Integrating AI-Powered Security into Multi-Cloud DevOps Environments: A Framework for Agile Development

Authors

  • Dr. Raju Dindigala Professor & Head Department of Mathematics, JB Institute of Engineering & Technology, India, 20122102india@gmail.com Author

Abstract

As organizations increasingly adopt multi-cloud environments for their operations, security has become a major concern, particularly within the scope of DevOps processes. The integration of AI-powered security tools in these environments can significantly enhance security posture and agility. This paper proposes a framework for incorporating AI-driven security into multi-cloud DevOps workflows to ensure seamless, real-time security threat detection and mitigation. The framework leverages machine learning (ML) models to provide proactive security measures, ensuring that DevOps teams can maintain agile development cycles while safeguarding against evolving threats. Key insights from studies like "Strengthening Cybersecurity in Edge Computing with Machine Learning" by Banik, Kothamali, and Dandyala et al. (2024), which evaluate ML models' effectiveness in edge computing environments, underscore the potential of these technologies for securing complex cloud infrastructures.

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Published

2024-12-09