"AI-Augmented CI/CD: Leveraging Machine Learning to Optimize Build-Test-Deploy Cycles"

Abstract

Continuous Integration and Continuous Deployment (CI/CD) pipelines are essential to modern DevOps workflows, enabling rapid software delivery and iterative quality assurance. However,at scale, these pipelines face substantial challenges—high build queue times, redundant test executions, and suboptimal deployment policies. Recent studies highlight machine learning (ML) as a viable approach to optimize various stages in the CI/CD lifecycle.