Q: What does Service Workbench on AWS do?
A: Service Workbench on AWS is a web frontend that simplifies the process of standing up compute instances and collaboration on central data for users that need to have simple access to these technologies without having to stand these up through AWS Console. It is an abstraction layer on top of standard AWS services that automates many steps required for these tasks by involving AWS CloudFormation templates. This saves research users time to stand up these environments and allows central administrators to build templates that are secure to prevent the risk of data breaches.
Q: Does the solution provide sample template for compute instances?
A: Out of the box, the solution installs four templates for compute instances, based on AWS CloudFormation templates. These default templates allow to stand up compute instances for: 1) EC2 with Linux operating system; 2) EC2 with Windows operating system; 3) SageMaker with Jupyter Notebook; 4) Hail on EMR
Q: What data stores are currently supported?
A: Service Workbench on AWS currently stores data in Amazon S3 in a bucket it manages. In the future, the system will support the ability to use S3 buckets that are owned and managed by other accounts as well in order to simplify the use of research data in already existing S3 buckets.
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Introduction to AWS CloudFormation
A basic overview of how AWS CloudFormation can be used to automate resource provision. Use cases where AWS CloudFormation is used to repeatedly and predictably create groups of resources is covered in this course. A demonstration in designing an AWS CloudFormation template for resource provisioning is also covered.
Introduction to AWS Machine Learning Services
This course introduces Amazon Machine Learning and Artificial Intelligence tools that enable capabilities across frameworks and infrastructure, machine learning platforms, and API-driven services.
Introduction to AWS Organizations
This course introduces you to AWS Organizations, the service that offers policy-based management for multiple AWS accounts. We discuss key features and terminology, review how access and use the service, and provide a demonstration.
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