AI DRIVEN WBAN IN HEALTHCARE USING MACHINE LEARNING

Abstract

Organizations must implement robust disaster recovery (DR) strategies to ensure business continuity. Traditional DR solutions often rely on manual intervention, leading to delays in recovery and increased risk. Automated disaster recovery orchestration (ADRO) leverages Infrastructure-as-Code (IaC) frameworks to streamline failover, improve resilience, and optimize Recovery Point Objective (RPO) and Recovery Time Objective (RTO) thresholds. This paper evaluates key IaC frameworks—Terraform for state management, Ansible for playbook-driven service restoration, and AWS CloudFormation for infrastructure provisioning—in automating disaster recovery. Additionally, it explores the role of Chaos Engineering (using Gremlin) in stress-testing RPO/RTO thresholds and assessing real-time replication strategies with DRBD and Ceph. We analyze how these technologies collectively improve disaster recovery preparedness, minimize downtime, and enhance system resilience.