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Integrating Generative Artificial Intelligence into Cloud-Based Layered System Architectures: Security, Automation, and DevOps Perspectives

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  • Madhu Babu Amarappalli

Abstract

The rapid advancement of Generative Artificial Intelligence (GenAI) has significantly transformed modern software systems, particularly within cloud-based environments. Integrating GenAI into layered system architecture introduces new opportunities for automation, scalability, and intelligent decision-making, while simultaneously presenting challenges related to security, privacy, system reliability, and operational governance. This paper explores a comprehensive framework for embedding generative AI models into cloud based layered architectures, emphasizing automation through Agile DevOps and CI/CD pipelines, robust test engineering practices, and security-by-design principles. Additionally, the study highlights the role of technical leadership in managing complexity through consensus building, negotiation, and de-escalation while maintaining open, inclusive, and engaging engineering environments. By synthesizing architectural, operational, and leadership perspectives, this paper provides a holistic approach for designing, deploying, and managing secure and scalable generative AI systems in modern cloud infrastructures.

Suggested Citation

  • Madhu Babu Amarappalli, 2024. "Integrating Generative Artificial Intelligence into Cloud-Based Layered System Architectures: Security, Automation, and DevOps Perspectives," International Journal of Scientific Research in Science, Engineering and Technology, Technoscience Academy, vol. 11(3), pages 683-698, May.
    • Handle: RePEc:ijs:ijsrse:v11:y2024:i3:id:830
    DOI: 10.32628/IJSRSET2414888
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