Adaptive Secure DevOps Architectures for Cloud Native Retail Platforms Under Regulatory and Resilience Pressures

Abstract

The rapid digitalization of the global retail sector has produced unprecedented dependence on cloud native infrastructures, continuous delivery pipelines, and data driven personalization systems. While these transformations have created new efficiencies and competitive advantages, they have simultaneously introduced complex security, compliance, and resilience challenges that traditional software engineering and governance frameworks struggle to address. Secure DevOps, or DevSecOps, has emerged as a promising paradigm to integrate security into every stage of the software development and operational lifecycle, yet empirical and theoretical research remains fragmented, particularly in the context of highly regulated, data intensive retail cloud environments. This article develops a comprehensive and integrative theoretical framework for adaptive secure DevOps in retail cloud platforms, drawing on interdisciplinary scholarship from software engineering, cybersecurity governance, chaos engineering, risk management, and information systems. Central to the analysis is the argument that retail cloud ecosystems represent a unique socio technical system characterized by volatile demand, regulatory scrutiny, and continuous exposure to adversarial threats, which necessitates not only automation and security tooling but also organizational learning, cognitive risk modeling, and resilience engineering. The work builds on recent advances in secure DevOps practices in retail cloud environments as articulated by Gangula (2025), situating them within broader theoretical debates about digital transformation, platform governance, and cyber resilience. Through an extensive qualitative synthesis of the literature, this study identifies critical dimensions of effective secure DevOps adoption, including governance alignment, pipeline security, container hardening, chaos based testing, zero trust secret management, and continuous compliance validation. Methodologically, the research employs a structured interpretive synthesis combined with a Delphi informed expert modeling approach to derive conceptual constructs and causal relationships that explain why some retail organizations achieve sustained security and reliability while others remain vulnerable despite heavy technological investment. The results reveal that security outcomes are less dependent on individual tools and more on the coherence of institutional structures, feedback loops, and adaptive capabilities embedded within DevOps pipelines. The discussion elaborates on the implications of these findings for theory and practice, highlighting tensions between speed and control, innovation and compliance, and automation and human judgment. By articulating a unified framework of adaptive secure DevOps for retail cloud systems, this article contributes to both academic scholarship and managerial practice, offering a foundation for future empirical research and strategic decision making in one of the most dynamic and risk sensitive sectors of the digital economy.