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Merge pull request #210225 from Blackmist/r-studio-vnet.md
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articles/machine-learning/how-to-create-manage-compute-instance.md

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@@ -353,9 +353,6 @@ You can set up other applications, such as RStudio, when creating a compute inst
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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-manage-compute-instance/custom-service-setup.png" alt-text="Screenshot showing Custom Service Setup.":::
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> [!NOTE]
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> Custom applications are currently not supported in private link workspaces.
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### Setup RStudio Workbench
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1. Select **Custom Application** on the **Application** dropdown
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1. Configure the **Application name** you would like to use.
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1. Set up the application to run on **Target port** `8787` - the docker image for RStudio open source listed below needs to run on this Target port.
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> [!TIP]
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> Using ports 8704-8993 is also supported.
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1. Set up the application to be accessed on **Published port** `8787` - you can configure the application to be accessed on a different Published port if you wish.
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> [!TIP]
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> Using ports 8704-8993 is also supported.
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1. Point the **Docker image** to `ghcr.io/azure/rocker-rstudio-ml-verse:latest`.
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1. Use **Bind mounts** to add access to the files in your default storage account:
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* Specify **/home/azureuser/cloudfiles** for **Host path**.
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* Specify **/home/azureuser/cloudfiles** for the **Container path**.
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* Select **Add** to add this mounting. Because the files are mounted, changes you make to them will be available in other compute instances and applications.
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3. Select **Create** to set up RStudio as a custom application on your compute instance.
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1. Select **Create** to set up RStudio as a custom application on your compute instance.
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:::image type="content" source="media/how-to-create-manage-compute-instance/rstudio-open-source.png" alt-text="Screenshot shows form to set up RStudio as a custom application" lightbox="media/how-to-create-manage-compute-instance/rstudio-open-source.png":::
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