Merge pull request #3940 from sdgilley/sdg-rename-files

[BULK UPDATE] rename files

Author: Stacyrch140

articles/ai-foundry/.openpublishing.redirection.ai-studio.json

@@ -1,5 +1,25 @@
 {
     "redirections": [
+        {
+          "source_path_from_root": "/articles/ai-foundry/azure-openai-in-ai-foundry.md",
+          "redirect_url": "/azure/ai-foundry/azure-openai-in-azure-ai-foundry",
+          "redirect_document_id": false
+        },
+        {
+          "source_path_from_root": "/articles/ai-foundry/what-is-ai-foundry.md",
+          "redirect_url": "/azure/ai-foundry/what-is-azure-ai-foundry",
+          "redirect_document_id": false
+        },
+        {
+          "source_path_from_root": "/articles/ai-foundry/whats-new-ai-foundry.md",
+          "redirect_url": "/azure/ai-foundry/whats-new-azure-ai-foundry",
+          "redirect_document_id": false
+        },
+        {
+          "source_path_from_root": "/articles/ai-foundry/concepts/rbac-ai-foundry.md",
+          "redirect_url": "/azure/ai-foundry/concepts/rbac-azure-ai-foundry",
+          "redirect_document_id": false
+        },
         {
             "source_path_from_root": "/articles/ai-studio/how-to/access-on-premises-resources.md",
             "redirect_url": "/azure/ai-foundry/how-to/access-on-premises-resources",
@@ -644,7 +664,7 @@
         },
         {
             "source_path_from_root": "/articles/ai-studio/concepts/rbac-ai-studio.md",
-            "redirect_url": "/azure/ai-foundry/concepts/rbac-ai-foundry",
+            "redirect_url": "/azure/ai-foundry/concepts/rbac-azure-ai-foundry",
             "redirect_document_id": true
         },
         {
@@ -669,7 +689,7 @@
         },
         {
             "source_path_from_root": "/articles/ai-studio/azure-openai-in-ai-studio.md",
-            "redirect_url": "/azure/ai-foundry/azure-openai-in-ai-foundry",
+            "redirect_url": "/azure/ai-foundry/azure-openai-in-azure-ai-foundry",
             "redirect_document_id": true
         },
         {
@@ -739,12 +759,12 @@
         },
         {
             "source_path_from_root": "/articles/ai-studio/what-is-ai-studio.md",
-            "redirect_url": "/azure/ai-foundry/what-is-ai-foundry",
+            "redirect_url": "/azure/ai-foundry/what-is-azure-ai-foundry",
             "redirect_document_id": true
         },
         {
             "source_path_from_root": "/articles/ai-studio/whats-new-ai-studio.md",
-            "redirect_url": "/azure/ai-foundry/whats-new-ai-foundry",
+            "redirect_url": "/azure/ai-foundry/whats-new-azure-ai-foundry",
             "redirect_document_id": true
         },
         {

articles/ai-foundry/ai-services/how-to/connect-azure-openai.md

@@ -145,5 +145,5 @@ At some point, you want to develop apps with code. Here are some developer resou
 
 ## Related content
 
-- [Azure OpenAI in Azure AI Foundry portal](../../azure-openai-in-ai-foundry.md)
+- [Azure OpenAI in Azure AI Foundry portal](../../azure-openai-in-azure-ai-foundry.md)
 - [Use Azure AI services resources](./connect-ai-services.md)

articles/ai-foundry/azure-openai-in-ai-foundry.md renamed to articles/ai-foundry/azure-openai-in-azure-ai-foundry.md

@@ -129,5 +129,5 @@ In the Azure portal, you can find resources that correspond to your project in A
 ## Next steps
 
 - [Quickstart: Analyze images and video in the chat playground](/azure/ai-services/openai/gpt-v-quickstart)
-- [Learn more about Azure AI Foundry](../what-is-ai-foundry.md)
+- [Learn more about Azure AI Foundry](../what-is-azure-ai-foundry.md)
 - [Learn more about projects](../how-to/create-projects.md)

articles/ai-foundry/concepts/ai-resources.md

@@ -28,7 +28,7 @@ At the top level, Azure AI Foundry provides access to the following resources:
 
     When you use Azure AI Foundry portal, you can directly work with Azure OpenAI without an Azure Studio project. Or you can use Azure OpenAI through a project.
 
-    For more information, visit [Azure OpenAI in Azure AI Foundry portal](../azure-openai-in-ai-foundry.md).
+    For more information, visit [Azure OpenAI in Azure AI Foundry portal](../azure-openai-in-azure-ai-foundry.md).
 
 - **Management center**: The management center streamlines governance and management of Azure AI Foundry resources such as hubs, projects, connected resources, and deployments.
 
@@ -108,7 +108,7 @@ Azure AI services including Azure OpenAI provide control plane endpoints for ope
 
 To reduce the complexity of Azure RBAC management, Azure AI Foundry provides a *control plane proxy* that allows you to perform operations on connected Azure AI services and Azure OpenAI resources. Performing operations on these resources through the control plane proxy only requires Azure RBAC permissions on the hub. The Azure AI Foundry service then performs the call to the Azure AI services or Azure OpenAI control plane endpoint on your behalf.
 
-For more information, see [Role-based access control in Azure AI Foundry portal](rbac-ai-foundry.md).
+For more information, see [Role-based access control in Azure AI Foundry portal](rbac-azure-ai-foundry.md).
 
 ## Attribute-based access control
 

articles/ai-foundry/concepts/architecture.md

@@ -41,6 +41,6 @@ We used an advanced prompt during synthetic data generation. The advanced prompt
 
 ## Related content
 
-- [What is Azure AI Foundry?](../what-is-ai-foundry.md)
+- [What is Azure AI Foundry?](../what-is-azure-ai-foundry.md)
 - [Deploy Meta Llama 3.1 models with Azure AI Foundry](../how-to/deploy-models-llama.md)
 - [Azure AI Foundry FAQ](../faq.yml)

articles/ai-foundry/concepts/concept-model-distillation.md

@@ -35,6 +35,6 @@ To see how to generate synthetic data, you can use the [sample notebook](https:/
 
 ## Related content
 
-- [What is Azure AI Foundry?](../what-is-ai-foundry.md)
+- [What is Azure AI Foundry?](../what-is-azure-ai-foundry.md)
 - [Deploy Meta Llama 3.1 models with Azure AI Foundry](../how-to/deploy-models-llama.md)
 - [Azure AI Foundry FAQ](../faq.yml)

articles/ai-foundry/concepts/concept-synthetic-data.md

@@ -54,7 +54,7 @@ When you create a connection with an existing Azure storage account, you can cho
 - **Identity-based**: Use your Microsoft Entra ID or managed identity to authenticate data access.
 
     > [!TIP]
-    > When you use an identity-based connection, Azure role-based access control (Azure RBAC) determines who can access the connection. You must assign the correct Azure RBAC roles to your developers before they can use the connection. For more information, see [Scenario: Connections using Microsoft Entra ID](rbac-ai-foundry.md#scenario-connections-using-microsoft-entra-id-authentication).
+    > When you use an identity-based connection, Azure role-based access control (Azure RBAC) determines who can access the connection. You must assign the correct Azure RBAC roles to your developers before they can use the connection. For more information, see [Scenario: Connections using Microsoft Entra ID](rbac-azure-ai-foundry.md#scenario-connections-using-microsoft-entra-id-authentication).
 
 
 The following table shows the supported Azure cloud-based storage services and authentication methods:
@@ -84,7 +84,7 @@ A Uniform Resource Identifier (URI) represents a storage location on your local
 
 Connections allow you to securely store credentials, authenticate access, and consume data and information.  Secrets associated with connections are securely persisted in the corresponding Azure Key Vault, adhering to robust security and compliance standards. As an administrator, you can audit both shared and project-scoped connections on a hub level. 
 
-Azure connections serve as key vault proxies, and interactions with connections are direct interactions with an Azure key vault. Azure AI Foundry connections store API keys securely, as secrets, in a key vault. The key vault [Azure role-based access control (Azure RBAC)](./rbac-ai-foundry.md) controls access to these connection resources. A connection references the credentials from the key vault storage location for further use. You won't need to directly deal with the credentials after they're stored in the hub's key vault. You have the option to store the credentials in the YAML file. A CLI command or SDK can override them. We recommend that you avoid credential storage in a YAML file, because a security breach could lead to a credential leak.  
+Azure connections serve as key vault proxies, and interactions with connections are direct interactions with an Azure key vault. Azure AI Foundry connections store API keys securely, as secrets, in a key vault. The key vault [Azure role-based access control (Azure RBAC)](./rbac-azure-ai-foundry.md) controls access to these connection resources. A connection references the credentials from the key vault storage location for further use. You won't need to directly deal with the credentials after they're stored in the hub's key vault. You have the option to store the credentials in the YAML file. A CLI command or SDK can override them. We recommend that you avoid credential storage in a YAML file, because a security breach could lead to a credential leak.  
 
 
 ## Next steps

articles/ai-foundry/concepts/connections.md

@@ -40,7 +40,7 @@ Assign roles, manage users, and ensure that all settings comply with organizatio
 
 :::image type="content" source="../media/management-center/user-management.png" alt-text="Screenshot of the user management section of the management center." lightbox="../media/management-center/user-management.png":::
 
-For more information, see [Role-based access control](rbac-ai-foundry.md#assigning-roles-in-azure-ai-foundry-portal).
+For more information, see [Role-based access control](rbac-azure-ai-foundry.md#assigning-roles-in-azure-ai-foundry-portal).
 
 ## Related content