Ronmia feedback comments

Author: v-sissondan

azure-local/includes/hci-arc-vm.md

@@ -1,12 +1,12 @@
 ---
 author: alkohli
 ms.topic: include
-ms.date: 03/21/2025
+ms.date: 03/28/2025
 ms.author: alkohli
 
 ---
 
 <!--- Link must remain site-relative to prevent build issues with incoming includes from the windowsserverdocs repo --->
 
 > [!NOTE]
-> The recommended way to create and manage VMs on Azure Local is using the [Azure Local VM management](/azure-stack/hci/manage/azure-arc-vm-management-overview). Use the method in this article to manage your VMs if you need functionality that isn't available in Azure Local VM management.
+> The recommended way to create and manage VMs on Azure Local is using [Azure Local VM management](/azure-stack/hci/manage/azure-arc-vm-management-overview). This article uses methods outside of Azure Local VM management to be able to attach an Ubuntu Linux VM on Azure Local.

azure-local/manage/attach-gpu-to-linux-vm.md

@@ -6,7 +6,7 @@ ms.author: alkohli
 ms.topic: how-to
 ms.service: azure-local
 ms.custom: linux-related-content
-ms.date: 03/21/2025
+ms.date: 03/28/2025
 ---
 
 # Attaching a GPU to an Ubuntu Linux VM on Azure Local
@@ -55,7 +55,7 @@ This topic provides step-by-step instructions on how to install and configure an
     Get-VMAssignableDevice -VMName Ubuntu
     ```
 
-    Successful assignment of the GPU to the VM that shows this output:
+    Successful assignment of the GPU to the VM shows this output:
 
     :::image type="content" source="media/attach-gpu-to-linux-vm/assign-gpu.png" alt-text="Assign GPU Screenshot." lightbox="media/attach-gpu-to-linux-vm/assign-gpu.png":::
 
@@ -160,7 +160,7 @@ This topic provides step-by-step instructions on how to install and configure an
 
 ## Configure Azure IoT Edge
 
-To prepare for this configuration, please review the FAQ contained in the [NVIDIA-Deepstream-Azure-IoT-Edge-on-a-NVIDIA-Jetson-Nano](https://github.com/Azure-Samples/NVIDIA-Deepstream-Azure-IoT-Edge-on-a-NVIDIA-Jetson-Nano) GitHub repo, which explains the need to install Docker instead of Moby. After reviewing, proceed using the steps.
+To prepare for this configuration, please review the FAQ contained in the [NVIDIA-Deepstream-Azure-IoT-Edge-on-a-NVIDIA-Jetson-Nano](https://github.com/Azure-Samples/NVIDIA-Deepstream-Azure-IoT-Edge-on-a-NVIDIA-Jetson-Nano) GitHub repo, which explains the need to install Docker instead of Moby. After reviewing, proceed to the next steps.
 
 ### Install NVIDIA Docker
 

azure-local/manage/gpu-manage-via-device.md

@@ -5,14 +5,14 @@ author: alkohli
 ms.author: alkohli
 ms.topic: how-to
 ms.service: azure-local
-ms.date: 03/21/2025
+ms.date: 03/28/2025
 ---
 
 # Manage GPUs via Discrete Device Assignment (preview)
 
 [!INCLUDE [applies-to](../includes/hci-applies-to-23h2.md)]
 
-This article describes how to manage GPU DDA with Azure Local virtual machines (VMs) enabled by Azure Arc. For GPU DDA management on Azure Kubernetes Service (AKS) enabled by Azure Arc, see [Use GPUs for compute-intensive workloads](/azure/aks/hybrid/deploy-gpu-node-pool#create-a-new-workload-cluster-with-a-gpu-enabled-node-pool).
+This article describes how to manage GPU DDA with Azure Local VMs enabled by Azure Arc. For GPU DDA management on Azure Kubernetes Service (AKS) enabled by Azure Arc, see [Use GPUs for compute-intensive workloads](/azure/aks/hybrid/deploy-gpu-node-pool#create-a-new-workload-cluster-with-a-gpu-enabled-node-pool).
 
 Discrete Device Assignment (DDA) allows you to dedicate a physical graphical processing unit (GPU) to your workload. In a DDA deployment, virtualized workloads run on the native driver and typically have full access to the GPU's functionality. DDA offers the highest level of app compatibility and potential performance.
 

azure-local/manage/gpu-preparation.md

@@ -4,15 +4,15 @@ description: Learn how to prepare GPUs for an Azure Local instance.
 author: alkohli
 ms.author: alkohli
 ms.topic: how-to
-ms.date: 03/17/2025
+ms.date: 03/28/2025
 ms.service: azure-local
 ---
 
 # Prepare GPUs for Azure Local
 
 [!INCLUDE [applies-to](../includes/hci-applies-to-23h2.md)]
 
-This article describes how to prepare graphical processing units (GPUs) on your Azure Local instance for computation-intensive workloads running on Azure Local virtual machines (VMs) enabled by Azure Arc and Azure Kubernetes Service (AKS) enabled by Azure Arc. GPUs are used for computation-intensive workloads such as machine learning and deep learning.
+This article describes how to prepare graphical processing units (GPUs) on your Azure Local instance for computation-intensive workloads running on Azure Local VMs enabled by Azure Arc and Azure Kubernetes Service (AKS) enabled by Azure Arc. GPUs are used for computation-intensive workloads such as machine learning and deep learning.
 
 
 ## Attaching GPUs on Azure Local