Handling Virtual Machines in Cloud Computing Environment

Abstract

The IT infrastructure landscape has been completely transformed by cloud computing, which offers scalable, on-demand resources to satisfy the changing demands of contemporary applications. Virtualization plays a pivotal role in cloud systems by enabling the effective distribution of computing resources via Virtual Machines (VMs). To improve performance, scalability, and resource efficiency, this study explores the many opportunities and problems associated with Virtual Machine (VM) administration in cloud computing environments. To identify gaps in current procedures, our study starts with a detailed evaluation of current VM management approaches. We identify new trends, best practices, and important challenges in VM handling through a methodical analysis of the literature. Based on this basis, we suggest a new framework that aims to solve the problems encountered and improve cloud Virtual Machine (VM) management performance. To maximize virtual machine performance, the suggested framework combines sophisticated monitoring methods, dynamic workload balancing mechanisms, and intelligent resource allocation algorithms. It also uses orchestration and automation techniques to speed up the deployment and maintenance procedures. Strong isolation and protection mechanisms for Virtual Machines (VMs) in shared cloud infrastructures are prioritized. We carried out comprehensive tests in various cloud environments, evaluating resource usage, scalability, and performance metrics to verify the efficacy of our framework. The outcomes exhibit noteworthy advancements in comparison to conventional virtual machine management techniques, indicating the possibility of improving both financial viability and operational effectiveness. This study adds to our understanding of the difficulties associated with Virtual Machine (VM) management and offers a workable framework that not only solves present problems but also foresees future needs in the rapidly changing field of cloud computing. Our results are a useful reference for architects, developers, and administrators looking to optimize virtual machine handling for increased overall system performance and dependability as businesses depend more and more on cloud services.