Architecting Operational Resilience in Cloud-Native and Cyber-Physical Systems: Integrating Chaos Engineering, Redundancy Design, Bayesian Modeling, and Reactive Execution Frameworks

Abstract

Operational resilience has emerged as a defining requirement for cloud-native infrastructures, microservices ecosystems, distributed artificial intelligence platforms, and cyber-physical systems. As critical infrastructure processes migrate toward highly virtualized, containerized, and decentralized architectures, traditional reliability engineering approaches are insufficient to capture dynamic interdependencies, adversarial threats, and systemic cascading failures. This research develops an integrative theoretical framework for operational resilience grounded strictly in established literature on chaos engineering, resilience engineering in cloud offerings, Bayesian network modeling of infrastructure resilience, redundancy allocation strategies, process resilience analysis, reactive execution models, and adversarial resilience in communication networks. The study synthesizes principles from chaos experimentation in digital twins and cyber-physical systems, microservices fault tolerance design, redundancy theory in mechanical and communication systems, and resilience-based supplier and infrastructure modeling. Methodologically, the research constructs a layered conceptual model linking proactive disruption testing, redundancy structuring, probabilistic dependency mapping, and reactive operational orchestration. Findings indicate that operational resilience in cloud-native and cyber-physical environments emerges from the interplay between controlled fault injection, probabilistic interdependency awareness, strategic redundancy allocation, and adaptive execution models. The discussion elaborates theoretical implications for distributed AI resilience, microservices orchestration, and critical infrastructure protection, highlighting limitations related to model complexity, adversarial unpredictability, and cost constraints. The study concludes that integrating chaos engineering with Bayesian resilience modeling and redundancy optimization offers a comprehensive paradigm for resilient digital and cyber-physical infrastructures in high-volume operational environments.