Merge pull request #17763 from LouisBerner/v-loberner-ado-march-2025-freshness

v-shils · web-flow · commit 865f4ade2a2c · 2025-05-01T11:44:08.000-07:00
Freshness updates for Mar-2025.
diff --git a/azure-local/concepts/single-server-clusters.md b/azure-local/concepts/single-server-clusters.md
@@ -6,7 +6,7 @@ ms.author: robess
 ms.topic: overview
 ms.reviewer: kimlam
 ms.lastreviewed: 04/01/2024
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ---
 
 # Using Azure Stack HCI on a single server
diff --git a/azure-local/manage/remote-support-arc-extension.md b/azure-local/manage/remote-support-arc-extension.md
@@ -6,7 +6,7 @@ ms.author: robess
 ms.topic: overview
 ms.reviewer: shisab
 ms.lastreviewed: 01/19/2024
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ---
 
 # Azure Local Remote Support ARC extension overview
diff --git a/azure-stack/operator/azure-site-recovery-known-issues.md b/azure-stack/operator/azure-site-recovery-known-issues.md
@@ -5,7 +5,7 @@ author: ronmiab
 ms.author: robess
 ms.topic: troubleshooting
 ms.custom: linux-related-content
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.reviewer: rtiberiu
 ms.lastreviewed: 04/25/2024
 ---
@@ -31,20 +31,20 @@ When you try to protect a VM with a disk of 1023Gb, the following behavior occur
 
 The current workaround for this issue is to create a new disk (of 1,022 GB or less), attach it to your source VM, copy the data from the 1,023 GB disk to the new one, and then remove the 1,023 GB disk from the source VM. Once this procedure is done, and the VM has all disks smaller or equal to 1,022 GB, you can enable the protection using Azure Site Recovery.
 
-## Re-protection: available data disk slots on appliance
+## Reprotection: available data disk slots on appliance
 
-1. Ensure the appliance VM has enough data disk slots, as the replica disks for re-protection are attached to the appliance.
+1. Ensure the appliance VM has enough data disk slots, as the replica disks for reprotection are attached to the appliance.
 
-2. The initial allowed number of disks being re-protected at the same time is 31. The default size of the appliance created from the marketplace item is [Standard_DS4_v2](../user/azure-stack-vm-sizes.md#dsv2-series), which supports up to 32 data disks, and the appliance itself uses one data disk.
+2. The initial allowed number of disks being reprotected at the same time is 31. The default size of the appliance created from the marketplace item is [Standard_DS4_v2](../user/azure-stack-vm-sizes.md#dsv2-series), which supports up to 32 data disks, and the appliance itself uses one data disk.
 
 3. If the sum of the protected VMs is greater than 31, perform one of the following actions:
-    - Split the VMs that require re-protection into smaller groups to ensure that the number of disks re-protected at the same time doesn't exceed the maximum number of data disks the appliance supports.
+    - Split the VMs that require reprotection into smaller groups to ensure that the number of disks reprotected at the same time doesn't exceed the maximum number of data disks the appliance supports.
     - Increase the size of the Azure Site Recovery appliance VM.
 
     >[!NOTE]
     > We don't test and validate large VM SKUs for the appliance VM.
 
-4. If you're trying to re-protect a VM, but there aren't enough slots on the appliance to hold the replication disks, the error message **An internal error occurred** displays. You can check the number of the data disks currently on the appliance, or sign in to the appliance, go to **Event Viewer**, and open logs for **Azure Site Recovery** under **Applications and Services Logs**:
+4. If you're trying to reprotect a VM, but there aren't enough slots on the appliance to hold the replication disks, the error message **An internal error occurred** displays. You can check the number of the data disks currently on the appliance, or sign in to the appliance, go to **Event Viewer**, and open logs for **Azure Site Recovery** under **Applications and Services Logs**:
 
     :::image type="content" source="../operator/media/azure-site-recovery/known-issues/event-viewer.png" alt-text="Sample screenshot of Event Viewer for Azure Site Recovery."lightbox="media/azure-site-recovery/known-issues/event-viewer.png":::
 
@@ -83,9 +83,9 @@ The current workaround for this issue is to create a new disk (of 1,022 GB or le
 
     :::image type="content" source="../operator/media/azure-site-recovery/known-issues/mobility-agent-update.png" alt-text="Sample screenshot of mobility agent update check."lightbox="media/azure-site-recovery/known-issues/mobility-agent-update.png":::
 
-## Re-protect manual resync isn't supported yet
+## Reprotect manual resync isn't supported yet
 
-After the re-protect job is complete, the replication is started in sequence. During replication, there may be cases that require a resync, which means a new initial replication is triggered to synchronize all the changes.
+After the reprotect job is complete, the replication is started in sequence. During replication, there may be cases that require a resync, which means a new initial replication is triggered to synchronize all the changes.
 
 There are two types of resync:
 
@@ -103,7 +103,7 @@ There are two types of resync:
 
 ## Known issues in PowerShell automation
 
-- If you leave `$failbackPolicyName` and `$failbackExtensionName` empty or null, the re-protect can fail. See the following examples:
+- If you leave `$failbackPolicyName` and `$failbackExtensionName` empty or null, the reprotect can fail. See the following examples:
 
     :::image type="content" source="../operator/media/azure-site-recovery/known-issues/reprotect-fail-error-1.png" alt-text="Sample screenshot of a VM failed to perform operation error."lightbox="media/azure-site-recovery/known-issues/reprotect-fail-error-1.png":::
 
@@ -147,5 +147,5 @@ To avoid this issue, make sure to first remove the protection from all items in
 
 ## Next steps
 
-- [Azure Site Recovery on Azure Stack Hub](azure-site-recovery-overview.md)
-- [Azure Site Recovery on Azure Stack Hub capacity planning](azure-site-recovery-capacity-planning.md)
+- [Azure Site Recovery on Azure Stack Hub](azure-site-recovery-overview.md).
+- [Azure Site Recovery on Azure Stack Hub capacity planning](azure-site-recovery-capacity-planning.md).
diff --git a/azure-stack/user/overview-patterns-solution-examples.md b/azure-stack/user/overview-patterns-solution-examples.md
@@ -3,7 +3,7 @@ title: Hybrid patterns and examples for Azure and Azure Stack Hub
 description: An overview of hybrid patterns and solution examples for learning and building hybrid solutions on Azure and Azure Stack Hub.
 author: ronmiab 
 ms.topic: overview
-ms.date: 04/04/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod
 ms.lastreviewed: 05/24/2021
diff --git a/azure-stack/user/pattern-cicd-pipeline.md b/azure-stack/user/pattern-cicd-pipeline.md
@@ -3,7 +3,7 @@ title: The DevOps pattern in Azure Stack Hub
 description: Learn about the DevOps pattern so you can ensure consistency across deployments in Azure and Azure Stack Hub.
 author: ronmiab 
 ms.topic: article
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod
 ms.lastreviewed: 11/05/2019
diff --git a/azure-stack/user/pattern-cross-cloud-scale-on-premises-data.md b/azure-stack/user/pattern-cross-cloud-scale-on-premises-data.md
@@ -3,7 +3,7 @@ title: Cross-cloud scaling (on-premises data) pattern in Azure Stack Hub
 description: Learn how to build a scalable cross-cloud app that uses on-premises data in Azure and Azure Stack Hub.
 author: ronmiab 
 ms.topic: article
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod
 ms.lastreviewed: 11/05/2019
diff --git a/azure-stack/user/pattern-cross-cloud-scale.md b/azure-stack/user/pattern-cross-cloud-scale.md
@@ -3,10 +3,10 @@ title: Cross-cloud scaling pattern in Azure Stack Hub
 description: Learn how to build a scalable cross-cloud app on Azure and Azure Stack Hub.
 author: ronmiab 
 ms.topic: article
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod
-ms.lastreviewed: 11/05/2019
+ms.lastreviewed: 04/05/2019
 
 # Intent: As an Azure Stack Hub user, I want to build a scalable cross-cloud app on Azure and Azure Stack Hub.
 # Keyword: cross-cloud scaling pattern azure stack hub
diff --git a/azure-stack/user/pattern-geo-distributed.md b/azure-stack/user/pattern-geo-distributed.md
@@ -3,7 +3,7 @@ title: Geo-distributed app pattern in Azure Stack Hub
 description: Learn about the geo-distributed app pattern for the intelligent edge using Azure and Azure Stack Hub.
 author: ronmiab 
 ms.topic: article
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod2019
 
diff --git a/azure-stack/user/pattern-highly-available-kubernetes.md b/azure-stack/user/pattern-highly-available-kubernetes.md
@@ -3,7 +3,7 @@ title: High availability Kubernetes pattern using Azure and Azure Stack Hub
 description: Learn how a Kubernetes cluster solution provides high availability using Azure and Azure Stack Hub.
 author: ronmiab 
 ms.topic: article
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: bryanla
 ms.lastreviewed: 12/03/2020
@@ -115,7 +115,7 @@ The Kubernetes cluster itself consists of, and is built on top of Azure (Stack)
 - [Control plane nodes](/azure/aks/concepts-clusters-workloads#control-plane) (master) provide the core Kubernetes services and orchestration of application workloads.
 - [Worker nodes](/azure/aks/concepts-clusters-workloads#nodes-and-node-pools) (worker) run your application workloads.
 
-When selecting VM sizes for the initial deployment, there are several considerations:  
+When you select VM sizes for the initial deployment, there are several considerations:  
 
 - **Cost** - When planning your worker nodes, keep in mind the overall cost per VM you incur. For example, if your application workloads require limited resources, you should plan to deploy smaller sized VMs. Azure Stack Hub, like Azure, is normally billed on a consumption basis, so appropriately sizing the VMs for Kubernetes roles is crucial to optimizing consumption costs. 
 
@@ -125,7 +125,7 @@ When selecting VM sizes for the initial deployment, there are several considerat
 
     Scaling is done manually using the AKS Engine helper VM that was used to deploy the Kubernetes cluster initially. For more information, see [Scaling Kubernetes clusters](https://github.com/Azure/aks-engine/blob/master/docs/topics/scale.md)
 
-- **Quotas** - Consider the [quotas](/azure-stack/operator/azure-stack-quota-types) you've configured when planning out an AKS deployment on your Azure Stack Hub. Make sure each [subscription](/azure-stack/operator/service-plan-offer-subscription-overview) has the proper plans and the quotas configured. The subscription needs to accommodate the amount of compute, storage, and other services needed for your clusters as they scale out.
+- **Quotas** - Consider the [quotas](/azure-stack/operator/azure-stack-quota-types) you configure when planning out an AKS deployment on your Azure Stack Hub. Make sure each [subscription](/azure-stack/operator/service-plan-offer-subscription-overview) has the proper plans and the quotas configured. The subscription needs to accommodate the amount of compute, storage, and other services needed for your clusters as they scale out.
 
 - **Application workloads** - Refer to the [Clusters and workloads concepts](/azure/aks/concepts-clusters-workloads#nodes-and-node-pools) in the Kubernetes core concepts for Azure Kubernetes Service document. This article helps you scope the proper VM size based on the compute and memory needs of your application.  
 
@@ -151,7 +151,7 @@ For the application layer, the most important consideration is whether the appli
 
 Exposing an application using a public IP via a Load Balancer or an Ingress Controller doesn't nessecarily mean that the application is now accessible via the Internet. It's possible for Azure Stack Hub to have a public IP address that is only visible on the local intranet - not all public IPs are truly Internet-facing.
 
-The previous block considers ingress traffic to the application. Another topic that must be considered for a successful Kubernetes deployment is outbound/egress traffic. Here are a few use cases that require egress traffic:
+The previous block considers ingress traffic to the application. Another consideration for a successful Kubernetes deployment is outbound/egress traffic. Here are a few use cases that require egress traffic:
 
 - Pulling Container Images stored on DockerHub or Azure Container Registry
 - Retrieving Helm Charts
@@ -191,7 +191,7 @@ In our architecture, these layers were considered:
 
 **Configuration**
 
-Configuration includes the configuration of Azure Stack Hub, AKS Engine, and the Kubernetes cluster itself. The configuration should be automated as much as possible, and stored as Infrastructure-as-Code in a Git-based version control system like Azure DevOps or GitHub. These settings cannot easily be synchronized across multiple deployments. Therefore we recommend storing and applying configuration from the outside, and using DevOps pipeline.
+Configuration includes the configuration of Azure Stack Hub, AKS Engine, and the Kubernetes cluster itself. The configuration should be automated as much as possible, and stored as Infrastructure-as-Code in a Git-based version control system like Azure DevOps or GitHub. These settings can't easily be synchronized across multiple deployments. Therefore we recommend storing and applying configuration from the outside, and using DevOps pipeline.
 
 **Application**
 
@@ -372,7 +372,7 @@ There are Microsoft Partner solutions that can extend the capabilities of Azure
 
 ## Storage and data solutions
 
-As described in [Data and storage considerations](#data-and-storage-considerations), Azure Stack Hub currently doesn't have a native solution to replicate storage across multiple instances. Unlike Azure, the capability of replicating storage across multiple regions does not exist. In Azure Stack Hub, each instance is its own distinct cloud. However, solutions are available from Microsoft Partners that enable storage replication across Azure Stack Hubs and Azure. 
+As described in [Data and storage considerations](#data-and-storage-considerations), Azure Stack Hub currently doesn't have a native solution to replicate storage across multiple instances. Unlike Azure, the capability of replicating storage across multiple regions doesn't exist. In Azure Stack Hub, each instance is its own distinct cloud. However, solutions are available from Microsoft Partners that enable storage replication across Azure Stack Hubs and Azure. 
 
 **SCALITY**
 
diff --git a/azure-stack/user/pattern-out-of-stock-at-edge.md b/azure-stack/user/pattern-out-of-stock-at-edge.md
@@ -3,7 +3,7 @@ title: Out of stock detection using Azure and Azure Stack Edge
 description: Learn how to use Azure and Azure Stack Edge services to implement out of stock detection.
 author: ronmiab 
 ms.topic: article
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod
 ms.lastreviewed: 05/24/2021
diff --git a/azure-stack/user/pattern-retail-footfall-detection.md b/azure-stack/user/pattern-retail-footfall-detection.md
@@ -3,7 +3,7 @@ title: Footfall detection pattern using Azure and Azure Stack Hub
 description: Learn how to use Azure and Azure Stack Hub to implement an AI-based footfall detection solution for analyzing retail store traffic.
 author: ronmiab 
 ms.topic: article
-ms.date: 10/31/2019
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod
 ms.lastreviewed: 10/31/2019
@@ -25,7 +25,7 @@ Contoso would like to find an unobtrusive, privacy-friendly way to determine the
 
 ## Solution
 
-This retail analytics pattern uses a tiered approach to inferencing at the edge. By using the Custom Vision AI Dev Kit, only images with human faces are sent for analysis to a private Azure Stack Hub that runs Azure Cognitive Services. Anonymized, aggregated data is sent to Azure for aggregation across all stores and visualization in Power BI. Combining the edge and public cloud lets Contoso take advantage of modern AI technology while also remaining in compliance with their corporate policies and respecting their customers' privacy.
+This retail analytics pattern uses a tiered approach to inferencing at the edge. When you use the Custom Vision AI Dev Kit, only images with human faces are sent for analysis to a private Azure Stack Hub that runs Azure Cognitive Services. Anonymized, aggregated data is sent to Azure for aggregation across all stores and visualization in Power BI. Combining the edge and public cloud lets Contoso take advantage of modern AI technology while also remaining in compliance with their corporate policies and respecting their customers' privacy.
 
 [![Footfall detection pattern solution](media/pattern-retail-footfall-detection/solution-architecture.png)](media/pattern-retail-footfall-detection/solution-architecture.png)
 
@@ -61,7 +61,7 @@ Consider the following points when deciding how to implement this solution:
 
 ### Scalability
 
-To enable this solution to scale across multiple cameras and locations, you'll need to make sure that all of the components can handle the increased load. You may need to take actions like:
+To enable this solution to scale across multiple cameras and locations, you must make sure that all of the components can handle the increased load. You may need to take actions like:
 
 - Increase the number of Stream Analytics streaming units.
 - Scale out the Face API deployment.
diff --git a/azure-stack/user/pattern-tiered-data-analytics.md b/azure-stack/user/pattern-tiered-data-analytics.md
@@ -3,7 +3,7 @@ title: Tiered data for analytics pattern using Azure and Azure Stack Hub
 description: Learn how to use Azure and Azure Stack Hub to implement a tiered data solution across the hybrid cloud.
 author: ronmiab 
 ms.topic: article
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod
 ms.lastreviewed: 11/05/2019
@@ -50,7 +50,7 @@ This pattern uses the following components:
 |----------|-----------|-------------|
 | Azure | Storage | An [Azure Storage](/azure/storage/) account provides a sterile data consumption endpoint. Azure Storage is Microsoft's cloud storage solution for modern data storage scenarios. Azure Storage offers a massively scalable object store for data objects and a file system service for the cloud. It also provides a messaging store for reliable messaging and a NoSQL store. |
 | Azure Stack Hub | Storage | An [Azure Stack Hub Storage](/azure-stack/user/azure-stack-storage-overview) account is used for multiple services:<br><br>- **Blob storage** for raw data storage. Blob storage can hold any type of text or binary data, such as a document, media file, or app installer. Every blob is organized under a container. Containers provide a useful way to assign security policies to groups of objects. A storage account may contain any number of containers, and a container can contain any number of blobs, up to the 500-TB capacity limit of the storage account.<br>- **Blob storage** for data archive. There are benefits to low-cost storage for cool data archiving. Examples of cool data include backups, media content, scientific data, compliance, and archival data. In general, any data that's accessed infrequently is considered cool storage. Tiering data based on attributes like frequency of access and retention period. Customer data is infrequently accessed but requires similar latency and performance to hot data.<br>- **Queue storage** for processed data storage. Queue storage provides cloud messaging between app components. In designing apps for scale, app components are often decoupled so they can scale independently. Queue storage delivers asynchronous messaging for communication between app components, whether they're running in the cloud, on the desktop, an on-premises server, or a mobile device. Queue storage also supports managing asynchronous tasks and building process work flows. |
-| | Azure Functions | The [Azure Functions](/azure/azure-functions/) service is provided by the [Azure App Service on Azure Stack Hub](/azure-stack/operator/azure-stack-app-service-overview) resource provider. Azure Functions lets you execute your code in a simple, serverless environment in response to a variety of events. Azure Functions scale to meet demand without having to create a VM or publish a web app, using the programming language of your choice. Functions are used by the solution for:<br><br>- **Data intake**<br>- **Data sterilization.** Manually triggered functions can perform scheduled data processing, clean up, and archiving. Examples may include nightly customer list scrubs and monthly report processing.|
+| | Azure Functions | The [Azure Functions](/azure/azure-functions/) service is provided by the [Azure App Service on Azure Stack Hub](/azure-stack/operator/azure-stack-app-service-overview) resource provider. Azure Functions lets you execute your code in a simple, serverless environment in response to various events. Azure Functions scale to meet demand without having to create a VM or publish a web app, using the programming language of your choice. Functions are used by the solution for:<br><br>- **Data intake**<br>- **Data sterilization.** Manually triggered functions can perform scheduled data processing, clean up, and archiving. Examples may include nightly customer list scrubs and monthly report processing.|
 
 ## Issues and considerations
 
diff --git a/azure-stack/user/pattern-train-machine-learning-model-at-edge.md b/azure-stack/user/pattern-train-machine-learning-model-at-edge.md
@@ -3,7 +3,7 @@ title: Train machine learning model at the edge pattern
 description: Learn how to do machine learning model training at the edge with Azure and Azure Stack Hub.
 author: ronmiab 
 ms.topic: article
-ms.date: 04/03/2025
+ms.date: 04/25/2025
 ms.author: robess
 ms.reviewer: anajod
 ms.lastreviewed: 11/05/2019
