# Launch RSessions from the RStudio Launcher


**Important**  
Custom IAM policies that allow Amazon SageMaker Studio or Amazon SageMaker Studio Classic to create Amazon SageMaker resources must also grant permissions to add tags to those resources. The permission to add tags to resources is required because Studio and Studio Classic automatically tag any resources they create. If an IAM policy allows Studio and Studio Classic to create resources but does not allow tagging, "AccessDenied" errors can occur when trying to create resources. For more information, see [Provide permissions for tagging SageMaker AI resources](security_iam_id-based-policy-examples.md#grant-tagging-permissions).  
[AWS managed policies for Amazon SageMaker AI](security-iam-awsmanpol.md) that give permissions to create SageMaker resources already include permissions to add tags while creating those resources.

 The following sections show how to use the RStudio Launcher to launch RSessions. They also include information about how to open the RStudio Launcher when using RStudio on Amazon SageMaker AI.

## Open RStudio Launcher


Open the RStudio launcher using the following set of procedures that matches your environment.

### Open RStudio Launcher from the Amazon SageMaker AI Console


1. Open the Amazon SageMaker AI console at [https://console.aws.amazon.com/sagemaker/](https://console.aws.amazon.com/sagemaker/).

1.  From the left navigation, select **RStudio**.

1.  Under **Get Started**, select the domain and user profile to launch.

1.  Choose **Launch RStudio**.

### Open RStudio Launcher from Amazon SageMaker Studio


1. Navigate to Studio following the steps in [Launch Amazon SageMaker Studio](studio-updated-launch.md).

1. Under **Applications**, select **RStudio**.

1. From the RStudio landing page, choose **Launch application**.

### Open RStudio Launcher from the AWS CLI


The procedure to open the RStudio Launcher using the AWS CLI differs depending on the method used to manage your users. 

 **IAM Identity Center** 

1.  Use the AWS access portal to open your Amazon SageMaker AI domain. 

1.  Modify the URL path to “/rstudio/default” as follows. 

   ```
   #Studio URL
   https://<domain-id>.studio.<region>.sagemaker.aws/jupyter/default/lab
   
   #modified URL
   https://<domain-id>.studio.<region>.sagemaker.aws/rstudio/default
   ```

 **IAM** 

 To open the RStudio Launcher from the AWS CLI in IAM mode, complete the following procedure. 

1.  Create a presigned URL using the following command. 

   ```
   aws sagemaker create-presigned-domain-url --region <REGION> \
       --domain-id <DOMAIN-ID> \
       --user-profile-name <USER-PROFILE-NAME>
   ```

1.  Append *&redirect=RStudioServerPro* to the generated URL. 

1.  Navigate to the updated URL. 

## Launch RSessions


 After you’ve launched the RStudio Launcher, you can create a new RSession. 

1.  Select **New Session**. 

1.  Enter a **Session Name**. 

1.  Select an instance type that your RSession runs on. This defaults to `ml.t3.medium`.

1.  Select an Image that your RSession uses as the kernel. 

1.  Select Start Session. 

1.  After your session has been created, you can start it by selecting the name.  
**Note**  
If you receive a warning that there is a version mismatch between your RSession and RStudioServerPro apps, then you must upgrade the version of your RStudioServerPro app. For more information, see [RStudio Versioning](rstudio-version.md).