Virtualization is a key technology for enabling cloud computing. As we have read before, virtualizing applications and consolidating hardware reduces IT Infrastructure costs (which includes purchasing hardware and maintaining it), allowing easier management of resources and on-demand provisioning of resources in the data center. The Infrastructure as a Service (IaaS) model of the Cloud deals with provisioning of hardware, storage and networking resources. Virtualizing applications via the use of Virtual machines holds great significance in this model to deliver and manage IT services. The Virtualization lifecycle comprises a set of technical assessment activities which are governed by business and operational decisions. Technical assessment for virtualizing candidates revolves around meeting end-user Service Level Agreements (SLA's), reducing IT costs, and designing an optimized data center. Every phase in the virtualization lifecycle for cloud computing is highly challenging with a wide variety of complex open problems which are currently being tackled.
Analysis & Discovery : For the process of moving from Physical environments to Virtualized environments (P2V), solid analysis of the virtualization candidates must be performed. This stage involves discovering the data center entities (servers, networks, storage devices), collecting utilization profile data of those entities along the different dimensions (CPU, memory, network i/o, disk i/o). The main theme of P2V is to move applications from an under-utilized bare metal environment to a virtualized / hypervisor environment to enable optimum utilization of hardware. In addition to discovering the heavy artillery in the data centers, it is important to assess the applications deployed on them. The OS characteristics (scheduling policies, caching strategies etc), application characteristics and configurations (Tomcat no. of starting threads etc). Once the performance and application characteristics are assessed, capacity management models for the need to be developed to host those applications in the virtual environments. For more information on the technical assessment for virtualization, see 'Conduct a Technical Assessment for Server Virtualization'.
Implementing Models : Developing capacity models for a virtual environment is a tricky task since it is governed by other business and operational factors. Target SLA's (performance, availability ), power consumption levels are to be kept in mind along with the possible impacts of virtualization (hardware normalization, hypervisor overheads). The idea is to come up with a 'pre-VM placement' strategy which describes the 'footprints' of VM's.
VM Placement & Management : Allocating Virtual Machines to Physical Machines dynamically and optimally would be the goal of IT Enterprises. VM's can be scaled out/up on demand. Provisioning of VM's goes hand-in-hand with capacity management monitoring to track the desired Service Levels of applications. Server consolidation is an important and inherent part of this phase, as optimal placement of VM's across physical architectures is the key to meet the business goals. Re-shaping and re-sizing the footprints of VM's dynamically in real time is also a hot research topic. Management of VM's also involve migration to other physical hosts, monitoring performance which can be done centrally. Many open issues also exists in VM Migration, such as synchronization problems and security issues.
Thus, the virtualization life cycle poses many challenges and many groups in the Industry and Academia are grappling to solve these issues. If executed well, it has a promising future in the context of cloud computing. For more resources on Virtualization and Cloud Computing, see 'Virtualization / Cloud Computing Blogs, Websites, Resources, Articles'.
