Merge pull request #263640 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)

Author: Taojunshen

articles/active-directory-b2c/identity-provider-amazon.md

@@ -91,7 +91,7 @@ You need to store the client secret that you previously recorded in your Azure A
 
 ## Configure Amazon as an identity provider
 
-To enable users to sign in using a Amazon account, you need to define the account as a claims provider. that Azure AD B2C can communicate with through an endpoint. The endpoint provides a set of claims that are used by Azure AD B2C to verify that a specific user has authenticated.
+To enable users to sign in using an Amazon account, you need to define the account as a claims provider. that Azure AD B2C can communicate with through an endpoint. The endpoint provides a set of claims that are used by Azure AD B2C to verify that a specific user has authenticated.
 
 You can define an Amazon account as a claims provider by adding it to the **ClaimsProviders** element in the extension file of your policy.
 

articles/ai-services/document-intelligence/concept-read.md

@@ -107,15 +107,7 @@ Try extracting text from forms and documents using the Document Intelligence Stu
 
 ### Microsoft Office and HTML text extraction
 
-Use the parameter `api-version=2023-07-31` when using the REST API or the corresponding SDKs of that API version to extract text from Microsoft Word, Excel, PowerPoint, and HTML files. The following illustration shows extraction of the digital text and text in the Word document by running OCR on the images. Text from embedded images isn't included in the extraction.
-
-> [!NOTE]
->
-> * [Add-on capabilities](concept-add-on-capabilities.md) are not supported for Microsoft Word, Excel, PowerPoint, and HTML file formats.
-
-:::image type="content" source="media/office-to-ocr.png" alt-text="Screenshot of a Microsoft Word document extracted by Document Intelligence Read OCR.":::
-
-The page units in the model output are computed as shown:
+When analyzing Microsft Office and HTML files, the page units in the model output are computed as shown:
 
  **File format**   | **Computed page unit**   | **Total pages**  |
 | --- | --- | --- |

articles/ai-services/document-intelligence/concept-retrieval-augumented-generation.md

@@ -45,7 +45,7 @@ Markdown is a structured and formatted markup language and a popular input for e
 
 * **Scalability and AI quality**. The Layout model is highly scalable in Optical Character Recognition (OCR), table extraction, and [document structure analysis](concept-layout.md#document-layout-analysis). It supports [309 printed and 12 handwritten languages](language-support-ocr.md#model-id-prebuilt-layout), further ensuring high-quality results driven by AI capabilities.
 
-* **Large learning model (LLM) compatibility**. The Layout model Markdown formatted output is LLM friendly and facilitates seamless integration into your workflows. You can turn any table in a document into Markdown format and avoid extensive effort parsing the documents for greater LLM understanding.
+* **Large language model (LLM) compatibility**. The Layout model Markdown formatted output is LLM friendly and facilitates seamless integration into your workflows. You can turn any table in a document into Markdown format and avoid extensive effort parsing the documents for greater LLM understanding.
 
 **Text image processed with Document Intelligence Studio and output to MarkDown using Layout model**
 

articles/ai-services/document-intelligence/overview.md

@@ -63,7 +63,7 @@ Document analysis models enable text extraction from forms and documents and ret
    :::column-end:::
    :::column span="":::
       :::image type="icon" source="media/overview/icon-layout.png" link="#layout":::</br>
-    [**Layout**](#layout) | Extract text </br>and document structure.
+    [**Layout**](#layout) | Extract text, tables, </br>and document structure.
    :::column-end:::
   :::row-end:::
 :::moniker-end
@@ -281,7 +281,7 @@ You can use Document Intelligence to automate document processing in application
 
 |Model ID| Description |Automation use cases | Development options |
 |----------|--------------|-------------------------|-----------|
-|[**prebuilt-read**](concept-read.md)|&#9679; Extract **text** from documents.</br>&#9679; [Data and field extraction](concept-read.md#read-model-data-extraction)| &#9679; Contract processing. </br>&#9679; Financial or medical report processing.|&#9679; [**Document Intelligence Studio**](https://formrecognizer.appliedai.azure.com/studio/read)</br>&#9679; [**REST API**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-3.0.0&preserve-view=true&pivots=programming-language-rest-api)</br>&#9679; [**C# SDK**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-3.0.0&preserve-view=true&pivots=programming-language-csharp)</br>&#9679; [**Python SDK**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-3.0.0&preserve-view=true&pivots=programming-language-python)</br>&#9679; [**Java SDK**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-3.0.0&preserve-view=true&pivots=programming-language-java)</br>&#9679; [**JavaScript**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-3.0.0&preserve-view=true&pivots=programming-language-javascript) |
+|[**prebuilt-read**](concept-read.md)|&#9679; Extract **text** from documents.</br>&#9679; [Data extraction](concept-read.md#read-model-data-extraction)| &#9679; Digitizing any document. </br>&#9679; Compliance and auditing. &#9679; Processing handwritten notes before translation.|&#9679; [**Document Intelligence Studio**](https://formrecognizer.appliedai.azure.com/studio/read)</br>&#9679; [**REST API**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-4.0.0&preserve-view=true&pivots=programming-language-rest-api)</br>&#9679; [**C# SDK**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-4.0.0&preserve-view=true&pivots=programming-language-csharp)</br>&#9679; [**Python SDK**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-4.0.0&preserve-view=true&pivots=programming-language-python)</br>&#9679; [**Java SDK**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-4.0.0&preserve-view=true&pivots=programming-language-java)</br>&#9679; [**JavaScript**](how-to-guides/use-sdk-rest-api.md?view=doc-intel-4.0.0&preserve-view=true&pivots=programming-language-javascript) |
 
 > [!div class="nextstepaction"]
 > [Return to model types](#document-analysis-models)
@@ -292,7 +292,7 @@ You can use Document Intelligence to automate document processing in application
 
 | Model ID | Description |Automation use cases | Development options |
 |----------|--------------|-------------------------|-----------|
-|[**prebuilt-layout**](concept-layout.md) |&#9679; Extract **text and layout** information from documents.</br>&#9679; [Data and field extraction](concept-layout.md#data-extraction)</br>&#9679; Layout API is updated to a prebuilt model. |&#9679; Document indexing and retrieval by structure.</br>&#9679; Preprocessing prior to OCR analysis. |&#9679; [**Document Intelligence Studio**](https://formrecognizer.appliedai.azure.com/studio/layout)</br>&#9679; [**REST API**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true)</br>&#9679; [**C# SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true#layout-model)</br>&#9679; [**Python SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true#layout-model)</br>&#9679; [**Java SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true#layout-model)</br>&#9679; [**JavaScript**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true#layout-model)|
+|[**prebuilt-layout**](concept-layout.md) |&#9679; Extract **text and layout** information from documents.</br>&#9679; [Data extraction](concept-layout.md#data-extraction) |&#9679; Document indexing and retrieval by structure.</br>&#9679; Financial and medical report analysis. |&#9679; [**Document Intelligence Studio**](https://formrecognizer.appliedai.azure.com/studio/layout)</br>&#9679; [**REST API**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>&#9679; [**C# SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true#layout-model)</br>&#9679; [**Python SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true#layout-model)</br>&#9679; [**Java SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true#layout-model)</br>&#9679; [**JavaScript**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true#layout-model)|
 
 > [!div class="nextstepaction"]
 > [Return to model types](#document-analysis-models)

articles/azure-arc/servers/plan-evaluate-on-azure-virtual-machine.md

@@ -90,14 +90,14 @@ When Azure Arc-enabled servers is configured on the VM, you see two representati
    If your Azure VM is running CentOS, Red Hat, or SUSE Linux Enterprise Server (SLES), perform the following steps to configure firewalld:
 
    ```bash
-   sudo firewall-cmd --permanent --direct --add-rule ipv4 filter OUTPUT 1 -p tcp -d 169.254.169.254 -j DROP
+   sudo firewall-cmd --permanent --direct --add-rule ipv4 filter OUTPUT 1 -p tcp -d 169.254.169.254 -j REJECT
    sudo firewall-cmd --reload
    ```
 
    For other distributions, consult your firewall docs or configure a generic iptables rule with the following command:
 
    ```bash
-   sudo iptables -A OUTPUT -d 169.254.169.254 -j DROP
+   sudo iptables -A OUTPUT -d 169.254.169.254 -j REJECT
    ```
 
    > [!NOTE]

articles/azure-functions/durable/quickstart-python-vscode.md

@@ -246,7 +246,7 @@ def hello_orchestrator(context):
 # Activity
 @myApp.activity_trigger(input_name="city")
 def hello(city: str):
-    return "Hello " + city   
+    return f"Hello {city}"
 ```
 
 Review the table below for an explanation of each function and its purpose in the sample.

articles/communication-services/concepts/router/classification-concepts.md

@@ -24,6 +24,10 @@ The process of classifying a Job involves optionally setting the following prope
 - Worker Selectors
 - Queue ID
 
+## Fallback queue
+
+The fallback queue is used when queue selectors, resulting from queue selector attachments, are unable to select a queue _and_ the job does not have a `queueId`. In this case, if the fallback queue is defined, the job is assigned to it.
+
 ## Prioritization rule
 
 The priority of a Job can be resolved during classification using one of many rule engines.

articles/networking/nva-accelerated-connections.md

@@ -9,9 +9,9 @@ ms.author: steveesp
 
 ---
 
-# Accelerated connections and NVAs (Limited GA)
+# Accelerated connections on NVAs or other VMs (Limited GA)
 
-This article helps you understand the **Accelerated Connections** feature. When Accelerated Connections is enabled on the virtual network interface (vNIC) with Accelerated Networking, this feature significantly improves networking efficiency, resulting in enhanced overall performance. This high-performance feature offers industry leading performance in Connections Per Second (CPS) optimization, along with improvements to handling large amounts of simultaneous connections. The feature also improves the number of Total Active Connections for network intensive workloads. Accelerated Connections is configured at the network interface level to allow flexibility to size the performance at vNIC. This especially benefits smaller VM sizes. These benefits are available for  Network Virtual Appliances (NVAs) with a large number of connections. To access this feature during limited General Availability (limited GA), use the [sign-up form](https://go.microsoft.com/fwlink/?linkid=2223706).
+This article helps you understand the **Accelerated Connections** feature. When Accelerated Connections is enabled on the virtual network interface (vNIC) with Accelerated Networking, this feature significantly improves networking efficiency, resulting in enhanced overall performance. This high-performance feature offers industry leading performance in Connections Per Second (CPS) optimization, along with improvements to handling large amounts of simultaneous connections. The feature also improves the number of Total Active Connections for network intensive workloads. Accelerated Connections is configured at the network interface level to allow flexibility to size the performance at vNIC. This especially benefits smaller VM sizes. These benefits are available for  Network Virtual Appliances (NVAs) as well as Virtual Machines (VMs) with a large number of connections. To access this feature during limited General Availability (limited GA), use the [sign-up form](https://go.microsoft.com/fwlink/?linkid=2223706).
 
 > [!IMPORTANT]
 > This feature is currently in limited General Availability (GA) and customer sign-up is needed to use it.
@@ -23,13 +23,11 @@ Feature enablement is at the vNIC level and irrespective of the VM size, making
 
 There are a total of four performance tiers at vNIC level which gives the flexibility to control the networking capability. All tiers have different networking capabilities. Instructions on how to select performance tier based on VM sizes will be provided after a customer sign up for the feature.
 
-Accelerated Connections is implemented at the network interface level to allow maximum flexibility of network capacity. Multiple vNICs can be configured with this enhancement, the number depends on the supported VM family. Network Virtual Appliances (NVAs) on Azure Marketplace will be the first workloads to be offered this ground-breaking feature.
+Accelerated Connections is implemented at the network interface level to allow maximum flexibility of network capacity. Multiple vNICs can be configured with this enhancement, the number depends on the supported VM family. VM families up to v4 will be the first workloads to be offered this ground-breaking feature.
+
+Network Virtual Appliances (NVAs) with the largest scale workloads requiring virtual firewalls, virtual switches, load balancers and other critical network features, as well as Virtual Machines (VMs) with high connection workloads will experience dramatically improved CPS performance with Accelerated Connections. 
 
-Network Virtual Appliances (NVAs) with the largest scale workloads requiring virtual firewalls, virtual switches, load balancers and other critical network features will experience dramatically improved CPS performance with Accelerated Connections. 
 
-> [!NOTE]
-> During limited GA, this feature is only supported for NVAs available on the [Azure Marketplace](https://azuremarketplace.microsoft.com/marketplace/apps?search=network%20virtual%20appliance&page=1&filters=virtual-machine-images%3Bpartners).
->
 
 **Architecture diagram**
 
@@ -45,7 +43,7 @@ Network Virtual Appliances (NVAs) with the largest scale workloads requiring vir
 
 ### Considerations and limitations
 
-* This feature is available only for NVAs deployed from Azure Marketplace during limited GA.
+* This feature is available for NVAs deployed from Azure Marketplace and Azure Virtual Machines during limited GA.
 * To enable this feature, you must sign up using the [sign-up form](https://go.microsoft.com/fwlink/?linkid=2223706).
 * This feature can be enabled and is supported only on new deployments.
 * Feature support may vary as per the NVAs available on Marketplace.

articles/openshift/howto-create-a-storageclass.md

@@ -55,7 +55,7 @@ ARO_RESOURCE_GROUP=aro-rg
 CLUSTER=cluster
 ARO_SERVICE_PRINCIPAL_ID=$(az aro show -g $ARO_RESOURCE_GROUP -n $CLUSTER --query servicePrincipalProfile.clientId -o tsv)
 
-az role assignment create --role Contributor --scope /subscriptions/mySubscriptionID/resourceGroups/myResourceGroupName --assignee $ARO_SERVICE_PRINCIPAL_ID -g $AZURE_FILES_RESOURCE_GROUP
+az role assignment create --role Contributor --scope /subscriptions/mySubscriptionID/resourceGroups/$AZURE_FILES_RESOURCE_GROUP --assignee $ARO_SERVICE_PRINCIPAL_ID
 ```
 
 ### Set ARO cluster permissions

articles/openshift/quickstart-openshift-arm-bicep-template.md

@@ -453,6 +453,27 @@ param aadClientSecret string
 @description('The ObjectID of the Resource Provider Service Principal')
 param rpObjectId string
 
+@description('Specify if FIPS validated crypto modules are used')
+@allowed([
+  'Enabled'
+  'Disabled'
+])
+param fips string = 'Disabled'
+
+@description('Specify if master VMs are encrypted at host')
+@allowed([
+  'Enabled'
+  'Disabled'
+])
+param masterEncryptionAtHost string = 'Disabled'
+
+@description('Specify if worker VMs are encrypted at host')
+@allowed([
+  'Enabled'
+  'Disabled'
+])
+param workerEncryptionAtHost string = 'Disabled'
+
 var contributorRoleDefinitionId = resourceId('Microsoft.Authorization/roleDefinitions', 'b24988ac-6180-42a0-ab88-20f7382dd24c')
 var resourceGroupId = '/subscriptions/${subscription().subscriptionId}/resourceGroups/aro-${domain}-${location}'
 var masterSubnetId=resourceId('Microsoft.Network/virtualNetworks/subnets', clusterVnetName, 'master')
@@ -525,6 +546,7 @@ resource clusterName_resource 'Microsoft.RedHatOpenShift/OpenShiftClusters@2023-
       domain: domain
       resourceGroupId: resourceGroupId
       pullSecret: pullSecret
+      fipsValidatedModules: fips
     }
     networkProfile: {
       podCidr: podCidr
@@ -537,6 +559,7 @@ resource clusterName_resource 'Microsoft.RedHatOpenShift/OpenShiftClusters@2023-
     masterProfile: {
       vmSize: masterVmSize
       subnetId: masterSubnetId
+      encryptionAtHost: masterEncryptionAtHost
     }
     workerProfiles: [
       {
@@ -545,6 +568,7 @@ resource clusterName_resource 'Microsoft.RedHatOpenShift/OpenShiftClusters@2023-
         diskSizeGB: workerVmDiskSize
         subnetId: workerSubnetId
         count: workerCount
+        encryptionAtHost: workerEncryptionAtHost
       }
     ]
     apiserverProfile: {