SageMaker Pipelines automating machine learning workflows

Remember the correct answer, 'SageMaker Pipelines'.
・It defines and runs steps such as data preparation, training, evaluation, and deployment as an automated and reproducible workflow.
・Because the steps can be run the same way every time, it is the core of MLOps.
Feature Store (storing features), Data Wrangler (preprocessing), and JumpStart (model hub) are not pipelines that automate the entire workflow; they each relate to individual steps or resources.