Dynamic automation of selection of pipeline artifacts

A computer program product to support a continuous integration and continuous deployment (CI/CD) pipeline for software development and operations (DevOps), the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a processor to:

• generate one or more dependency graphs based on two or more application artifacts;
• employ a machine learning (ML) model to capture a relationship between the one or more dependency graphs and one or more pipeline artifacts;
• detect a change to the one or more application artifacts, and responsive to the detected change the ML model to:
• leverage the captured relationship to identify impact of the detected change on the one or more pipeline artifacts;
• and
• selectively optimize the pipeline responsive to the identified impact, the optimization including automatic encoding mapped changes corresponding to the identified impact into the pipeline;
• and
• execute the optimized pipeline.

A method comprising:

• generating one or more dependency graphs based on two or more application artifacts;
• employing a machine learning (ML) model to capture a relationship between dependency graphs and one or more pipeline artifacts;
• detecting a change to one or more of the application artifacts, and responsive to the detected change the ML model:
• leveraging the captured relationship to identify impact of the detected change on the one or more pipeline artifacts;
• and
• selectively optimizing a continuous integration and continuous deployment (CI/CD) pipeline responsive to the identified impact, the optimization including automatically encoding mapped changes corresponding to the identified impact into the pipeline;
• and
• executing the optimized pipeline.