DevOps: Practices, Metrics, Security, and Emerging Trends

Abstract

DevOps, the set of practices and cultural principles that unify software development and IT operations, has matured from a grassroots movement into a formally measured engineering discipline. This paper surveys the current state of DevOps: its continuous lifecycle and toolchain, the DORA (DevOps Research and Assessment) metrics used to benchmark software delivery performance, the rise of platform engineering and internal developer platforms, the adoption of GitOps for declarative infrastructure management, and the integration of security into the delivery pipeline through DevSecOps. It reviews the growing role of artificial intelligence across the DevOps lifecycle, from AI-assisted coding to predictive pipeline automation, and the emerging evidence that AI adoption is decoupling delivery speed from delivery stability. The paper includes three original figures illustrating the DevOps lifecycle, a DevSecOps-integrated CI/CD pipeline, and a comparison of DORA performance tiers, and closes with a discussion of open challenges, including tool sprawl, the platform engineering skills gap, and the measurement difficulties introduced by AI-assisted development