Local Disaster Recovery Using Virtualization Technology

Abstract

Business applications running on IT infrastructure necessitate high levels of availability in order to minimize the amount of downtime experienced during any planned and unplanned outages. As a result, disaster recovery has gained great significance in IT. Exploiting virtualization and ability to automatically reinstall a host, where the action on a virtual machine is performed only when a disaster occurs. Virtualization affords significant cost and performance advantages over more traditional disaster recovery options such as tape backup or imaging. Our approach is to design and implement a continual migration strategy for virtual machines to achieve automatic failure recovery. By continually and transparently propagating virtual machine’s state to a backup host via live migration techniques, trivial applications encapsulated in the virtual machine can be recovered from hardware failures with minimal downtime while no modifications are required. Moreover, our framework intends to monitor virtual machines for problems such as CPU utilization, I/O activity, and memory utilization. This raises a difficult problem, since it is quite difficult to discriminate based on these measures between a virtual object that is performing properly, and one that is quite ill. We apply the out-of-band monitoring using virtualization and machine learning can accurately identify faults in the guest OS, while avoiding the many pitfalls associated with in-band monitoring.