# RStudio on Amazon SageMaker AI user guide
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With RStudio support in Amazon SageMaker AI, you can put your production workflows in place and take advantage of SageMaker AI features. The following topics show how to launch an RStudio session and complete key workflows. For information about managing RStudio on SageMaker AI, see [RStudio on Amazon SageMaker AI management](rstudio-manage.md). 

For information about the onboarding steps to create an Amazon SageMaker AI domain with RStudio enabled, see [Amazon SageMaker AI domain overview](gs-studio-onboard.md).  

For information about the Amazon Regions that RStudio on SageMaker AI is supported in, see [Supported Regions and Quotas](regions-quotas.md).  

**Topics**
+ [Collaborate in RStudio](#rstudio-collaborate)
+ [Base R image](#rstudio-base-image)
+ [RSession application colocation](#rstudio-colocation)
+ [Launch RSessions from the RStudio Launcher](rstudio-launcher.md)
+ [Suspend your RSessions](rstudio-launcher-suspend.md)
+ [Delete your RSessions](rstudio-launcher-delete.md)
+ [RStudio Connect](rstudio-connect.md)
+ [Amazon SageMaker AI feature integration with RStudio on Amazon SageMaker AI](rstudio-sm-features.md)

## Collaborate in RStudio
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 To share your RStudio project, you can connect RStudio to your Git repo. For information on setting this up, see [ Version Control with Git and SVN](https://support.rstudio.com/hc/en-us/articles/200532077-Version-Control-with-Git-and-SVN). 

 Note: Project sharing and realtime collaboration are not currently supported when using RStudio on Amazon SageMaker AI.  

## Base R image
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 When launching your RStudio instance, the Base R image serves as the basis of your instance. This image extends the [r-session-complete](https://hub.docker.com/r/rstudio/r-session-complete) Docker image.  

 This Base R image includes the following: 
+  R v4.0 or higher
+  `awscli`, `sagemaker`, and `boto3` Python packages 
+  [Reticulate](https://rstudio.github.io/reticulate/) package for R SDK integration 

## RSession application colocation
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Users can create multiple RSession applications on the same instance. Each instance type supports up to four colocated RSession applications. This applies to each user independently. For example, if two users create applications, then SageMaker AI allocates different underlying instances to each user. Each of these instances would support 4 RSession applications.

Customers only pay for the instance type used regardless of how many Rsession applications are running on the instance. If a user creates an RSession with a different associated instance type, then a new underlying instance is created.