Authors: Manoj K. Lama
Abstract: The growing reliance on cloud infrastructure has introduced unprecedented complexity in managing regulatory compliance, as organizations operate across multiple environments, jurisdictions, and service models. Traditional manual compliance methods struggle to keep pace with continuous integration and deployment cycles, leaving enterprises vulnerable to misconfigurations and regulatory breaches. Autonomous Policy Engines (APEs) have emerged as intelligent automation frameworks that enforce compliance dynamically by interpreting, monitoring, and executing policies in real time. These systems leverage rule-based logic, artificial intelligence (AI), and policy-as-code paradigms to ensure that every cloud resource adheres to internal and external standards without manual oversight. This review article explores the architectural foundation, functional mechanisms, and practical implications of APEs in achieving continuous compliance across hybrid and multi-cloud ecosystems. It examines their integration with DevOps pipelines, orchestration tools, and Infrastructure-as-Code frameworks, and evaluates their ability to reduce compliance risk, improve audit readiness, and streamline governance. Additionally, the paper discusses the limitations and challenges of deploying autonomous engines, including issues of policy complexity, explainability, and integration with legacy infrastructure. Finally, it identifies future research directions such as AI-driven predictive compliance, intent-based policy models, and blockchain-enhanced auditing systems. Through this comprehensive review, the article highlights how autonomous policy engines transform cloud compliance from a reactive audit-driven process into a proactive, intelligent, and self-sustaining governance model.
DOI: http://doi.org/10.5281/zenodo.17882727
