Merge pull request #265391 from eric-urban/eur/azure-ai-hub

change ai resource to ai hub resource

Author: ttorble

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

@@ -17,7 +17,7 @@ author: eric-urban
 
 [!INCLUDE [Azure AI Studio preview](../includes/preview-ai-studio.md)]
 
-Connections in Azure AI Studio are a way to authenticate and consume both Microsoft and third-party resources within your Azure AI projects. For example, connections can be used for prompt flow, training data, and deployments. [Connections can be created](../how-to/connections-add.md) exclusively for one project or shared with all projects in the same Azure AI resource. 
+Connections in Azure AI Studio are a way to authenticate and consume both Microsoft and third-party resources within your Azure AI projects. For example, connections can be used for prompt flow, training data, and deployments. [Connections can be created](../how-to/connections-add.md) exclusively for one project or shared with all projects in the same Azure AI hub resource. 
 
 ## Connections to Azure AI services
 
@@ -73,9 +73,9 @@ A Uniform Resource Identifier (URI) represents a storage location on your local
 
 ## Key vaults and secrets
 
-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 an Azure AI resource level (link to connection rbac). 
+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 an Azure AI hub resource level (link to connection rbac). 
 
-Azure connections serve as key vault proxies, and interactions with connections are direct interactions with an Azure key vault. Azure AI Studio connections store API keys securely, as secrets, in a key vault. The key vault [Azure role-based access control (Azure RBAC)](./rbac-ai-studio.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 are stored in the Azure AI resource'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 Studio connections store API keys securely, as secrets, in a key vault. The key vault [Azure role-based access control (Azure RBAC)](./rbac-ai-studio.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 are stored in the Azure AI hub resource'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-studio/concepts/connections.md

@@ -32,7 +32,7 @@ Azure AI Studio simplifies deployments. A simple select or a line of code deploy
 
 ### Azure OpenAI models
 
-Azure OpenAI allows you to get access to the latest OpenAI models with the enterprise features from Azure. Learn more about [how to deploy OpenAI models in AI studio](../how-to/deploy-models-openai.md).
+Azure OpenAI allows you to get access to the latest OpenAI models with the enterprise features from Azure. Learn more about [how to deploy OpenAI models in AI Studio](../how-to/deploy-models-openai.md).
 
 ### Open models
 

articles/ai-studio/concepts/deployments-overview.md

@@ -22,7 +22,7 @@ Mitigating harms presented by large language models (LLMs) such as the Azure Ope
 :::image type="content" source="../media/evaluations/mitigation-layers.png" alt-text="Diagram of strategy to mitigate potential harms of generative AI applications." lightbox="../media/evaluations/mitigation-layers.png":::
 
  ## Model layer
-At the model level, it's important to understand the models you use and what fine-tuning steps might have been taken by the model developers to align the model towards its intended uses and to reduce the risk of potentially harmful uses and outcomes. Azure AI studio's model catalog enables you to explore models from Azure OpenAI Service, Meta, etc., organized by collection and task. In the [model catalog](../how-to/model-catalog.md), you can explore model cards to understand model capabilities and limitations, experiment with sample inferences, and assess model performance. You can further compare multiple models side-by-side through benchmarks to select the best one for your use case. Then, you can enhance model performance by fine-tuning with your training data. 
+At the model level, it's important to understand the models you use and what fine-tuning steps might have been taken by the model developers to align the model towards its intended uses and to reduce the risk of potentially harmful uses and outcomes. Azure AI Studio's model catalog enables you to explore models from Azure OpenAI Service, Meta, etc., organized by collection and task. In the [model catalog](../how-to/model-catalog.md), you can explore model cards to understand model capabilities and limitations, experiment with sample inferences, and assess model performance. You can further compare multiple models side-by-side through benchmarks to select the best one for your use case. Then, you can enhance model performance by fine-tuning with your training data. 
 
 ## Safety systems layer
 For most applications, it’s not enough to rely on the safety fine-tuning built into the model itself.  LLMs can make mistakes and are susceptible to attacks like jailbreaks. In many applications at Microsoft, we use another AI-based safety system, [Azure AI Content Safety](https://azure.microsoft.com/products/ai-services/ai-content-safety/), to provide an independent layer of protection, helping you to block the output of harmful content.  

articles/ai-studio/concepts/evaluation-improvement-strategies.md

@@ -17,31 +17,31 @@ author: Blackmist
 
 [!INCLUDE [Azure AI Studio preview](../includes/preview-ai-studio.md)]
 
-In this article, you learn how to manage access (authorization) to an Azure AI resource. Azure Role-based access control is used to manage access to Azure resources, such as the ability to create new resources or use existing ones. Users in your Microsoft Entra ID are assigned specific roles, which grant access to resources. Azure provides both built-in roles and the ability to create custom roles. 
+In this article, you learn how to manage access (authorization) to an Azure AI hub resource. Azure Role-based access control is used to manage access to Azure resources, such as the ability to create new resources or use existing ones. Users in your Microsoft Entra ID are assigned specific roles, which grant access to resources. Azure provides both built-in roles and the ability to create custom roles. 
 
 > [!WARNING]
 > Applying some roles might limit UI functionality in Azure AI Studio for other users. For example, if a user's role does not have the ability to create a compute instance, the option to create a compute instance will not be available in studio. This behavior is expected, and prevents the user from attempting operations that would return an access denied error. 
 
-## Azure AI resource vs Azure AI project
-In the Azure AI Studio, there are two levels of access: the Azure AI resource and the Azure AI project. The resource is home to the infrastructure (including virtual network setup, customer-managed keys, managed identities, and policies) as well as where you configure your Azure AI services. Azure AI resource access can allow you to modify the infrastructure, create new Azure AI resources, and create projects. Azure AI projects are a subset of the Azure AI resource that act as workspaces that allow you to build and deploy AI systems. Within a project you can develop flows, deploy models, and manage project assets. Project access lets you develop AI end-to-end while taking advantage of the infrastructure setup on the Azure AI resource.
+## Azure AI hub resource vs Azure AI project
+In the Azure AI Studio, there are two levels of access: the Azure AI hub resource and the Azure AI project. The resource is home to the infrastructure (including virtual network setup, customer-managed keys, managed identities, and policies) as well as where you configure your Azure AI services. Azure AI hub resource access can allow you to modify the infrastructure, create new Azure AI hub resources, and create projects. Azure AI projects are a subset of the Azure AI hub resource that act as workspaces that allow you to build and deploy AI systems. Within a project you can develop flows, deploy models, and manage project assets. Project access lets you develop AI end-to-end while taking advantage of the infrastructure setup on the Azure AI hub resource.
 
-## Default roles for the Azure AI resource 
+## Default roles for the Azure AI hub resource 
 
-The Azure AI Studio has built-in roles that are available by default. In addition to the Reader, Contributor, and Owner roles, the Azure AI Studio has a new role called Azure AI Developer. This role can be assigned to enable users to create connections, compute, and projects, but not let them create new Azure AI resources or change permissions of the existing Azure AI resource.
+The Azure AI Studio has built-in roles that are available by default. In addition to the Reader, Contributor, and Owner roles, the Azure AI Studio has a new role called Azure AI Developer. This role can be assigned to enable users to create connections, compute, and projects, but not let them create new Azure AI hub resources or change permissions of the existing Azure AI hub resource.
 
-Here's a table of the built-in roles and their permissions for the Azure AI resource:
+Here's a table of the built-in roles and their permissions for the Azure AI hub resource:
 
 | Role | Description | 
 | --- | --- |
-| Owner | Full access to the Azure AI resource, including the ability to manage and create new Azure AI resources and assign permissions. This role is automatically assigned to the Azure AI resource creator|
-| Contributor |    User has full access to the Azure AI resource, including the ability to create new Azure AI resources, but isn't able to manage Azure AI resource permissions on the existing resource. |
-| Azure AI Developer |     Perform all actions except create new Azure AI resources and manage the Azure AI resource permissions. For example, users can create projects, compute, and connections. Users can assign permissions within their project. Users can interact with existing AI resources such as Azure OpenAI, Azure AI Search, and Azure AI services. |
-| Reader |     Read only access to the Azure AI resource. This role is automatically assigned to all project members within the Azure AI resource. |
+| Owner | Full access to the Azure AI hub resource, including the ability to manage and create new Azure AI hub resources and assign permissions. This role is automatically assigned to the Azure AI hub resource creator|
+| Contributor |    User has full access to the Azure AI hub resource, including the ability to create new Azure AI hub resources, but isn't able to manage Azure AI hub resource permissions on the existing resource. |
+| Azure AI Developer |     Perform all actions except create new Azure AI hub resources and manage the Azure AI hub resource permissions. For example, users can create projects, compute, and connections. Users can assign permissions within their project. Users can interact with existing Azure AI resources such as Azure OpenAI, Azure AI Search, and Azure AI services. |
+| Reader |     Read only access to the Azure AI hub resource. This role is automatically assigned to all project members within the Azure AI hub resource. |
 
 
-The key difference between Contributor and Azure AI Developer is the ability to make new Azure AI resources. If you don't want users to make new Azure AI resources (due to quota, cost, or just managing how many Azure AI resources you have), assign the AI Developer role.
+The key difference between Contributor and Azure AI Developer is the ability to make new Azure AI hub resources. If you don't want users to make new Azure AI hub resources (due to quota, cost, or just managing how many Azure AI hub resources you have), assign the AI Developer role.
 
-Only the Owner and Contributor roles allow you to make an Azure AI resource. At this time, custom roles won't grant you permission to make Azure AI resources.
+Only the Owner and Contributor roles allow you to make an Azure AI hub resource. At this time, custom roles won't grant you permission to make Azure AI hub resources.
 
 The full set of permissions for the new "Azure AI Developer" role are as follows:
 
@@ -91,7 +91,7 @@ Here's a table of the built-in roles and their permissions for the Azure AI proj
 | Azure AI Developer |     User can perform most actions, including create deployments, but can't assign permissions to project users. |
 | Reader |     Read only access to the Azure AI project. |
 
-When a user gets access to a project, two more roles are automatically assigned to the project user. The first role is Reader on the Azure AI resource. The second role is the Inference Deployment Operator role, which allows the user to create deployments on the resource group that the project is in. This role is composed of these two permissions: ```"Microsoft.Authorization/*/read"``` and    ```"Microsoft.Resources/deployments/*"```.
+When a user gets access to a project, two more roles are automatically assigned to the project user. The first role is Reader on the Azure AI hub resource. The second role is the Inference Deployment Operator role, which allows the user to create deployments on the resource group that the project is in. This role is composed of these two permissions: ```"Microsoft.Authorization/*/read"``` and    ```"Microsoft.Resources/deployments/*"```.
 
 In order to complete end-to-end AI development and deployment, users only need these two autoassigned roles and either the Contributor or Azure AI Developer role on a *project*.
 
@@ -100,22 +100,22 @@ Below is an example of how to set up role-based access control for your Azure AI
 
 | Persona | Role | Purpose |
 | --- | --- | ---|
-| IT admin | Owner of the Azure AI resource | The IT admin can ensure the Azure AI resource is set up to their enterprise standards and assign managers the Contributor role on the resource if they want to enable managers to make new Azure AI resources or they can assign managers the Azure AI Developer role on the resource to not allow for new Azure AI resource creation. |
-| Managers | Contributor or Azure AI Developer on the Azure AI resource | Managers can create projects for their team and create shared resources (ex: compute and connections) for their group at the Azure AI resource level. |
+| IT admin | Owner of the Azure AI hub resource | The IT admin can ensure the Azure AI hub resource is set up to their enterprise standards and assign managers the Contributor role on the resource if they want to enable managers to make new Azure AI hub resources or they can assign managers the Azure AI Developer role on the resource to not allow for new Azure AI hub resource creation. |
+| Managers | Contributor or Azure AI Developer on the Azure AI hub resource | Managers can create projects for their team and create shared resources (ex: compute and connections) for their group at the Azure AI hub resource level. |
 | Managers | Owner of the Azure AI Project | When managers create a project, they become the project owner. This allows them to add their team/developers to the project. Their team/developers can be added as Contributors or Azure AI Developers to allow them to develop in the project. |
 | Team members/developers | Contributor or Azure AI Developer on the Azure AI Project | Developers can build and deploy AI models within a project and create assets that enable development such as computes and connections. |
 
-## Access to resources created outside of the Azure AI resource
+## Access to resources created outside of the Azure AI hub resource
 
-When you create an Azure AI resource, the built-in role-based access control permissions grant you access to use the resource. However, if you wish to use resources outside of what was created on your behalf, you need to ensure both: 
+When you create an Azure AI hub resource, the built-in role-based access control permissions grant you access to use the resource. However, if you wish to use resources outside of what was created on your behalf, you need to ensure both: 
 - The resource you're trying to use has permissions set up to allow you to access it.
-- Your Azure AI resource is allowed to access it. 
+- Your Azure AI hub resource is allowed to access it. 
 
-For example, if you're trying to consume a new Blob storage, you need to ensure that Azure AI resource's managed identity is added to the Blob Storage Reader role for the Blob. If you're trying to use a new Azure AI Search source, you might need to add the Azure AI resource to the Azure AI Search's role assignments. 
+For example, if you're trying to consume a new Blob storage, you need to ensure that Azure AI hub resource's managed identity is added to the Blob Storage Reader role for the Blob. If you're trying to use a new Azure AI Search source, you might need to add the Azure AI hub resource to the Azure AI Search's role assignments. 
 
 ## Manage access with roles 
 
-If you're an owner of an Azure AI resource, you can add and remove roles for the Studio. Within the Azure AI Studio, go to **Manage** and select your Azure AI resource. Then select **Permissions** to add and remove users for the Azure AI resource. You can also manage permissions from the Azure portal under **Access Control (IAM)** or through the Azure CLI. For example, use the [Azure CLI](/cli/azure/) to assign the Azure AI Developer role to "[email protected]" for resource group "this-rg" with the following command: 
+If you're an owner of an Azure AI hub resource, you can add and remove roles for the Studio. Within the Azure AI Studio, go to **Manage** and select your Azure AI hub resource. Then select **Permissions** to add and remove users for the Azure AI hub resource. You can also manage permissions from the Azure portal under **Access Control (IAM)** or through the Azure CLI. For example, use the [Azure CLI](/cli/azure/) to assign the Azure AI Developer role to "[email protected]" for resource group "this-rg" with the following command: 
 
 ```azurecli-interactive
 az role assignment create --role "Azure AI Developer" --assignee "[email protected]" --resource-group this-rg 
@@ -124,7 +124,7 @@ az role assignment create --role "Azure AI Developer" --assignee "[email protected]
 ## Create custom roles
 
 > [!NOTE]
-> In order to make a new Azure AI resource, you need the Owner or Contributor role. At this time, a custom role, even with all actions allowed, will not enable you to make an Azure AI resource. 
+> In order to make a new Azure AI hub resource, you need the Owner or Contributor role. At this time, a custom role, even with all actions allowed, will not enable you to make an Azure AI hub resource. 
 
 If the built-in roles are insufficient, you can create custom roles. Custom roles might have read, write, delete, and compute resource permissions in that AI Studio. You can make the role available at a specific project level, a specific resource group level, or a specific subscription level. 
 
@@ -133,6 +133,6 @@ If the built-in roles are insufficient, you can create custom roles. Custom role
 
 ## Next steps
 
-- [How to create an Azure AI resource](../how-to/create-azure-ai-resource.md)
+- [How to create an Azure AI hub resource](../how-to/create-azure-ai-resource.md)
 - [How to create an Azure AI project](../how-to/create-projects.md)
 - [How to create a connection in Azure AI Studio](../how-to/connections-add.md)