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@@ -50,12 +50,6 @@ Choose the tab for the environment you're using for other prerequisites.
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* No extra prerequisites.
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# [Studio (preview)](#tab/azure-studio-preview)
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* To use the Studio (preview) version, enable the preview feature **Create Compute Instances using the optimized creation wizard**:
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:::image type="content" source="media/how-to-create-compute-instance/preview-panel.png" alt-text="Screenshot shows how to enable the preview feature.":::
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---
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## Create
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# [Studio](#tab/azure-studio)
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1. Navigate to [Azure Machine Learning studio](https://ml.azure.com).
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1. Under __Manage__, select __Compute__.
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1. Select **Compute instance** at the top.
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1. If you have no compute instances, select **Create** in the middle of the page.
|Compute name | - Name is required and must be between 3 to 24 characters long.<br/> - Valid characters are upper and lower case letters, digits, and the **-** character.<br/> - Name must start with a letter<br/> - Name needs to be unique across all existing computes within an Azure region. You see an alert if the name you choose isn't unique<br/> - If **-** character is used, then it needs to be followed by at least one letter later in the name |
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|Virtual machine type | Choose CPU or GPU. This type can't be changed after creation |
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|Virtual machine size | Supported virtual machine sizes might be restricted in your region. Check the [availability list](https://azure.microsoft.com/global-infrastructure/services/?products=virtual-machines)|
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1. Select **Create** unless you want to configure advanced settings for the compute instance.
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1. <aname="advanced-settings"></a> Select **Next: Advanced Settings** if you want to:
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* Enable idle shutdown. Configure a compute instance to automatically shut down if it's inactive. For more information, see [enable idle shutdown](#configure-idle-shutdown).
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* Add schedule. Schedule times for the compute instance to automatically start and/or shut down. For more information, see [schedule details](#schedule-automatic-start-and-stop).
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* Enable SSH access. Follow the information in the [detailed SSH access instructions](#enable-ssh-access) section.
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* Enable virtual network:
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* If you're using an __Azure Virtual Network__, specify the **Resource group**, **Virtual network**, and **Subnet** to create the compute instance inside an Azure Virtual Network. You can also select __No public IP__ to prevent the creation of a public IP address, which requires a private link workspace. You must also satisfy these [network requirements](./how-to-secure-training-vnet.md) for virtual network setup.
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* If you're using an Azure Machine Learning __managed virtual network__, the compute instance is created inside the managed virtual network. You can also select __No public IP__ to prevent the creation of a public IP address. For more information, see [managed compute with a managed network](./how-to-managed-network-compute.md).
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* Assign the computer to another user. For more about assigning to other users, see [Create on behalf of](#create-on-behalf-of).
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* Provision with a setup script - for more information about how to create and use a setup script, see [Customize the compute instance with a script](how-to-customize-compute-instance.md).
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# [Studio (preview)](#tab/azure-studio-preview)
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1. Navigate to [Azure Machine Learning studio](https://ml.azure.com).
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1. Under __Manage__, select __Compute__.
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1. Select **Compute instance** at the top.
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# [Studio](#tab/azure-studio)
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* When creating a new compute instance:
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1. Select **Advanced** after completing required settings.
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1. Select **Enable idle shutdown** to enable or disable.
1. In the list, select the compute instance you wish to change
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1. Select the **Edit** pencil in the **Schedules** section.
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:::image type="content" source="media/how-to-create-compute-instance/edit-idle-time.png" alt-text="Screenshot: Edit idle time for a compute instance." lightbox="media/how-to-create-compute-instance/edit-idle-time.png":::
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# [Studio (preview)](#tab/azure-studio-preview)
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* When creating a new compute instance:
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1. Select **Next** to advance to **Scheduling** after completing required settings.
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# [Studio](#tab/azure-studio)
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1. [Fill out the form](?tabs=azure-studio#create).
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1. On the second page of the form, open **Show advanced settings**.
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1. Select **Add schedule** to add a new schedule.
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:::image type="content" source="media/how-to-create-attach-studio/create-schedule.png" alt-text="Screenshot: Add schedule in advanced settings.":::
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1. Select **Start compute instance** or **Stop compute instance**.
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1. Select the **Time zone**.
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1. Select the **Startup time** or **Shutdown time**.
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1. Select the days when this schedule is active.
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:::image type="content" source="media/how-to-create-attach-studio/stop-compute-schedule.png" alt-text="Screenshot: schedule a compute instance to shut down.":::
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1. Select **Add schedule** again if you want to create another schedule.
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Once the compute instance is created, you can view, edit, or add new schedules from the compute instance details section.
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> [!NOTE]
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> Timezone labels don't account for day light savings. For instance, (UTC+01:00) Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna is actually UTC+02:00 during day light savings.
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# [Studio (preview)](#tab/azure-studio-preview)
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1. [Fill out the form](?tabs=azure-studio-preview#create).
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1. Select **Next** to advance to **Scheduling** after completing required settings.
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1. Select **Add schedule** to add a new schedule.
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As an administrator, you can create a compute instance on behalf of a data scientist and assign the instance to them with:
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* Studio, using the [Advanced settings](?tabs=azure-studio#advanced-settings) or [Security settings (preview)](?tabs=azure-studio-preview#security-settings)
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* Studio, using the [Security settings](?tabs=azure-studio-preview#security-settings)
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* [Azure Resource Manager template](https://github.com/Azure/azure-quickstart-templates/tree/master/quickstarts/microsoft.machinelearningservices/machine-learning-compute-create-computeinstance). For details on how to find the TenantID and ObjectID needed in this template, see [Find identity object IDs for authentication configuration](../healthcare-apis/azure-api-for-fhir/find-identity-object-ids.md). You can also find these values in the Microsoft Entra admin center.
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@@ -574,21 +488,12 @@ identity:
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- resource_id: identity_resource_id
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```
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# [Studio](#tab/azure-studio)
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You can create compute instance with managed identity from Azure Machine Learning studio:
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1. Fill out the form to [create a new compute instance](?tabs=azure-studio#create).
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1. Select **Next: Advanced Settings**.
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1. Enable **Assign a managed identity**.
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1. Select **System-assigned** or **User-assigned** under **Identity type**.
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1. If you selected **User-assigned**, select subscription and name of the identity.
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# [Studio (preview)](#tab/azure-studio-preview)
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You can create compute instance with managed identity from Azure Machine Learning studio:
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1. Fill out the form to [create a new compute instance](?tabs=azure-studio-preview#create).
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1. Select **Security**.
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1. Enable **Assign a managed identity**.
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1. Select **System-assigned** or **User-assigned** under **Identity type**.
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You can set up other applications, such as RStudio, or Posit Workbench (formerly RStudio Workbench), when creating a compute instance. Follow these steps in studio to set up a custom application on your compute instance
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# [Python SDK](#tab/python)
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Use either Studio or Studio (preview) to see how to set up applications.
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# [Azure CLI](#tab/azure-cli)
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Use either Studio or Studio (preview) to see how to set up applications.
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# [Studio](#tab/azure-studio)
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1. Fill out the form to [create a new compute instance](?tabs=azure-studio#create)
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1. Select **Next: Advanced Settings**
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1. Select **Add application** under the **Custom application setup (RStudio Workbench, etc.)** section
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:::image type="content" source="media/how-to-create-compute-instance/custom-service-setup.png" alt-text="Screenshot showing Custom Service Setup.":::
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# [Studio (preview)](#tab/azure-studio-preview)
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1. Fill out the form to [create a new compute instance](?tabs=azure-studio-preview#create)
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1. Select **Applications**
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1. Select **Add application**
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:::image type="content" source="media/how-to-create-compute-instance/custom-service-setup-preview.png" alt-text="Screenshot showing Custom Service Setup.":::
RStudio is one of the most popular IDEs among R developers for ML and data science projects. You can easily set up Posit Workbench, which provides access to RStudio along with other development tools, to run on your compute instance, using your own Posit license, and access the rich feature set that Posit Workbench offers
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