add architecture and fix links

Author: sdgilley

articles/ai-studio/azure-openai-in-ai-studio.md

@@ -18,7 +18,7 @@ ms.custom: ignite-2023, build-2024
 
 Azure OpenAI Service provides REST API access to OpenAI's powerful language models. Azure OpenAI Studio was previously where you went to access and work with the Azure OpenAI Service. This studio is now integrated into Azure AI Foundry portal. 
 
-[!INCLUDE [new-name](../includes/new-name.md)]
+[!INCLUDE [new-name](includes/new-name.md)]
 
 ## Access Azure OpenAI Service in Azure AI Foundry portal
 

articles/ai-studio/concepts/architecture.md

@@ -13,34 +13,36 @@ ms.author: larryfr
 author: Blackmist
 ---
 
-# Azure AI Studio architecture 
+# Azure AI Foundry architecture 
 
-AI Studio provides a unified experience for AI developers and data scientists to build, evaluate, and deploy AI models through a web portal, SDK, or CLI. AI Studio is built on capabilities and services provided by other Azure services.
+AI Foundry provides a unified experience for AI developers and data scientists to build, evaluate, and deploy AI models through a web portal, SDK, or CLI. AI Foundry is built on capabilities and services provided by other Azure services.
+
+[!INCLUDE [new-name](../includes/new-name.md)]
 
 :::image type="content" source="../media/concepts/ai-studio-architecture.png" alt-text="Diagram of the high-level architecture of Azure AI Studio." lightbox="../media/concepts/ai-studio-architecture.png":::
 
-At the top level, AI Studio provides access to the following resources:
+At the top level, AI Foundry provides access to the following resources:
 
 <!-- The top level AI Studio resources (hub and project) are based on Azure Machine Learning. Connected resources, such as Azure OpenAI, Azure AI services, and Azure AI Search, are used by the hub and project in reference, but follow their own resource management lifecycle. -->
 
 - **Azure OpenAI**: Provides access to the latest Open AI models. You can create secure deployments, try playgrounds, fine tune models, content filters, and batch jobs. The Azure OpenAI resource provider is `Microsoft.CognitiveServices/account` and the kind of resource is `OpenAI`. You can also connect to Azure OpenAI by using a kind of `AIServices`, which also includes other [Azure AI services](/azure/ai-services/what-are-ai-services).
 
-    When using Azure AI Studio, you can directly work with Azure OpenAI without an Azure Studio project or you can use Azure OpenAI through a project.
+    When using 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 Studio](../azure-openai-in-ai-studio.md).
 
 - **Management center**: The management center streamlines governance and management of AI Studio resources such as hubs, projects, connected resources, and deployments.
 
     For more information, visit [Management center](management-center.md).
-- **AI Studio hub**: The hub is the top-level resource in AI Studio, and is based on the Azure Machine Learning service. The Azure resource provider for a hub is `Microsoft.MachineLearningServices/workspaces`, and the kind of resource is `Hub`. It provides the following features:
+- **AI Foundry hub**: The hub is the top-level resource in AI Foundry portal, and is based on the Azure Machine Learning service. The Azure resource provider for a hub is `Microsoft.MachineLearningServices/workspaces`, and the kind of resource is `Hub`. It provides the following features:
     - Security configuration including a managed network that spans projects and model endpoints.
     - Compute resources for interactive development, fine-tuning, open source, and serverless model deployments.
     - Connections to other Azure services such as Azure OpenAI, Azure AI services, and Azure AI Search. Hub-scoped connections are shared with projects created from the hub.
     - Project management. A hub can have multiple child projects.
     - An associated Azure storage account for data upload and artifact storage.
 
     For more information, visit [Hubs and projects overview](ai-resources.md).
-- **AI Studio project**: A project is a child resource of the hub. The Azure resource provider for a project is `Microsoft.MachineLearningServices/workspaces`, and the kind of resource is `Project`. The project provides the following features:
+- **AI Foundry project**: A project is a child resource of the hub. The Azure resource provider for a project is `Microsoft.MachineLearningServices/workspaces`, and the kind of resource is `Project`. The project provides the following features:
     - Access to development tools for building and customizing AI applications.   
     - Reusable components including datasets, models, and indexes.
     - An isolated container to upload data to (within the storage inherited from the hub).
@@ -51,13 +53,13 @@ At the top level, AI Studio provides access to the following resources:
 
     For more information, visit [Hubs and projects overview](ai-resources.md).
 
-- **Connections**: Azure AI Studio hubs and projects use connections to access resources provided by other services. For example, data in an Azure Storage Account, Azure OpenAI or other Azure AI services.
+- **Connections**: Azure AI Foundry hubs and projects use connections to access resources provided by other services. For example, data in an Azure Storage Account, Azure OpenAI or other Azure AI services.
 
     For more information, visit [Connections](connections.md).
 
 ## Azure resource types and providers
 
-Azure AI Studio is built on the Azure Machine Learning resource provider, and takes a dependency on several other Azure services. The resource providers for these services must be registered in your Azure subscription. The following table lists the resource types, provider, and kind:
+Azure AI Foundry is built on the Azure Machine Learning resource provider, and takes a dependency on several other Azure services. The resource providers for these services must be registered in your Azure subscription. The following table lists the resource types, provider, and kind:
 
 [!INCLUDE [Resource provider kinds](../includes/resource-provider-kinds.md)]
 
@@ -72,7 +74,7 @@ For information on registering resource providers, see [Register an Azure resour
 
 ### Microsoft-hosted resources
 
-While most of the resources used by Azure AI Studio live in your Azure subscription, some resources are in an Azure subscription managed by Microsoft. The cost for these managed resources shows on your Azure bill as a line item under the Azure Machine Learning resource provider. The following resources are in the Microsoft-managed Azure subscription, and don't appear in your Azure subscription:
+While most of the resources used by Azure AI Foundry live in your Azure subscription, some resources are in an Azure subscription managed by Microsoft. The cost for these managed resources shows on your Azure bill as a line item under the Azure Machine Learning resource provider. The following resources are in the Microsoft-managed Azure subscription, and don't appear in your Azure subscription:
 
 - **Managed compute resources**: Provided by Azure Batch resources in the Microsoft subscription.
 - **Managed virtual network**: Provided by Azure Virtual Network resources in the Microsoft subscription. If FQDN rules are enabled, an Azure Firewall (standard) is added and charged to your subscription. For more information, see [Configure a managed virtual network for Azure AI Studio](../how-to/configure-managed-network.md).
@@ -91,7 +93,7 @@ Hubs provide a central way for a team to govern security, connectivity, and comp
 
 Often, projects in a business domain require access to the same company resources such as vector indices, model endpoints, or repos. As a team lead, you can preconfigure connectivity with these resources within a hub, so developers can access them from any new project workspace without delay on IT.
 
-[Connections](connections.md) let you access objects in AI Studio that are managed outside of your hub. For example, uploaded data on an Azure storage account, or model deployments on an existing Azure OpenAI resource. A connection can be shared with every project or made accessible to one specific project. Connections can be configured to use key-based access or Microsoft Entra ID passthrough to authorize access to users on the connected resource. As an administrator, you can  track, audit, and manage connections across the organization from a single view in AI Studio.
+[Connections](connections.md) let you access objects in AI Foundry that are managed outside of your hub. For example, uploaded data on an Azure storage account, or model deployments on an existing Azure OpenAI resource. A connection can be shared with every project or made accessible to one specific project. Connections can be configured to use key-based access or Microsoft Entra ID passthrough to authorize access to users on the connected resource. As an administrator, you can  track, audit, and manage connections across the organization from a single view in AI Foundry.
 
 :::image type="content" source="../media/concepts/connected-resources-spog.png" alt-text="Screenshot of AI Studio showing an audit view of all connected resources across a hub and its projects." :::
 
@@ -105,15 +107,15 @@ If you require isolation between dev, test, and production as part of your LLMOp
 
 Azure AI services including Azure OpenAI provide control plane endpoints for operations such as listing model deployments. These endpoints are secured using a separate Azure role-based access control (RBAC) configuration than the one used for a hub. 
 
-To reduce the complexity of Azure RBAC management, AI Studio 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 Studio service then performs the call to the Azure AI services or Azure OpenAI control plane endpoint on your behalf.
+To reduce the complexity of Azure RBAC management, 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 Studio](rbac-ai-studio.md).
 
 ## Attribute-based access control
 
 Each hub you create has a default storage account. Each child project of the hub inherits the storage account of the hub. The storage account is used to store data and artifacts.
 
-To secure the shared storage account, Azure AI Studio uses both Azure RBAC and Azure attribute-based access control (Azure ABAC). Azure ABAC is a security model that defines access control based on attributes associated with the user, resource, and environment. Each project has:
+To secure the shared storage account, Azure AI Foundry uses both Azure RBAC and Azure attribute-based access control (Azure ABAC). Azure ABAC is a security model that defines access control based on attributes associated with the user, resource, and environment. Each project has:
 
 - A service principal that is assigned the Storage Blob Data Contributor role on the storage account.
 - A unique ID (workspace ID).
@@ -142,7 +144,7 @@ The default storage account for a hub has the following containers. These contai
 
 ## Encryption
 
-Azure AI Studio uses encryption to protect data at rest and in transit. By default, Microsoft-managed keys are used for encryption. However you can use your own encryption keys. For more information, see [Customer-managed keys](../../ai-services/encryption/cognitive-services-encryption-keys-portal.md?context=/azure/ai-studio/context/context).
+Azure AI Foundry uses encryption to protect data at rest and in transit. By default, Microsoft-managed keys are used for encryption. However you can use your own encryption keys. For more information, see [Customer-managed keys](../../ai-services/encryption/cognitive-services-encryption-keys-portal.md?context=/azure/ai-studio/context/context).
 
 ## Virtual network
 
@@ -155,7 +157,7 @@ For more information on how to configure a managed virtual network, see [Configu
 
 ## Azure Monitor
 
-Azure monitor and Azure Log Analytics provide monitoring and logging for the underlying resources used by Azure AI Studio. Since Azure AI Studio is built on Azure Machine Learning, Azure OpenAI, Azure AI services, and Azure AI Search, use the following articles to learn how to monitor the services:
+Azure monitor and Azure Log Analytics provide monitoring and logging for the underlying resources used by Azure AI Foundry. Since Azure AI Foundry is built on Azure Machine Learning, Azure OpenAI, Azure AI services, and Azure AI Search, use the following articles to learn how to monitor the services:
 
 | Resource | Monitoring and logging |
 | --- | --- |
@@ -175,6 +177,6 @@ For more information on price and quota, use the following articles:
 
 Create a hub using one of the following methods:
 
-- [Azure AI Studio](../how-to/create-azure-ai-resource.md#create-a-hub-in-ai-studio): Create a hub for getting started.
+- [Azure AI Foundry portal](../how-to/create-azure-ai-resource.md#create-a-hub-in-ai-studio): Create a hub for getting started.
 - [Azure portal](../how-to/create-secure-ai-hub.md): Create a hub with your own networking.
 - [Bicep template](../how-to/create-azure-ai-hub-template.md).

articles/ai-studio/what-is-ai-studio.md

@@ -18,7 +18,7 @@ ms.custom: ignite-2023, build-2024
 
 [Azure AI Foundry](https://ai.azure.com) is a trusted platform that empowers developers to drive innovation and shape the future with AI in a safe, secure, and responsible way.
 
-[!INCLUDE [new-name](../includes/new-name.md)]
+[!INCLUDE [new-name](includes/new-name.md)]
 
 [AI Foundry](https://ai.azure.com) is designed for developers to: