Merge pull request #266663 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: rmca14

articles/active-directory-b2c/custom-policies-series-validate-user-input.md

@@ -49,7 +49,7 @@ Azure Active Directory B2C (Azure AD B2C) custom policy not only allows you to m
 
 ## Step 1 - Validate user input by limiting user input options 
 
-If you know all the possible values that a user can enter for a given input, you can provide a finite set of values that a user must select from. You can use *DropdownSinglSelect*, *CheckboxMultiSelect*, and *RadioSingleSelect* [UserInputType](claimsschema.md#userinputtype) for this purpose. In this article, you'll use a *RadioSingleSelect* input type:
+If you know all the possible values that a user can enter for a given input, you can provide a finite set of values that a user must select from. You can use *DropdownSingleSelect*, *CheckboxMultiSelect*, and *RadioSingleSelect* [UserInputType](claimsschema.md#userinputtype) for this purpose. In this article, you'll use a *RadioSingleSelect* input type:
 
 1. In VS Code, open the file `ContosoCustomPolicy.XML`. 
 

articles/active-directory-b2c/session-behavior.md

@@ -25,6 +25,9 @@ With single sign-on, users sign in once with a single account and get access to
 
 When the user initially signs in to an application, Azure AD B2C persists a cookie-based session. Upon subsequent authentication requests, Azure AD B2C reads and validates the cookie-based session, and issues an access token without prompting the user to sign in again. If the cookie-based session expires or becomes invalid, the user is prompted to sign-in again.  
 
+>[!NOTE]
+>If the user uses a browser that blocks third-party cookies, there are limitations with SSO due to limited access to the cookie-based session.  The most user-visible impact is that there are more interactions required for sign-in. Additionally, the front channel sign-out doesn't immediately clear authentication state from federated applications. Check our recommended ways about [how to handle third-party cookie blocking in browsers](/entra/identity-platform/reference-third-party-cookies-spas). 
+
 ## Prerequisites
 
 [!INCLUDE [active-directory-b2c-customization-prerequisites](../../includes/active-directory-b2c-customization-prerequisites.md)]

articles/ai-studio/how-to/quota.md

@@ -94,7 +94,7 @@ Use quotas to manage compute target allocation between multiple Azure AI hub r
 
 By default, all Azure AI hub resources share the same quota as the subscription-level quota for VM families. However, you can set a maximum quota for individual VM families for more granular cost control and governance on Azure AI hub resources in a subscription. Quotas for individual VM families let you share capacity and avoid resource contention issues. 
 
-In Azure AI Studio, select **Manage** from the top menu. Select **Quota** to view your quota at the subscription level in a region for both Azure Machine Learning virtual machine families and for your Azure Open AI resources. 
+In Azure AI Studio, select **Manage** from the top menu. Select **Quota** to view your quota at the subscription level in a region for both Azure Machine Learning virtual machine families and for your Azure OpenAI resources. 
 
 :::image type="content" source="../media/cost-management/quota-manage.png" alt-text="Screenshot of the page to view and request quota for virtual machines and Azure OpenAI models." lightbox="../media/cost-management/quota-manage.png":::
 

articles/azure-monitor/agents/azure-monitor-agent-send-data-to-event-hubs-and-storage.md

@@ -602,7 +602,6 @@ Use custom template deployment to create the DCR association and AMA deployment.
             "settings": {
             "authentication": {
                 "managedIdentity": {
-                "identifier-type": "mi_res_id",
                 "identifier-name": "mi_res_id",
                 "identifier-value": "[resourceID('Microsoft.ManagedIdentity/userAssignedIdentities/',parameters('identityName'))]"
                 }
@@ -680,7 +679,6 @@ Use custom template deployment to create the DCR association and AMA deployment.
             "settings": {
             "authentication": {
                 "managedIdentity": {
-                "identifier-type": "mi_res_id",
                 "identifier-name": "mi_res_id",
                 "identifier-value": "[resourceID('Microsoft.ManagedIdentity/userAssignedIdentities/',parameters('identityName'))]"
                 }

articles/devtest-labs/image-factory-create.md

@@ -21,7 +21,7 @@ The solution enables the speed of creating virtual machines from custom images w
 <br/>
 
 ## High-level view of the solution
-The solution enables the speed of creating virtual machines from custom images while eliminating extra ongoing maintenance costs. With this solution, you can automatically create custom images and distribute them to other DevTest Labs. You use Azure DevOps (formerly Visual Studio Team Services) as the orchestration engine for automating the all the operations in the DevTest Labs.
+The solution enables the speed of creating virtual machines from custom images while eliminating extra ongoing maintenance costs. With this solution, you can automatically create custom images and distribute them to other DevTest Labs. You use Azure DevOps (formerly Visual Studio Team Services) as the orchestration engine for automating all the operations in the DevTest Labs.
 
 ![High-level view of the solution.](./media/create-image-factory/high-level-view-of-solution.png)
 

articles/machine-learning/prompt-flow/concept-connections.md

@@ -24,12 +24,12 @@ Connections in prompt flow play a crucial role in establishing connections to re
 
 In the Azure Machine Learning workspace, connections can be configured to be shared across the entire workspace or limited to the creator. Secrets associated with connections are securely persisted in the corresponding Azure Key Vault, adhering to robust security and compliance standards.
 
-Prompt flow provides various prebuilt connections, including Azure Open AI, Open AI, and Azure Content Safety. These prebuilt connections enable seamless integration with these resources within the built-in tools. Additionally, users have the flexibility to create custom connection types using key-value pairs, empowering them to tailor the connections to their specific requirements, particularly in Python tools.
+Prompt flow provides various prebuilt connections, including Azure OpenAI, OpenAI, and Azure Content Safety. These prebuilt connections enable seamless integration with these resources within the built-in tools. Additionally, users have the flexibility to create custom connection types using key-value pairs, empowering them to tailor the connections to their specific requirements, particularly in Python tools.
 
 | Connection type                                              | Built-in tools                  |
 | ------------------------------------------------------------ | ------------------------------- |
-| [Azure Open AI](https://azure.microsoft.com/products/cognitive-services/openai-service) | LLM or Python                   |
-| [Open AI](https://openai.com/)                               | LLM or Python                   |
+| [Azure OpenAI](https://azure.microsoft.com/products/cognitive-services/openai-service) | LLM or Python                   |
+| [OpenAI](https://openai.com/)                               | LLM or Python                   |
 | [Azure Content Safety](https://aka.ms/acs-doc)               | Content Safety (Text) or Python |
 | [Azure AI Search](https://azure.microsoft.com/products/search) (formerly Cognitive Search) | Vector DB Lookup or Python      |
 | [Serp](https://serpapi.com/)                                 | Serp API or Python              |

articles/machine-learning/v1/azure-machine-learning-release-notes.md

@@ -2400,7 +2400,7 @@ Azure Machine Learning is now a resource provider for Event Grid, you can config
   + **Preview features**
     + We are releasing preview support for disk encryption of your local SSD in Azure Machine Learning Compute. Raise a technical support ticket to get your subscription allow listed to use this feature.
     + Public Preview of Azure Machine Learning Batch Inference. Azure Machine Learning Batch Inference targets large inference jobs that are not time-sensitive. Batch Inference provides cost-effective inference compute scaling, with unparalleled throughput for asynchronous applications. It is optimized for high-throughput, fire-and-forget inference over large collections of data.
-    + [**azureml-contrib-dataset**](/python/api/azureml-contrib-dataset)
+    + **azureml-contrib-dataset**
         + Enabled functionalities for labeled dataset
         ```Python
         import azureml.core

articles/orbital/register-spacecraft.md

@@ -81,7 +81,7 @@ Submit a spacecraft authorization request in order to schedule [contacts](concep
    > A [Basic Support Plan](https://azure.microsoft.com/support/plans/) or higher is required to submit a spacecraft authorization request.
 
    > [!NOTE]
-   > **Private spacecraft**: prior to submitting an authorization request, you must have an active spacecraft license for your satellite and work with Mircosot to add your satellite to our ground station licenses. Microsoft can provide technical information required to complete the federal regulator and ITU processes as needed. Learn more about [initiating ground station licensing](initiate-licensing.md).
+   > **Private spacecraft**: prior to submitting an authorization request, you must have an active spacecraft license for your satellite and work with Microsoft to add your satellite to our ground station licenses. Microsoft can provide technical information required to complete the federal regulator and ITU processes as needed. Learn more about [initiating ground station licensing](initiate-licensing.md).
    > 
    > **Public spacecraft**: licensing is not required for authorization. The Azure Orbital Ground Station service supports several public satellites including Aqua, Suomi NPP, JPSS-1/NOAA-20, and Terra.
 

articles/postgresql/migrate/how-to-migrate-single-to-flexible-cli.md

@@ -122,7 +122,7 @@ The structure of the JSON is:
     {
       "sourceServerPassword": "<password>",
       "targetServerPassword": "<password>"
-    }
+    },
    "sourceServerUserName": "<username>@<servername>",
    "targetServerUserName": "<username>"
 },