A SageMaker Pipeline is composed of ‘steps’. You can choose any of the natively supported step types to compose a workflow that invokes various SageMaker features (eg. training, evaluation) or other AWS services (eg. EMR, Lambda). You can also lift-and-shift your existing ML Python code into SageMaker Pipeline by either using the ‘@step’ python decorator or adding entire python Notebooks as components of the Pipeline. For additional details, please refer to the SageMaker Pipelines developer guide.