Advanced Disaster Recovery System in Cloud Infrastructure

Enterprise organizations increasingly require robust disaster recovery capabilities to maintain business continuity amid evolving operational threats and system disruptions. This comprehensive technical review presents the design and implementation of advanced disaster recovery systems leveraging leading cloud platforms, including Amazon Web Services and Microsoft Azure, integrated with sophisticated automation frameworks utilizing Python and PowerShell technologies. The proposed solution demonstrates automated data replication, backup operations, and failover mechanisms deployed across geographically distributed cloud regions to minimize downtime and prevent data loss during disaster scenarios. Implementation encompasses services such as Azure Site Recovery and AWS Disaster Recovery Service to orchestrate seamless workload transitions between primary and secondary environments through automated failover and failback procedures. Automation scripts developed in PowerShell and Python streamline recovery processes while embedding resilience into Infrastructure as Code deployments, significantly reducing manual intervention requirements and enhancing operational efficiency. A well-architectured multi-cloud disaster recovery reduces single points of failure and vendor lock-in risks while providing superior availability compared to traditional single-cloud deployments. Performance evaluation demonstrates substantial improvements in Recovery Time Objectives and Recovery Point Objectives compared to conventional disaster recovery implementations. Cost optimization strategies achieve significant reductions in capital expenditures while providing enhanced scalability and testing capabilities. Security frameworks incorporate comprehensive encryption protocols, role-based access controls, and regulatory compliance measures. Future directions explore artificial intelligence integration for predictive failure detection and edge computing disaster recovery scenarios, positioning organizations for enhanced resilience and competitive advantages through advanced cloud-based disaster recovery capabilities.

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Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-08-04
DOI
https://doi.org/10.32996/jcsts.2025.7.8.48
Primary Topic
Network Security and Intrusion Detection
Type
article
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article

Advanced Disaster Recovery System in Cloud Infrastructure

Sathish Kuppan Pandurangan
Journal of Computer Science and Technology Studies
Network Security and Intrusion Detection
article

Advanced Disaster Recovery System in Cloud Infrastructure

Sathish Kuppan Pandurangan
article en

Abstract

Enterprise organizations increasingly require robust disaster recovery capabilities to maintain business continuity amid evolving operational threats and system disruptions. This comprehensive technical review presents the design and implementation of advanced disaster recovery systems leveraging leading cloud platforms, including Amazon Web Services and Microsoft Azure, integrated with sophisticated automation frameworks utilizing Python and PowerShell technologies. The proposed solution demonstrates automated data replication, backup operations, and failover mechanisms deployed across geographically distributed cloud regions to minimize downtime and prevent data loss during disaster scenarios. Implementation encompasses services such as Azure Site Recovery and AWS Disaster Recovery Service to orchestrate seamless workload transitions between primary and secondary environments through automated failover and failback procedures. Automation scripts developed in PowerShell and Python streamline recovery processes while embedding resilience into Infrastructure as Code deployments, significantly reducing manual intervention requirements and enhancing operational efficiency. A well-architectured multi-cloud disaster recovery reduces single points of failure and vendor lock-in risks while providing superior availability compared to traditional single-cloud deployments. Performance evaluation demonstrates substantial improvements in Recovery Time Objectives and Recovery Point Objectives compared to conventional disaster recovery implementations. Cost optimization strategies achieve significant reductions in capital expenditures while providing enhanced scalability and testing capabilities. Security frameworks incorporate comprehensive encryption protocols, role-based access controls, and regulatory compliance measures. Future directions explore artificial intelligence integration for predictive failure detection and edge computing disaster recovery scenarios, positioning organizations for enhanced resilience and competitive advantages through advanced cloud-based disaster recovery capabilities.

Journal of Computer Science and Technology StudiesVol. 7(8)
University of Zurich (CH)
Openalex Percentile: Top 78%
Network Security and Intrusion Detection
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Advanced Disaster Recovery System in Cloud Infrastructure — Sathish Kuppan Pandurangan · Journal of Computer Science and Technology Studies (2025) | TGRS Research Map | TGRS