Edits

Author: kraigb

articles/notebooks/configure-manage-azure-notebooks-projects.md

@@ -37,13 +37,13 @@ The **Run** drop-down list on the project dashboard is where you select the comp
 
 ![Compute tier drop-down list on the project dashboard](media/project-compute-tier-list.png)
 
-You can bypass these limitations by using a different virtual machine that you've provisioned in an Azure subscription. You must install and run JupyterHub on that virtual machine. The Data Science Virtual Machine for Linux (Ubuntu) image is a good choice because it is supported, it has a compatible JupyterHub by default, and it will be automatically discovered.
+You can bypass these limitations by using a different virtual machine that you've provisioned in an Azure subscription. You must install and run JupyterHub on that virtual machine. The [Data Science Virtual Machine (DSVM) for Linux (Ubuntu)](/azure/machine-learning/data-science-virtual-machine) image is a good choice because it's supported, it includes a compatible JupyterHub by default, and it's automatically discovered by Azure Notebooks.
 
 Once you have a suitably configured Azure virtual machine, select the **Direct Compute** option in the drop-down list, which prompts you for a name (to show in the list), the VM's IP address and port (typically 8000, the default port to which JupyterHub listens), and the VM credentials:
 
 ![Prompt to collect server information for the Direct Compute option](media/project-compute-tier-direct.png)
 
-If the following conditions are true, the drop-down list also shows [Data Science Virtual Machine (DSVM)](/azure/machine-learning/data-science-virtual-machine) instances. (If any of these conditions aren't met, you can still connect to the DSVM using the Direct Compute option and enter the values obtained from the Azure portal.)
+If the following conditions are true, the drop-down list also shows DSVM instances. (If any of these conditions aren't met, you can still connect to the DSVM using the Direct Compute option and enter the values obtained from the Azure portal.)
 
 - You're signed into Azure Notebooks with an account that uses Azure Active Directory (AAD), such as a company account.
 - Your account is connected to an Azure subscription.
@@ -53,17 +53,12 @@ If the following conditions are true, the drop-down list also shows [Data Scienc
 
 When you select a DSVM instance, Azure Notebooks may prompt you for the specific machine credentials used when you created the VM.
 
-To create a new DSVM instance, follow the instructions on [Create an Ubuntu Data Science VM](/azure/machine-learning/data-science-virtual-machine/dsvm-ubuntu-intro). Use the **Data Science Virtual Machine for Linux (Ubuntu)** image if you want the DSVM to appear in the drop-down list in Azure Notebooks. 
+To create a new DSVM instance, follow the instructions on [Create an Ubuntu Data Science VM](/azure/machine-learning/data-science-virtual-machine/dsvm-ubuntu-intro). Use the **Data Science Virtual Machine for Linux (Ubuntu)** image if you want the DSVM to appear in the drop-down list in Azure Notebooks.
 
-> When a project is run on a VM the files will be mounted on the root directory of the Jupyter Server replacing the default Azure Notebooks files.
+> [!NOTE]
+> When a project is run on a VM, the files are mounted on the root directory of the Jupyter server (the directory shown in JupyterHub), replacing the default Azure Notebooks files. When you shut down the VM using the **Shutdown** button on the notebook UI, Azure Notebooks restores the default files.
 >
-> If you would like to get the default files back then you will need to shutdown the compute.
->
-> ![Shutdown compute](media/shutdown.png)
->
-> Then the default files will reappear if you go to JupyterHub directly.
->
-> ![Default Azure Notebooks files](media/juptyerhub-files.png)
+> ![Shutdown button in Azure Notebooks](media/shutdown.png)
 
 > [!IMPORTANT]
 > When using different virtual machines, the notebooks you run on them must be entirely self-contained. At present, Azure Notebooks copies only the *.ipynb* file to the VM but doesn't copy any other files in the project. As a result, notebooks running on other VMs fail to find other project files.