Merge pull request #240551 from LouisBerner/v-lberner-ADO_91135

Court72 · web-flow · commit 7d136e165ca7 · 2023-07-10T17:33:12.000-06:00
Framing out tabs
diff --git a/articles/databox-online/azure-stack-edge-migrate-fpga-gpu.md b/articles/databox-online/azure-stack-edge-migrate-fpga-gpu.md
@@ -1,65 +1,80 @@
 ---
-title: Migration guide for Azure Stack Edge Pro FPGA to GPU physical device
-description: This guide contains instructions to migrate workloads from an Azure Stack Edge Pro FPGA device to an Azure Stack Edge Pro GPU device.
+title: Migration guide for Azure Stack Edge Pro FPGA to Pro 2 physical device
+description: This guide contains instructions to migrate workloads from an Azure Stack Edge Pro FPGA device to an Azure Stack Edge Pro 2 or Azure Stack Edge GPU device.
 services: databox
 author: alkohli
 
 ms.service: databox
 ms.subservice: edge
 ms.topic: tutorial
-ms.date: 06/02/2021
+ms.date: 07/07/2023
 ms.author: alkohli  
 ---
-# Migrate workloads from an Azure Stack Edge Pro FPGA to an Azure Stack Edge Pro GPU
+# Migrate workloads from an Azure Stack Edge Pro FPGA to an Azure Stack Edge Pro 2 or Azure Stack Edge GPU device
 
-This article describes how to migrate workloads and data from an Azure Stack Edge Pro FPGA device to an Azure Stack Edge Pro GPU device. The migration process begins with a comparison of the two devices, a migration plan, and a review of migration considerations. The migration procedure gives detailed steps ending with verification and device cleanup.
+This article describes how to migrate workloads and data from an Azure Stack Edge Pro FPGA device to an Azure Stack Edge Pro 2 or Pro GPU device. The migration process begins with selection of a new device, a migration plan, and a review of migration considerations. The migration procedure gives detailed steps ending with verification and device cleanup.
 
 [!INCLUDE [Azure Stack Edge Pro FPGA end-of-life](../../includes/azure-stack-edge-fpga-eol.md)]
 
 ## About migration
 
 Migration is the process of moving workloads and application data from one storage location to another. This entails making an exact copy of an organization’s current data from one storage device to another storage device - preferably without disrupting or disabling active applications - and then redirecting all input/output (I/O) activity to the new device. 
 
-This migration guide provides a step-by-step walkthrough of the steps required to migrate data from an Azure Stack Edge Pro FPGA device to an Azure Stack Edge Pro GPU device. This document is intended for information technology (IT) professionals and knowledge workers who are responsible for operating, deploying, and managing Azure Stack Edge devices in the datacenter.
+This migration guide provides a step-by-step walkthrough of the steps required to migrate data from an Azure Stack Edge Pro FPGA device to an alternate Azure Stack Edge device. This document is intended for information technology (IT) professionals and knowledge workers who are responsible for operating, deploying, and managing Azure Stack Edge devices in the datacenter.
 
-In this article, the Azure Stack Edge Pro FPGA device is referred to as the *source* device and the Azure Stack Edge Pro GPU device is the *target* device. 
+In this article, the Azure Stack Edge Pro FPGA device is referred to as the *source* device and the alternate Azure Stack Edge device is the *target* device. 
 
 ## Comparison summary
 
-This section provides a comparative summary of capabilities between the Azure Stack Edge Pro GPU vs. the Azure Stack Edge Pro FPGA devices. The hardware in both the source and the target device is largely identical; only the hardware acceleration card and the storage capacity may differ.<!--Please verify: These components MAY, but need not necessarily, differ?-->
+This section provides a comparative summary of capabilities between the Azure Stack Edge Pro FPGA device and Azure Stack Edge Pro 2 and Azure Stack Edge Pro GPU devices. Azure Stack Edge Pro 2 devices are offered in a range of options to meet a variety of cost and functionality needs.
+<!--Please verify: These components MAY, but need not necessarily, differ?-->
+
+### [Migrate to Azure Stack Edge Pro 2](#tab/migrate-to-ase-pro2)
+
+|    Capability  | Azure Stack Edge Pro 2 (Target device)  | Azure Stack Edge Pro FPGA (Source device)|
+|----------------|-----------------------|------------------------|
+| Hardware       | Hardware acceleration: 1 or 2 Nvidia A2 GPUs. <br> 64 GB, 128 GB, or 256 GB of memory. <br> 2x 10 GB BASE-T iWarp RDMA-capable network ports. <br> 2x optical 100 GB/sec RoCE RDMA-capable network ports. <br> Power supply units - 1. <br> For more information, see [Azure Stack Edge Pro 2 technical specifications](azure-stack-edge-pro-2-technical-specifications-compliance.md).   | Hardware acceleration: Intel Arria 10 FPGA. <br> 128 GB of memory. <br> 2x copper 1 GB/sec network ports. <br> 4x optical 25 GB/sec RDMA-capable network ports. <br> Power supply units - 2. <br> For more information, see [Azure Stack Edge Pro FPGA technical specifications](azure-stack-edge-technical-specifications-compliance.md).  |
+| Usable storage | 720 GB - 2.5 TB <br> After reserving space for resiliency and internal use. | 12.5 TB <br> After reserving space for internal use. |
+| Security       | Certificates |                                                     |
+| Workloads      | IoT Edge workloads <br> VM workloads <br> Kubernetes workloads| IoT Edge workloads |
+| Pricing        | [Azure Stack Edge pricing](https://azure.microsoft.com/pricing/details/azure-stack/edge/). | [Azure Stack Edge pricing](https://azure.microsoft.com/pricing/details/azure-stack/edge/).  |
+
+
+### [Migrate to Azure Stack Edge Pro GPU](#tab/migrate-to-ase-pro-gpu)
 
 |    Capability  | Azure Stack Edge Pro GPU (Target device)  | Azure Stack Edge Pro FPGA (Source device)|
 |----------------|-----------------------|------------------------|
-| Hardware       | Hardware acceleration: 1 or 2 Nvidia T4 GPUs <br> Compute, memory, network interface, power supply unit, and power cord specifications are identical to the device with FPGA.  | Hardware acceleration: Intel Arria 10 FPGA <br> Compute, memory, network interface, power supply unit, and power cord specifications are identical to the device with GPU.          |
-| Usable storage | 4.19 TB <br> After reserving space for parity resiliency and internal use | 12.5 TB <br> After reserving space for internal use |
+| Hardware       | Hardware acceleration: 1 or 2 Nvidia T4 GPUs. <br> Compute, memory, network interface, power supply unit, and power cord specifications are identical to the device with FPGA. <br> For more information, see [Azure Stack Edge Pro GPU technical specifications](azure-stack-edge-gpu-technical-specifications-compliance.md).   | Hardware acceleration: Intel Arria 10 FPGA. <br> Compute, memory, network interface, power supply unit, and power cord specifications are identical to the device with GPU. <br> For more information, see [Azure Stack Edge Pro FPGA technical specifications](azure-stack-edge-technical-specifications-compliance.md).  |
+| Usable storage | 4.19 TB <br> After reserving space for parity resiliency and internal use. | 12.5 TB <br> After reserving space for internal use. |
 | Security       | Certificates |                                                     |
 | Workloads      | IoT Edge workloads <br> VM workloads <br> Kubernetes workloads| IoT Edge workloads |
-| Pricing        | [Pricing](https://azure.microsoft.com/pricing/details/azure-stack/edge/) | [Pricing](https://azure.microsoft.com/pricing/details/azure-stack/edge/)|
+| Pricing        | [Azure Stack Edge pricing](https://azure.microsoft.com/pricing/details/azure-stack/edge/). | [Azure Stack Edge pricing](https://azure.microsoft.com/pricing/details/azure-stack/edge/).  |
+
+---
 
 ## Migration plan
 
 To create your migration plan, consider the following information:
 
 - Develop a schedule for migration. 
-- When you migrate data, you may experience a downtime. We recommend that you schedule migration during a downtime maintenance window as the process is disruptive. You will set up and restore configurations in this downtime as described later in this document.
-- Understand the total length of downtime and communicate it to all the stakeholders.
-- Identify the local data that needs to be migrated from the source device. As a precaution, ensure that all the data on the existing storage has a recent backup. 
-
+- When you migrate data, you may experience downtime. We recommend that you schedule migration during a downtime maintenance window as the process is disruptive. You will set up and restore configurations in this downtime as described later in this document.
+- Understand the total duration of downtime and communicate it to all stakeholders.
+- Identify local data to be migrated from the source device. As a precaution, ensure that all data on the existing storage has a recent backup. 
 
 ## Migration considerations 
 
 Before you proceed with the migration, consider the following information: 
 
-- An Azure Stack Edge Pro GPU device can't be activated against an Azure Stack Edge Pro FPGA resource. You should create a new resource for the Azure Stack Edge Pro GPU device as described in [Create an Azure Stack Edge Pro GPU order](azure-stack-edge-gpu-deploy-prep.md#create-a-new-resource).
-- The Machine Learning models deployed on the source device that used the FPGA will need to be changed for the target device with GPU. For help with the models, you can contact Microsoft Support. The custom models deployed on the source device that did not use the FPGA (used CPU only) should work as-is on the target device (using CPU).
+- An Azure Stack Edge device can't be activated against an Azure Stack Edge Pro FPGA resource. Instead, create a new resource for the target Azure Stack Edge device as described in [Create an Azure Stack Edge Pro GPU order](azure-stack-edge-gpu-deploy-prep.md#create-a-new-resource).
+- The Machine Learning models deployed on the source device that used the FPGA will need to be changed for the target device. For help with the models, you can contact Microsoft Support. The custom models deployed on the source device that did not use the FPGA (used CPU only) should work as-is on the target device (using CPU).
 - The IoT Edge modules deployed on the source device may require changes before the modules can be successfully deployed on the target device. 
 - The source device supports NFS 3.0 and 4.1 protocols. The target device only supports NFS 3.0 protocol.
 - The source device support SMB and NFS protocols. The target device supports storage via the REST protocol using storage accounts in addition to the SMB and NFS protocols for shares.
 - The share access on the source device is via the IP address whereas the share access on the target device is via the device name.
 
 ## Migration steps at-a-glance
 
-This table summarizes the overall flow for migration, describing the steps required for migration and the location where to take these steps.
+The following table summarizes the overall flow for migration, describing the steps required for migration and the location where the steps take place.
 
 | In this phase | Do this step| On this device |
 |---------------|-------------|----------------|
@@ -73,7 +88,54 @@ This table summarizes the overall flow for migration, describing the steps requi
 
 ## Prepare source device
 
-The preparation includes that you identify the Edge cloud shares, Edge local shares, and the IoT Edge modules deployed on the device. 
+The preparation includes that you identify the Edge cloud shares, Edge local shares, and the IoT Edge modules deployed on the device.
+
+### [Migrate to Azure Stack Edge Pro 2](#tab/migrate-to-ase-pro2)
+
+### 1. Record configuration data
+
+Do these steps on your source device via the local UI.
+
+Record the configuration data on the *source* device. Use the [Deployment checklist](azure-stack-edge-pro-2-deploy-checklist.md) to help you record the device configuration. During migration, you'll use this configuration information to configure the new target device. 
+
+### 2. Back up share data
+
+The device data can be of one of the following types:
+
+- Data in Edge cloud shares
+- Data in local shares
+
+#### Data in Edge cloud shares
+
+Edge cloud shares tier data from your device to Azure. Do these steps on your *source* device via the Azure portal. 
+
+- Make a list of all the Edge cloud shares and users that you have on the source device.
+- Make a list of all the bandwidth schedules that you have. You will recreate these bandwidth schedules on your target device.
+- Depending on the network bandwidth available, configure bandwidth schedules on your device to maximize the data tiered to the cloud. That minimizes the local data on the device.
+- Ensure that the shares are fully tiered to the cloud. The tiering can be confirmed by checking the share status in the Azure portal.  
+
+#### Data in Edge local shares
+
+Data in Edge local shares stays on the device. Do these steps on your *source* device via the Azure portal. 
+
+- Make a list of the Edge local shares on the device.
+- Since you'll be doing a one-time migration of the data, create a copy of the Edge local share data to another on-premises server. You can use copy tools such as `robocopy` (SMB) or `rsync` (NFS) to copy the data. Optionally you may have already deployed a third-party data protection solution to back up the data in your local shares. The following third-party solutions are supported for use with Azure Stack Edge Pro FPGA devices:
+
+    | Third-party software           | Reference to the solution                               |
+    |--------------------------------|---------------------------------------------------------|
+    | Cohesity                       | [https://www.cohesity.com/solution/cloud/azure/](https://www.cohesity.com/solution/cloud/azure/) <br> For details, contact Cohesity.          |
+    | Commvault                      | [https://www.commvault.com/azure](https://www.commvault.com/azure) <br> For details, contact Commvault.          |
+    | Veritas                        | [http://veritas.com/azure](http://veritas.com/azure) <br> For details, contact Veritas.   |
+    | Veeam                          | [https://www.veeam.com/kb4041](https://www.veeam.com/kb4041) <br> For details, contact Veeam. |
+
+
+### 3. Prepare IoT Edge workloads
+
+- If you have deployed IoT Edge modules and are using FPGA acceleration, you may need to modify the modules before these will run on the GPU device. Follow the instructions in [Modify IoT Edge modules](azure-stack-edge-gpu-modify-fpga-modules-gpu.md). 
+
+<!--- If you have deployed IoT Edge workloads, the configuration data is shared on a share on the device. Back up the data in these shares.-->
+
+### [Migrate to Azure Stack Edge Pro GPU](#tab/migrate-to-ase-pro-gpu)
 
 ### 1. Record configuration data
 
@@ -118,9 +180,39 @@ Data in Edge local shares stays on the device. Do these steps on your *source* d
 
 <!--- If you have deployed IoT Edge workloads, the configuration data is shared on a share on the device. Back up the data in these shares.-->
 
+---
 
 ## Prepare target device
 
+ Use the following steps to prepare the target device.
+
+### [Migrate to Azure Stack Edge Pro 2](#tab/migrate-to-ase-pro2) 
+
+### 1. Create new order
+
+You need to create a new order (and a new resource) for your *target* device. The target device must be activated against the GPU resource and not against the FPGA resource.
+
+To place an order, [Create a new Azure Stack Edge resource](azure-stack-edge-pro-2-deploy-prep.md#create-a-new-resource) in the Azure portal.
+
+
+### 2. Set up, activate
+
+You need to set up and activate the *target* device against the new resource you created earlier. 
+
+Follow these steps to configure the *target* device via the Azure portal:
+
+1. Gather the information required in the [Deployment checklist](azure-stack-edge-pro-2-deploy-checklist.md). You can use the information that you saved from the source device configuration. 
+1. [Unpack](azure-stack-edge-pro-2-deploy-install.md#unpack-the-device), [rack mount](azure-stack-edge-pro-2-deploy-install.md#rack-mount-the-device) and [cable your device](azure-stack-edge-pro-2-deploy-install.md#cable-the-device). 
+1. [Connect to the local UI of the device](azure-stack-edge-pro-2-deploy-connect.md).
+1. Configure the network using a different set of IP addresses (if using static IPs) than the ones that you used for your old device. See how to [configure network settings](azure-stack-edge-pro-2-deploy-configure-network-compute-web-proxy.md).
+1. Assign the same device name as your old device and provide a DNS domain. See how to [configure device setting](azure-stack-edge-pro-2-deploy-set-up-device-update-time.md).
+1. Configure certificates on the new device. See how to [configure certificates](azure-stack-edge-pro-2-deploy-configure-certificates.md).
+1. Get the activation key from the Azure portal and activate the new device. See how to [activate the device](azure-stack-edge-pro-2-deploy-activate.md).
+
+You are now ready to restore the share data and deploy the workloads that you were running on the old device.
+
+### [Migrate to Azure Stack Edge Pro GPU](#tab/migrate-to-ase-pro-gpu)
+
 ### 1. Create new order
 
 You need to create a new order (and a new resource) for your *target* device. The target device must be activated against the GPU resource and not against the FPGA resource.
@@ -144,6 +236,8 @@ Follow these steps to configure the *target* device via the Azure portal:
 
 You are now ready to restore the share data and deploy the workloads that you were running on the old device.
 
+---
+
 ## Migrate data
 
 You will now copy data from the source device to the Edge cloud shares and Edge local shares on your *target* device.
@@ -194,8 +288,7 @@ After migration, verify that all the data has migrated and the workloads have be
 
 ## Erase data, return
 
-After the data migration is complete, erase local data and return the source device. Follow the steps in [Return your Azure Stack Edge Pro device](azure-stack-edge-return-device.md).
-
+After the data migration is complete, erase local data and return the source device. Follow the steps in [Return your Azure Stack Edge Pro FPGA device](azure-stack-edge-return-device.md).
 
 ## Next steps
 
diff --git a/includes/azure-stack-edge-fpga-eol.md b/includes/azure-stack-edge-fpga-eol.md
@@ -2,9 +2,9 @@
 author: v-dalc
 ms.service: databox  
 ms.topic: include
-ms.date: 03/15/2021
+ms.date: 06/07/2023
 ms.author: alkohli
 ---
 
 > [!IMPORTANT]
-> Azure Stack Edge Pro FPGA devices will reach end-of-life in February 2024. If you are considering new deployments, we recommend that you explore [Azure Stack Edge Pro GPU](../articles/databox-online/azure-stack-edge-gpu-overview.md) devices for your workloads.
+> Azure Stack Edge Pro FPGA devices will reach end-of-life in February 2024. If you are considering new deployments, we recommend that you explore [Azure Stack Edge Pro 2](../articles/databox-online/azure-stack-edge-pro-2-overview.md) or [Azure Stack Edge Pro GPU](../articles/databox-online/azure-stack-edge-gpu-overview.md) devices for your workloads.
