Merge pull request #188883 from alkohli/2202rn

Updates to release notes and update article

Author: PRMerger17

articles/databox-online/azure-stack-edge-gpu-2202-release-notes.md

@@ -23,18 +23,28 @@ This article applies to the **Azure Stack Edge 2202** release, which maps to sof
 
 ## What's new
 
-The 2202 release introduces clustering for Azure Stack Edge. You can now deploy a two-node device cluster in addition to a single node device. The clustering feature is in preview and is available only for the Azure Stack Edge Pro GPU devices.
+The 2202 release has the following features and enhancements:
 
-For more information, see [What is clustering on Azure Stack Edge?](azure-stack-edge-gpu-clustering-overview.md).
+- **Clustering support** - This release introduces clustering support for Azure Stack Edge. You can now deploy a two-node device cluster in addition to a single node device. The clustering feature is in preview and is available only for the Azure Stack Edge Pro GPU devices.
 
+    For more information, see [What is clustering on Azure Stack Edge?](azure-stack-edge-gpu-clustering-overview.md).
 
-<!--## Issues fixed in 2202 release
+- **Password reset extension** - Starting this release, password reset extension for both Windows and Linux virtual machines (VMs) are enabled.
+- **VM improvements** - A new VM size F12 was added in this release.
+- **Multi-Access Edge Computing (MEC) and Virtual Network Functions (VNF) improvements**:
+    - In this release, VM create and delete for VNF create and delete were parallelized. This has significantly reduced the creation time for VNFs that contain multiple VMs. 
+    - The VHD ingestion job resource clean up was moved out of VNF create and delete. This reduced the VNF creation and deletion times.
+- **Updates for Azure Arc and Edge container registry** - Azure Arc and Edge container registry versions were updated. For more information, see [About updates](azure-stack-edge-gpu-install-update.md#about-latest-update).
+
+
+
+## Issues fixed in 2202 release
 
 The following table lists the issues that were release noted in previous releases and fixed in the current release.
 
 | No. | Feature | Issue | 
 | --- | --- | --- |
-|**1.**|Multi-Access Edge Compute | In  previous releases, the Azure Stack Edge device did not send VNF operation results back to the Azure Network Function Manager, owing to the MEC Operation Manager (a component of MEC agent) being reset.  |-->
+|**1.**|Azure Arc | In the previous releases, there was a bug in the proxy implementation that resulted in Azure Arc not functioning properly. In this version, a web proxy bypass  list was added to the Azure Arc *no_proxy* list.   |
 
 
 ## Known issues in 2202 release

articles/databox-online/azure-stack-edge-gpu-install-update.md

@@ -31,7 +31,7 @@ The current update is Update 2202. This update installs two updates, the device
 
 For information on what's new in this update, go to [Release notes](azure-stack-edge-gpu-2202-release-notes.md).
 
-**To apply 2202 update, your device must be running 2106.** 
+**To apply 2202 update, your device must be running 2106 or later.** 
 
 - If you are not running the minimal supported version, you'll see this error: *Update package cannot be installed as its dependencies are not met*. 
 - You can update to 2106 from an older version and then install 2202.
@@ -43,7 +43,7 @@ The procedure to update an Azure Stack Edge is the same whether it is a single-n
 
 - **Single node** - For a single node device, installing an update or hotfix is disruptive and will restart your device. Your device will experience a downtime for the entire duration of the update.
 
-- **Two-node** - For a two-node cluster, this is an optimized update. The two-node cluster may experience short, intermittent disruptions while the update is in progress. We recommend that you shouldn't perform any operations on the other node when update is in progress on the first node of the cluster. 
+- **Two-node** - For a two-node cluster, this is an optimized update. The two-node cluster may experience short, intermittent disruptions while the update is in progress. We recommend that you shouldn't perform any operations on the device node when update is in progress. 
 
     The Kubernetes worker VMs will go down when a node goes down. The Kubernetes master VM will fail over to the other node. Workloads will continue to run. For more information, see [Kubernetes failover scenarios for Azure Stack Edge](azure-stack-edge-gpu-kubernetes-failover-scenarios.md).