Today, AWS announced a new feature in SageMaker Pipelines, the ML workflow management service, to enable users run their desired steps in a pipeline as a sub-workflow. The new feature, called Selective Execution, allows you to run your selected steps in a pipeline while avoiding to rerun the entire pipeline. As a Data Scientist, Applied Scientist or an ML Engineer iterating on a pipeline for experimentation and deployment of ML models at scale, you can use this feature to initiate a pipeline execution on your desired steps and save hours of processing time, and simplify managing the code used for executions.
Source:: Amazon AWS