Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that enables data scientists and developers to perform every step of the ML workflow, from preparing data to building, training, tuning, and deploying models.
To access SageMaker Studio, Amazon SageMaker Canvas, or other Amazon ML environments like RStudio on Amazon SageMaker, you must first provision a SageMaker domain. A SageMaker domain includes an associated Amazon Elastic File System (Amazon EFS) volume; a list of authorized users; and a variety of security, application, policy, and Amazon Virtual Private Cloud (Amazon VPC) configurations.
Administrators can now provision multiple SageMaker domains in order to separate different lines of business or teams within a single AWS account. This creates a logical separation between the users, files storage, and configuration settings for various groups in your organization. As an example, your organization may want to separate your financial line of business

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