Merge pull request #279024 from MicrosoftDocs/main

Publish to live, Monday 4 AM PST, 6/24

Author: ttorble

.openpublishing.redirection.virtual-desktop.json

@@ -429,6 +429,11 @@
             "source_path_from_root": "/articles/virtual-desktop/host-pool-load-balancing.md",
             "redirect_url": "/azure/virtual-desktop/configure-host-pool-load-balancing",
             "redirect_document_id": false
+        },
+        {
+            "source_path_from_root": "/articles/virtual-desktop/configure-rdp-shortpath-limit-ports-public-networks.md",
+            "redirect_url": "/azure/virtual-desktop/configure-rdp-shortpath",
+            "redirect_document_id": true
         }
     ]
 }

articles/active-directory-b2c/configure-authentication-sample-python-web-app.md

@@ -1,19 +1,19 @@
 ---
-title: Configure authentication in a sample Python web application by using Azure Active Directory B2C
+title: Configure authentication in a sample Python web app by using Azure AD B2C
 description:  This article discusses how to use Azure Active Directory B2C to sign in and sign up users in a Python web application.
 
 author: kengaderdus
-manager: CelesteDG
+manager: mwongerapk
 ms.service: active-directory
 
 ms.topic: reference
-ms.date: 01/11/2024
+ms.date: 06/04/2024
 ms.author: kengaderdus
 ms.subservice: B2C
 ms.custom: b2c-support, devx-track-python
 
 
-#Customer intent: As a Python web app developer, I want to configure Azure AD B2C authentication in my web application, so that I can securely sign users in and add authentication and authorization support to my app.
+#Customer intent: As a Python web app developer, I want to configure Azure AD B2C authentication in a sample web app by using my own tenant, so that I can securely sign customer users.
 
 ---
 
@@ -37,7 +37,7 @@ The sign-in flow involves the following steps:
 
 - An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/free/?WT.mc_id=A261C142F).
 - If you don't have one already, [create an Azure AD B2C tenant](tutorial-create-tenant.md) that is linked to your Azure subscription.
-- [Python 3.7+](https://www.python.org/downloads/)
+- [Python 3.8+](https://www.python.org/downloads/)
 
 ## Step 1: Configure your user flow
 
@@ -222,4 +222,4 @@ You can add and modify redirect URIs in your registered applications at any time
 * The redirect URL is case-sensitive. Its case must match the case of the URL path of your running application. 
 
 ## Next steps
-* Learn how to [Configure authentication options in a Python web app by using Azure AD B2C](enable-authentication-python-web-app-options.md).
+* Learn how to [Configure authentication options in a Python web app by using Azure AD B2C](enable-authentication-python-web-app-options.md).

articles/ai-services/speech-service/includes/phonetic-sets/text-to-speech/en-us.md

@@ -69,9 +69,9 @@ ms.author: eur
 
 | `sapi` | `ipa` | VisemeID | Example 1        | Example 2  | Example 3   |
 |--------|-------|----------|------------------|------------|-------------|
-| m      | `m`   | 21       | **m**at, smash   | ca**m**era | roo**m**    |
+| m      | `m`   | 21       | **m**at, s**m**ash   | ca**m**era | roo**m**    |
 | n      | `n`   | 19       | **n**o, s**n**ow | te**n**t   | chicke**n** |
-| ng     | `ŋ`   | 20       |                  | li**n**k   | s**ing**    |
+| ng     | `ŋ`   | 20       |                  | li**n**k   | si**ng**    |
 
 #### Fricatives for English
 

articles/ai-services/speech-service/includes/quickstarts/openai-speech/csharp.md

@@ -230,7 +230,8 @@ Here are some more considerations:
 
 - To change the speech recognition language, replace `en-US` with another [supported language](~/articles/ai-services/speech-service/language-support.md). For example, `es-ES` for Spanish (Spain). The default language is `en-US`. For details about how to identify one of multiple languages that might be spoken, see [language identification](~/articles/ai-services/speech-service/language-identification.md).
 - To change the voice that you hear, replace `en-US-JennyMultilingualNeural` with another [supported voice](~/articles/ai-services/speech-service/language-support.md#prebuilt-neural-voices). If the voice doesn't speak the language of the text returned from Azure OpenAI, the Speech service doesn't output synthesized audio.
-- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#text-streaming). 
+- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#text-streaming).
+- To enable [TTS Avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/what-is-text-to-speech-avatar.md) as a visual experience of speech output, refer to [real-time synthesis for text to speech avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/real-time-synthesis-avatar.md) and [sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/js/browser/avatar#chat-sample) for chat scenario with avatar.
 - To use a different [model](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability), replace `gpt-35-turbo-instruct` with the ID of another [deployment](/azure/ai-services/openai/how-to/create-resource?pivots=web-portal#deploy-a-model). The deployment ID isn't necessarily the same as the model name. You named your deployment when you created it in [Azure OpenAI Studio](https://oai.azure.com/).
 - Azure OpenAI also performs content moderation on the prompt inputs and generated outputs. The prompts or responses might be filtered if harmful content is detected. For more information, see the [content filtering](/azure/ai-services/openai/concepts/content-filter) article.
 

articles/ai-services/speech-service/includes/quickstarts/openai-speech/python.md

@@ -177,7 +177,8 @@ Here are some more considerations:
 
 - To change the speech recognition language, replace `en-US` with another [supported language](~/articles/ai-services/speech-service/language-support.md). For example, `es-ES` for Spanish (Spain). The default language is `en-US`. For details about how to identify one of multiple languages that might be spoken, see [language identification](~/articles/ai-services/speech-service/language-identification.md).
 - To change the voice that you hear, replace `en-US-JennyMultilingualNeural` with another [supported voice](~/articles/ai-services/speech-service/language-support.md#prebuilt-neural-voices). If the voice doesn't speak the language of the text returned from Azure OpenAI, the Speech service doesn't output synthesized audio.
-- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#text-streaming). 
+- To reduce latency for text to speech output, use the text streaming feature, which enables real-time text processing for fast audio generation and minimizes latency, enhancing the fluidity and responsiveness of real-time audio outputs. Refer to [how to use text streaming](~/articles/ai-services/speech-service/how-to-lower-speech-synthesis-latency.md#text-streaming).
+- To enable [TTS Avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/what-is-text-to-speech-avatar.md) as a visual experience of speech output, refer to [real-time synthesis for text to speech avatar](~/articles/ai-services/speech-service/text-to-speech-avatar/real-time-synthesis-avatar.md) and [sample code](https://github.com/Azure-Samples/cognitive-services-speech-sdk/tree/master/samples/js/browser/avatar#chat-sample) for chat scenario with avatar.
 - To use a different [model](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability), replace `gpt-35-turbo-instruct` with the ID of another [deployment](/azure/ai-services/openai/how-to/create-resource#deploy-a-model). Keep in mind that the deployment ID isn't necessarily the same as the model name. You named your deployment when you created it in [Azure OpenAI Studio](https://oai.azure.com/).
 - Azure OpenAI also performs content moderation on the prompt inputs and generated outputs. The prompts or responses might be filtered if harmful content is detected. For more information, see the [content filtering](/azure/ai-services/openai/concepts/content-filter) article.
 

articles/app-service/environment/overview.md

@@ -10,8 +10,6 @@ ms.custom: "UpdateFrequency3, references_regions"
 
 # App Service Environment overview
 
-[!INCLUDE [regionalization-note](../includes/regionalization-note.md)]
-
 An App Service Environment is an Azure App Service feature that provides a fully isolated and dedicated environment for running App Service apps securely at high scale. Unlike the App Service public multitenant offering where supporting ingfrastructure is shared, with App Service Environment, compute is dedicated to a single customer. For more information on the differences between App Service Environment and App Service public multitenant, see the [comparison of the offerings](ase-multi-tenant-comparison.md).
 
 > [!NOTE]

articles/application-gateway/application-gateway-faq.yml

@@ -280,8 +280,37 @@ sections:
         answer: Application Gateway v2 supports IPv4 and IPv6 frontends. Currently, IPv6 support is available for new application gateways only. To support IPv6, the virtual network should be dual stack. Application Gateway v1 doesn't support dual-stack virtual networks. 
 
       - question: Does Application Gateway support FIPS?
-        answer: Application Gateway v1 SKUs can run in a FIPS 140-2 approved mode of operation, which is commonly referred to as "FIPS mode." FIPS mode calls a FIPS 140-2 validated cryptographic module that ensures FIPS-compliant algorithms for encryption, hashing, and signing when enabled. To ensure FIPS mode is enabled, the `FIPSMode` setting must be configured via PowerShell, Azure Resource Manager template, or REST API after the subscription has been enrolled to enable configuration of `FIPSmode`.
+        answer: |
+          Application Gateway v1 SKUs can run in a FIPS 140-2 approved mode of operation, which is commonly referred to as "FIPS mode." FIPS mode calls a FIPS 140-2 validated cryptographic module that ensures FIPS-compliant algorithms for encryption, hashing, and signing when enabled. To ensure FIPS mode is enabled, the `FIPSMode` setting must be configured via PowerShell, Azure Resource Manager template, or REST API after the subscription has been enrolled to enable configuration of `FIPSmode`.
+
+          **Note:** As part of the FedRAMP compliance, US Government mandates that systems operate in a [FIPS-approved mode](/azure/compliance/offerings/offering-fips-140-2) after August 2024. 
+          **Steps to enable FIPS Mode in V1 SKU**
+          
+          * Register the **‘AllowApplicationGatewayEnableFIPS’** feature to enroll the subscription for FIPS mode configuration.
+          
+          ```azurepowershell-interactive
+          Register-AzProviderFeature -FeatureName AllowApplicationGatewayEnableFIPS -ProviderNamespace Microsoft.Network
+          ```
+          Use the following steps to enroll for FIPS Mode in Application Gateway V1 using the **Azure portal**
+          1.	Sign in to the Azure portal.
+          1.	In the search box, enter subscriptions and select **Subscriptions**.
+          1.	Select the link for your subscription's name.
+          1.	From the left menu, under **Settings** select **Preview features**.
+          1.	You see a list of available features and your current registration status.
+          1.	From Preview features type into the filter box **AllowApplicationGatewayEnableFIPS**, select the feature, and then select Register.
+
+          * Once **step 1** is complete, the **enableFips** property needs to be set to True through PowerShell, Azure Resource Manager template, or REST API.
 
+          ```azurepowershell-interactive
+          # Get the application gateway
+          $appgw = Get-AzApplicationGateway -Name <ApplicationGatewayName> -ResourceGroupName <ResourceGroupName>
+          # Set the EnableFips property
+          $appgw.EnableFips = $true
+          # Update the application gateway
+          Set-AzApplicationGateway -ApplicationGateway $appgw
+          ```
+          Changing FIPS mode doesn't affect the overall availability of cipher suites on V1 gateways. However, when using [elliptic curve cryptography](/windows/win32/secauthn/tls-elliptic-curves-in-windows-10-1607-and-later) for ciphers, with FIPS mode disabled  you can use curve25519, NistP256, and NistP384 whereas with FIPS mode enabled only NistP256 and NistP384 are allowed and curve25519 is disabled. Since curve25519 becomes unavailable in FIPS mode, make sure your clients support NistP256 or NistP384 for secure communication before enabling FIPS. 
+          
       - question: How do I use Application Gateway v2 with only a private frontend IP address?
         answer: |
           Application Gateway v2 currently supports private IP frontend configuration only (no public IP) via public preview. For more information, see [Private Application Gateway deployment (preview)](application-gateway-private-deployment.md).

articles/azure-netapp-files/configure-kerberos-encryption.md

@@ -5,7 +5,7 @@ services: azure-netapp-files
 author: b-hchen
 ms.service: azure-netapp-files
 ms.topic: how-to
-ms.date: 01/10/2022
+ms.date: 06/24/2024
 ms.author: anfdocs
 ---
 # Configure NFSv4.1 Kerberos encryption for Azure NetApp Files
@@ -93,7 +93,7 @@ Follow instructions in [Configure an NFS client for Azure NetApp Files](configur
 
 5. Mount the volume on the host: 
 
-    `sudo mount -t nfs -o sec=krb5p,rw,hard,rsize=1048576,wsize=1048576,vers=4.1,tcp $ANFEXPORT $ANFMOUNTPOINT`
+    `sudo mount -t nfs -o sec=krb5p,rw,hard,rsize=262144,wsize=262144,vers=4.1,tcp $ANFEXPORT $ANFMOUNTPOINT`
 
     * The `$ANFEXPORT` variable is the `host:/export` path found in the mount instructions.
     * The `$ANFMOUNTPOINT` variable is the user-created folder on the Linux host.

articles/batch/batch-task-dependencies.md

@@ -2,7 +2,7 @@
 title: Create task dependencies to run tasks
 description: Create tasks that depend on the completion of other tasks for processing MapReduce style and similar big data workloads in Azure Batch.
 ms.topic: how-to
-ms.date: 06/29/2021
+ms.date: 06/13/2024
 ms.devlang: csharp
 ms.custom: "H1Hack27Feb2017, devx-track-csharp"
 ---
@@ -59,9 +59,9 @@ There are three basic task dependency scenarios that you can use in Azure Batch:
 
 | Scenario        | Example | Illustration |
 |:---:| --- | --- |
-|  [One-to-one](#one-to-one) |*taskB* depends on *taskA* <p/> *taskB* will not be scheduled for execution until *taskA* has completed successfully |:::image type="content" source="media/batch-task-dependency/01_one_to_one.png" alt-text="Diagram showing the one-to-one task dependency scenario."::: |
-|  [One-to-many](#one-to-many) |*taskC* depends on both *taskA* and *taskB* <p/> *taskC* will not be scheduled for execution until both *taskA* and *taskB* have completed successfully |:::image type="content" source="media/batch-task-dependency/02_one_to_many.png" alt-text="Diagram showing the one-to-many task dependency scenario."::: |
-|  [Task ID range](#task-id-range) |*taskD* depends on a range of tasks <p/> *taskD* will not be scheduled for execution until the tasks with IDs *1* through *10* have completed successfully |:::image type="content" source="media/batch-task-dependency/03_task_id_range.png" alt-text="Diagram showing the task ID range task dependency scenario."::: |
+|  [One-to-one](#one-to-one) |*taskB* depends on *taskA* <p/> *taskB* won't be scheduled for execution until *taskA* has completed successfully |:::image type="content" source="media/batch-task-dependency/01_one_to_one.png" alt-text="Diagram showing the one-to-one task dependency scenario."::: |
+|  [One-to-many](#one-to-many) |*taskC* depends on both *taskA* and *taskB* <p/> *taskC* won't be scheduled for execution until both *taskA* and *taskB* have completed successfully |:::image type="content" source="media/batch-task-dependency/02_one_to_many.png" alt-text="Diagram showing the one-to-many task dependency scenario."::: |
+|  [Task ID range](#task-id-range) |*taskD* depends on a range of tasks <p/> *taskD* won't be scheduled for execution until the tasks with IDs *1* through *10* have completed successfully |:::image type="content" source="media/batch-task-dependency/03_task_id_range.png" alt-text="Diagram showing the task ID range task dependency scenario."::: |
 
 > [!TIP]
 > You can create **many-to-many** relationships, such as where tasks C, D, E, and F each depend on tasks A and B. This is useful, for example, in parallelized preprocessing scenarios where your downstream tasks depend on the output of multiple upstream tasks.