Question

A machine learning platform team wants to define their SageMaker infrastructure (endpoints, endpoint configs, and IAM roles) as code. The team is composed of Python developers who want to use loops, conditionals, and reusable classes to generate the infrastructure definitions, while still deploying through AWS's native provisioning and rollback engine. Which approach best meets these requirements?

Accepted Answer

Author AWS CDK stacks in Python, which synthesize into CloudFormation templates for deployment

Answer

Write raw CloudFormation templates in YAML and manually parameterize them for each resource

Answer

Use the AWS CLI in a shell script to create endpoints imperatively at deploy time

Answer

Use Terraform with the AWS provider to manage all SageMaker resources