In this rapidly growing digital era, development for cloud computing disaster recovery, a revolutionary approach combining artificial intelligence with Kubernetes container orchestration has achieved remarkable system reliability and cost efficiency improvements. The research, published in the International Journal of Computer Engineering and Technology by Varun Tamminedi, demonstrates significant advancements in protecting cloud infrastructure from failures and outages in modern computing environments.
Smart Systems, Faster Recovery The innovative framework leverages deep learning-based predictive analytics and automated recovery mechanisms to enhance system resilience. By implementing intelligent resource optimization algorithms, the system achieved a 73% reduction in Recovery Time Objective (RTO). It maintained Recovery Point Objective (RPO) under 10 seconds for critical workloads, ensuring maximum business continuity for enterprises.
Preventing Failures Before They HappenThe hybrid AI approach, combining supervised and unsupervised learning techniques, demonstrated 89% accuracy in failure prediction with a 15-minute warning window. This predictive capability, coupled with automated response mechanisms, resulted in a 94% reduction in false positive failure predictions and …