AI and Automation in DevOps: A New Paradigm for Accelerating Software Development and Deployment

Abstract

In recent years, artificial intelligence (AI) and automation have become integral components of the DevOps framework, revolutionizing software development and deployment processes. The convergence of AI and automation in DevOps enables faster, more efficient, and highly reliable software delivery cycles. This paper explores how AI technologies such as machine learning (ML) and natural language processing (NLP) are enhancing automation in DevOps practices, optimizing processes like continuous integration/continuous delivery (CI/CD), monitoring, and testing. Moreover, the paper leverages insights from the study “Feature Engineering for Effective Threat Detection” by Kothamali et al. (2021), where feature engineering techniques are applied to improve cybersecurity models. This approach has significant implications for building automated security measures within DevOps pipelines. By examining use cases, challenges, and future trends, this paper highlights the emerging paradigm shift in DevOps towards AI-driven automation.