Cloud computing has become a fundamental technology for Higher Education Institutions (HEIs), supporting teaching, research, learning management, student services, and administrative operations. As institutional dependence on cloud platforms increases, ensuring cloud resilience has become essential for maintaining service continuity during cyberattacks, infrastructure failures, configuration errors, network disruptions, and large-scale disasters. Unlike traditional dependability approaches that primarily emphasize reliability and availability, cloud resilience focuses on anticipating, withstanding, recovering from, and adapting to disruptions while maintaining acceptable service performance. This review presents a comprehensive analysis of cloud resilience from architectural, operational, and evaluation perspectives. It examines the conceptual foundations of resilience, cloud architecture frameworks, resilience mechanisms, failure characteristics, fault models, and widely adopted resilience evaluation metrics. The paper further reviews architectural techniques including redundancy, replication, load balancing, autoscaling, checkpointing, self-healing, container orchestration, and microservices, together with emerging practices such as chaos engineering, AI-driven resilience management, cyber resilience, and multi-cloud architectures. The review also identifies current research challenges involving interoperability, scalability, security, resilience evaluation, autonomous recovery, and edge-cloud environments. In addition, it highlights future research directions centered on intelligent resilience, predictive analytics, standardized evaluation frameworks, and adaptive cloud-native architectures. By synthesizing recent advances and identifying research gaps, this paper provides researchers and practitioners with a structured understanding of cloud resilience and offers practical guidance for designing resilient cloud infrastructures that sustain critical educational and research services in Higher Education Institutions.
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