Resilience Engineering in Distributed Cloud Architectures
DOI:
https://doi.org/10.58425/ijea.v2i1.355Keywords:
Resilience engineering, distributed cloud systems, fault tolerance, hybrid cloud strategies, AI-driven self-healing systemsAbstract
Aim: This study aims to evaluate the fundamental resilience engineering strategies in distributed cloud systems and explore their role in enhancing system availability, security, and fault tolerance. As businesses increasingly rely on geographically dispersed cloud infrastructures, ensuring continuous service delivery amid failures and cyber threats has become critical.
Methods: The research adopts a qualitative case analysis approach, complemented by a thorough literature review, to investigate key resilience practices such as redundancy, fault tolerance, proactive monitoring, and disaster recovery planning.
Results: The analysis reveals that integrating artificial intelligence (AI)-based identity and access management (IAM) tools and dynamic load balancing significantly improves system recovery performance, reduces downtime, and supports continuous availability of services. Additionally, the study finds that combining multi-cloud architectures with automated security mechanisms substantially strengthens cloud system robustness against localized failures and security breaches. These resilience strategies improve fault tolerance and support scalability and adaptive performance under changing workloads.
Conclusion: There is need for resilience engineering in the face of growing cloud adoption and system complexity.
Recommendations: Organizations should invest in hybrid cloud infrastructures and AI-driven self-healing capabilities to ensure long-term operational stability, data protection, and compliance in dynamic digital environments.
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