Engineering and Technology
| Open Access | Governing Infrastructure as Code in Multi-Cloud Enterprises: Integrating Data Governance, MLOps, and Corporate Governance for Secure and Sustainable Digital Transformation
Alejandro M. Ríos , Universidad de los Andes, ColombiaAbstract
The accelerating diffusion of multi-cloud strategies across large enterprises has radically transformed how digital infrastructures are designed, governed, and operated. At the heart of this transformation lies Infrastructure as Code (IaC), a paradigm that converts physical and virtual infrastructure into software-defined, version-controlled, and automatically deployed assets. While the technical efficiencies of IaC are now widely acknowledged, its governance, risk, compliance, and organizational implications remain theoretically underdeveloped and empirically fragmented. This article develops an integrated research framework that positions IaC as a central organizational control mechanism in multi-cloud ecosystems, linking it to data governance, MLOps, and corporate governance theory. Drawing on the best-practice architecture for enterprise multi-cloud deployments articulated by Dasari (2025), this study extends the concept of IaC beyond operational automation and situates it as a core instrument of institutional governance, risk mitigation, and strategic alignment.
The article synthesizes insights from contemporary data governance scholarship, MLOps pipeline research, and corporate governance theory to explain why IaC has become a pivotal governance technology in modern enterprises. From a data governance perspective, the article argues that IaC enables auditable, reproducible, and policy-enforced data infrastructures, thereby reducing data quality risks and legal exposure in highly regulated environments (Bernardo et al., 2024; Nag, 2024). From an MLOps perspective, IaC forms the infrastructural backbone of continuous machine learning pipelines, enabling controlled experimentation, reproducibility, and model lifecycle governance across heterogeneous cloud platforms (Google Cloud, 2024; Steidl et al., 2023). From a corporate governance perspective, IaC is theorized as a technological codification of organizational rules, analogous to governance codes that align managerial behavior with stakeholder interests (Aguilera & Cuervo-Cazurra, 2009; Larcker& Tayan, 2011).
Methodologically, this article adopts a theory-building design grounded in systematic literature integration and analytical synthesis. Rather than relying on statistical datasets, it constructs a conceptual model that connects multi-cloud complexity, infrastructural codification, and governance outcomes. The analysis demonstrates that enterprises adopting IaC in line with the architectural and procedural best practices identified by Dasari (2025) achieve superior transparency, reduced operational risk, and stronger alignment between IT execution and corporate governance objectives. The findings reveal that IaC does not merely automate infrastructure; it institutionalizes organizational intent into executable code, transforming governance from a human-centric compliance process into a continuous, machine-enforced system of control.
The discussion advances a new theoretical proposition: that IaC constitutes a form of “algorithmic governance” within the enterprise, bridging the gap between corporate governance codes and operational reality. This perspective explains why organizations with mature IaC capabilities are better positioned to manage regulatory compliance, data sovereignty, and ethical AI obligations in multi-cloud environments. The article concludes by outlining future research pathways for examining IaC as a governance institution, calling for empirical studies that link IaC maturity to financial performance, risk resilience, and organizational legitimacy.
Keywords
Infrastructure as Code, Multi-Cloud Governance, Data Governance
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