SECURITY-ENHANCED AI-ASSISTED AUTOMATED SOFTWARE DEPLOYMENT USING CI/CD, CONTAINERIZATION, AND DEVSECOPS INTEGRATION

Abstract

This paper presents a security-enhanced, AI-assisted automated software deployment framework that combines CI/CD practices, containerization, Kubernetes orchestration, and DevSecOps integration. The proposed system automates the build, test, and deployment pipeline while embedding security checks at multiple stages through static code analysis, dependency scanning, image vulnerability assessment, and configuration validation. In addition, an AI-assisted monitoring component analyzes runtime metrics and error patterns to support early detection of anomalies and recommends rollback actions when deployments deviate from expected behavior. The framework is implemented using Git-based version control, a CI server, Docker images, and Kubernetes-based staging and production environments. Experimental evaluation comparing the traditional manual approach and the proposed pipeline shows significant reductions in deployment time and failure rate, along with higher test pass rates, improved vulnerability detection, and faster recovery from faults. The results indicate that integrating AI-driven analysis with security-aware CI/CD automation provides a more reliable, efficient, and secure deployment process suitable for modern large-scale software systems.