leslielin
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---
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> [!NOTE]
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> In this preview release, you can only deploy the same Kubernetes version that the Arc Resource Bridge supports. The Kubernetes version you provide in the command must align with the Arc Resource Bridge version. You can find the Arc Resource Bridge version in the Azure portal under **Azure Arc > Management > Resource Bridge**. To determine the corresponding Kubernetes version, see [What's new with Azure Arc resource bridge](/azure/azure-arc/resource-bridge/release-notes).
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## Delete the cluster
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Run the `az aksarc delete` command to clean up the cluster you created:
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```azurecli
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az aksarc delete -n '<name of your cluster>' -g $resource_group
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```
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> [!IMPORTANT]
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> The delete operation can fail if your vCenter credentials are invalid. To prevent this, verify that you have proper administrative access for Arc-enabled VMware vSphere. For more information, see [Updating the vSphere account credentials](/azure/azure-arc/vmware-vsphere/administer-arc-vmware#updating-the-vsphere-account-credentials-using-a-new-password-or-a-new-vsphere-account-after-onboarding).
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## Next steps
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‎AKS-Arc/aks-vmware-troubleshooting-guide.md

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@@ -4,9 +4,9 @@ description: Learn how to troubleshoot issues and errors in AKS enabled by Arc o
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ms.topic: how-to
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ms.custom: devx-track-azurecli
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author: sethmanheim
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ms.date: 03/20/2024
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ms.date: 03/19/2025
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ms.author: sethm
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ms.lastreviewed: 03/20/2024
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ms.lastreviewed: 03/19/2025
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ms.reviewer: leslielin
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---
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## Arc Resource Bridge
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### Azure Arc resource bridge issues
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To keep your Azure Arc resource bridge deployment online and operational, you must perform maintenance operations such as updating credentials, monitoring upgrades, and ensuring the appliance VM is online. For more information, see [Azure Arc resource bridge maintenance operations](/azure/azure-arc/resource-bridge/maintenance#update-credentials-in-the-appliance-vm).
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For Azure Arc resource bridge issues, see the [troubleshooting guide here](/azure/azure-arc/resource-bridge/troubleshoot-resource-bridge).
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### Recover from failed deployments of Arc Resource Bridge
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See the [troubleshooting guide here](/azure/azure-arc/vmware-vsphere/quick-start-connect-vcenter-to-arc-using-script#recovering-from-failed-deployments).
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See [Recovering from failed deployments](/azure/azure-arc/vmware-vsphere/quick-start-connect-vcenter-to-arc-using-script#recovering-from-failed-deployments) for troubleshooting.
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### vCenter connection to Azure
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‎AKS-Arc/deploy-ai-model.md

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author: sethmanheim
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ms.author: sethm
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ms.topic: how-to
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ms.date: 12/06/2024
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ms.date: 03/21/2025
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ms.reviewer: haojiehang
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ms.lastreviewed: 12/03/2024
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### [Azure CLI](#tab/azurecli)
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To create a GPU node pool using Azure CLI, run the following command. The GPU VM SKU used in the following example is for the **A16** model; for the full list of VM SKUs, see [Supported VM sizes](deploy-gpu-node-pool.md#supported-vm-sizes).
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To create a GPU node pool using Azure CLI, run the following command. The GPU VM SKU used in the following example is for the **A16** model; for the full list of VM SKUs, see [Supported VM sizes](scale-requirements.md#supported-vm-sizes).
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```azurecli
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az aksarc nodepool add --name "samplenodepool" --cluster-name "samplecluster" --resource-group "sample-rg" --node-vm-size "Standard_NC16_A16" --os-type "Linux"

‎AKS-Arc/deploy-gpu-node-pool.md

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description: Learn how to deploy GPU-enabled node pools in AKS enabled by Arc.
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author: sethmanheim
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ms.topic: how-to
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ms.date: 02/29/2024
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ms.date: 03/21/2025
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ms.author: sethm
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ms.lastreviewed: 06/05/2024
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ms.reviewer: baziwane
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ms.lastreviewed: 03/21/2025
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ms.reviewer: abha
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# Intent: As an IT Pro, I want to learn how to deploy GPU-enabled node pools
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# Keyword: Run GPU workloads on Kubernetes
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Graphical Processing Units (GPU) are used for compute-intensive workloads such as machine learning, deep learning, and more. This article describes how to use GPUs for compute-intensive workloads in AKS enabled by Azure Arc.
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## Supported GPU models
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The following GPU models are supported by AKS on Azure Local, version 23H2:
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| Manufacturer | GPU model | Supported version |
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|--------------|-----------|-------------------|
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| NVidia | A2 | 2311.2 |
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| NVidia | A16 | 2402.0 |
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| NVidia | T4 | 2408.0 |
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## Supported VM sizes
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The following VM sizes for each GPU models are supported by AKS on Azure Local, version 23H2.
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### Nvidia T4 is supported by NK T4 SKUs
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| VM size | GPUs | GPU Memory: GiB | vCPU | Memory: GiB |
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|-----------------|---|----|-----|----|
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| Standard_NK6 | 1 | 8 | 6 | 12 |
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| Standard_NK12 | 2 | 16 | 12 | 24 |
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### Nvidia A2 is supported by NC2 A2 SKUs
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| VM size | GPUs | GPU Memory: GiB | vCPU | Memory: GiB |
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|-------------------|---|----|----|----|
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| Standard_NC4_A2 | 1 | 16 | 4 | 8 |
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| Standard_NC8_A2 | 1 | 16 | 8 | 16 |
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| Standard_NC16_A2 | 2 | 48 | 16 | 64 |
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| Standard_NC32_A2 | 2 | 48 | 32 | 128 |
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### Nvidia A16 is supported by NC2 A16 SKUs
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| VM size | GPUs | GPU Memory: GiB | vCPU | Memory: GiB |
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|--------------------|---|----|----|----|
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| Standard_NC4_A16 | 1 | 16 | 4 | 8 |
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| Standard_NC8_A16 | 1 | 16 | 8 | 16 |
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| Standard_NC16_A16 | 2 | 48 | 16 | 64 |
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| Standard_NC32_A16 | 2 | 48 | 32 | 128 |
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## Before you begin
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To use GPUs in AKS Arc, make sure you installed the necessary GPU drivers before you begin the deployment of the cluster. Follow the steps in this section.
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## Next steps
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- [Supported VM sizes](scale-requirements.md)
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- [Use GPUs (AKS on Azure Local 22H2)](deploy-gpu-node-pool-22h2.md)
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- [AKS overview](aks-hybrid-options-overview.md)

‎AKS-Arc/docfx.json

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"breadcrumb_path": "/azure/aks/aksarc/breadcrumb/toc.json",
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"extendBreadcrumb": false,
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"manager":"lizross",
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"ms.service": "azure-stack",
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"recommendations": true,
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"zone_pivot_group_filename": "../azure-stack/zone-pivot-groups.json"
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‎AKS-Arc/scale-requirements.md

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title: Scale requirements for AKS on Azure Local
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description: Learn about scale requirements for AKS on Azure Local.
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ms.topic: conceptual
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| Standard_D8s_v3 | 8 | 32 |
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For more worker node sizes with GPU support, see [Use GPUs](deploy-gpu-node-pool.md).
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For more worker node sizes with GPU support, see the next section.
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## Supported GPU models
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The following GPU models are supported by AKS on Azure Local, version 23H2:
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| Manufacturer | GPU model | Supported version |
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|--------------|-----------|-------------------|
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| NVidia | A2 | 2311.2 |
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| NVidia | A16 | 2402.0 |
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| NVidia | T4 | 2408.0 |
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## Supported VM sizes
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The following VM sizes for each GPU models are supported by AKS on Azure Local, version 23H2.
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### Nvidia T4 is supported by NK T4 SKUs
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| VM size | GPUs | GPU Memory: GiB | vCPU | Memory: GiB |
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|-----------------|---|----|-----|----|
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| Standard_NK6 | 1 | 8 | 6 | 12 |
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| Standard_NK12 | 2 | 16 | 12 | 24 |
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### Nvidia A2 is supported by NC2 A2 SKUs
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| VM size | GPUs | GPU Memory: GiB | vCPU | Memory: GiB |
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|-------------------|---|----|----|----|
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| Standard_NC4_A2 | 1 | 16 | 4 | 8 |
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| Standard_NC8_A2 | 1 | 16 | 8 | 16 |
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| Standard_NC16_A2 | 2 | 48 | 16 | 64 |
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| Standard_NC32_A2 | 2 | 48 | 32 | 128 |
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### Nvidia A16 is supported by NC2 A16 SKUs
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| VM size | GPUs | GPU Memory: GiB | vCPU | Memory: GiB |
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|--------------------|---|----|----|----|
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| Standard_NC4_A16 | 1 | 16 | 4 | 8 |
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| Standard_NC8_A16 | 1 | 16 | 8 | 16 |
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| Standard_NC16_A16 | 2 | 48 | 16 | 64 |
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| Standard_NC32_A16 | 2 | 48 | 32 | 128 |
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## Next steps
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‎azure-local/TOC.yml

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- name: Compare VM management capabilities
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- name: Supported operations for VMs
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- name: Assign RBAC role
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- name: Manage Azure Local VM resources
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- name: Collect log files for Azure Local VM
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‎azure-local/concepts/billing.md

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title: Azure Local billing and payment
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‎azure-local/concepts/compare-vm-management-capabilities.md

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| VM provisioning and management methods | Azure Local VMs enabled by Azure Arc | Arc-enabled servers | Unmanaged VMs |
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| Provisioning method | [Azure Local VMs provisioning flow](../manage/create-arc-virtual-machines.md?tabs=azureportal). Create Azure Local VMs using Azure CLI, Azure portal, or Azure Resource Manager (ARM) template. Using ARM templates, you can also automate VM provisioning in a secure cloud environment. <br><br> [Azure Migrate flow](../migrate/migration-azure-migrate-overview.md). Migrate existing VMware and Hyper-V VMs to Azure Local using the migration flow. | Connect these machines to Azure by [deploying the Connected Machine agent](/azure/azure-arc/servers/deployment-options) | On-premises provisioning flow. Use local tools like Failover Cluster Manager available in your on-premises environment, or use [Windows Admin Center](../manage/vm.md#create-a-new-vm), [System Center Virtual Machine Manager (SCVMM)](/system-center/vmm/provision-vms), or [PowerShell](../manage/vm-powershell.md#create-a-vm).|
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| Management method | Via Azure. | Via Azure. See [Management and monitoring for Azure Arc-enabled servers](/azure/cloud-adoption-framework/scenarios/hybrid/arc-enabled-servers/eslz-management-and-monitoring-arc-server). | Via the local tools. Manage these VMs through the management consoles of the same local tools used for their creation. |
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| Management method | [Via Azure](../manage/manage-arc-virtual-machines.md). | Via Azure. See [Management and monitoring for Azure Arc-enabled servers](/azure/cloud-adoption-framework/scenarios/hybrid/arc-enabled-servers/eslz-management-and-monitoring-arc-server). | Via the local tools. Manage these VMs through the management consoles of the same local tools used for their creation. |
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‎azure-local/concepts/compare-windows-server.md

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---

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