Development of a Predictive VM Provisioning in a Cloud Environment

In contemporary virtualized data center environments, efficient resource allocation in virtualized data center environments is crucial for preventing server downtimes. This paper introduces a method to mitigate resource exhaustion on ESXi servers using predictive analytics. Leveraging historical workload data, the proposed approach forecasts potential resource saturation events by analyzing past usage patterns. A proactive provisioning mechanism is outlined to deploy virtual machines (VMs) onto new ESXi servers during predicted high-load intervals. This preemptive strategy strategically distributes workloads, averting server downtime and ensuring optimal resource utilization. Experimental results validate the effectiveness of the proposed method in improving the dependability and security of ESXi servers in virtualized environments and out performs better than other state-of-arts. The proposed method is implemented using ESXi host client and the result shows effective performance and improved stability of the overall system.