Amazon SageMaker AI Notebook instances provide a fully managed Jupyter environment for running graph notebooks that are connected to a Neptune Analytics graph. SageMaker AI Notebooks run natively on Amazon Linux 2, and support use of the Jupyter Classic Notebook or JupyterLab 3 interface on the same instance.
You can use one of the following AWS CloudFormation templates to set up a new Neptune Analytics notebook to use with your Neptune Analytics graph:
To use an AWS CloudFormation stack to create a new Neptune Analytics notebook
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Choose one of the Launch Stack buttons in the following table to launch the AWS CloudFormation stack on the AWS CloudFormation console.
Region View View in Designer Launch US East (N. Virginia) View View in Designer 
US East (Ohio) View View in Designer
US West (Oregon) View View in Designer
Europe (Ireland) View View in Designer
Europe (Frankfurt) View View in Designer
Asia Pacific (Tokyo) View View in Designer
Asia Pacific (Singapore) View View in Designer
On the Select Template page, choose Next.
In the Stack Details page, under GraphEndpoint, enter the public or private endpoint of your Neptune Analytics graph.
Under Notebook Name enter a name for the new notebook that is unique for your account and region in SageMaker AI.
On the Options page, choose Next.
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If you're using a private endpoint for your Neptune Analytics graph, enter the following under Network Options:
Under GraphVPC enter the ID of a VPC associated with the private graph endpoint.
Under GraphSubnetId enter the ID of any subnet associated with your private graph endpoint.
Under GraphSecurityGroup enter the ID of a security group associated with the VPC. This is optional; if not provided, a new security group is automatically created for this purpose.
Click through the rest of the stack creation steps, leaving everything as default, and submit for creation.
In around 5 minutes, you should see the new Neptune Analytics notebook appear in the SageMaker AI and Neptune consoles.
