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@article{183286,
        author = {Divyesh Pradeep Shah},
        title = {Real-World Implementation of Disaster Recovery in AWS: Reducing Downtime Below 1%},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {3},
        pages = {1578-1585},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=183286},
        abstract = {In the era of always-on digital services, reducing system downtime has become a critical performance metric for enterprises operating in the cloud. This review explores the real-world implementation of disaster recovery (DR) strategies in Amazon Web Services (AWS), with a particular focus on reducing annual downtime below 1%. Through a synthesis of recent case studies, emerging technologies, and scholarly research, we analyze the evolution of DR architectures from manual failover systems to intelligent, autonomous models that leverage real-time telemetry, AI-based orchestration, and serverless automation. The paper introduces a novel, AI-assisted DR model that integrates multi-source monitoring, predictive analytics, and event-driven recovery workflows to achieve consistent recovery time objectives (RTOs) under two minutes and availability levels exceeding 99.5%. Comparative analysis against baseline models demonstrates significant gains in predictive accuracy, system adaptability, and operational resilience. This review provides valuable insights for researchers, cloud practitioners, and policymakers aiming to build more robust, scalable, and cost-effective DR systems—especially in high-growth regions such as India. By addressing existing gaps and proposing a resilient framework, this paper contributes toward the realization of fully autonomous disaster recovery systems in cloud-native environments.},
        keywords = {Disaster Recovery, AWS, Cloud Resilience, High Availability, Autonomous Recovery, Machine Learning, Infrastructure-as-Code, Serverless, Downtime Reduction, Predictive Analytics, Real-Time Orchestration, Multi-Cloud, Resilient Architecture.},
        month = {August},
        }