Reliability engineering frameworks for large-scale cloud platforms: A review of practices in the United States

In the United States, the rapid evolution of cloud computing in the United States has elevated reliability engineering to a strategic requirement continuity, performance, and trust in large-scale digital systems. Cloud ecosystems today are defined by distributed microservices, multi-cloud deployments and dynamic scalability, which combine to raise the complexity of architecture and operational instability. The ongoing failure of core U.S. platforms points to the underlying vulnerability and the prohibitive nature of service failure when it comes to cloud-reliant services. This narrative review takes an integrative method to combine academic and industry literature about the cloud-native period in the United States through thematic analysis to track the development of the reliability paradigms. Results show that there is a transition between hardware-based redundancies to distributed system reliability and then to cloud-native resilience that is motivated by automation and continuous delivery methods. The main challenges are trade-offs between reliability and scalability, the growing complexity of the system, observability constraints, human factors, optimization of costs, and the difficulties in coordinating across multi-clouds. In order to fill these gaps, this study proposes the Unified Adaptive Cloud Resilience Framework (UACRF), a multi-layer, adaptive model that integrates monitoring, failure testing, automated recovery, and governance across infrastructure, platform, application, and operational layers. This framework offers a reference model of scalable, resilient, and adaptable cloud systems.