Lorrie A. Tomek

Using virtualization for high availability and disaster recovery

Traditional high-availability and disaster recovery solutions require proprietary hardware, complex configurations, applicationspecific logic, highly skilled personnel, and a rigorous and lengthy testing process. The resulting high costs have limited their adoption to environments with the most critical applications. However, high availability and disaster recovery are becoming increasingly important in many environments that cannot bear the complexity and the expense involved. In this paper, we show that virtualization can be used to develop solutions that meet this market demand. We describe the recently released Virtual Availability Manager (VAM) product offering, which provides simplified availability solutions using Xent-based virtualization, and which is available as part of the IBM Systems Director product. We present key design principles of VAM, explain its architecture and current capabilities, and describe the way it is being extended to enable recovery in case of disaster.

A virtual resource placement service

Server, storage, and network virtualization and the growing adoption of cloud computing has expanded both the complexity and the value of intelligent allocation and management of data center resources. Resource allocation in a cloud environment is of fundamental importance. There are many competing goals, with differing priorities, that contribute to optimizing virtual resource allocation and placement including performance, reliability, security, energy, etc. We have developed an open extensible architecture to provide placement recommendations which allows for different independently developed Domain Managers to provide input/advice on placement. We have further developed the means to orchestrate the placement, ensuring that the required configuration actions be enacted both before and after the migration of the virtual machine. This paper explores the topic of providing a core placement calculation and orchestration architecture to facilitate management of workload demands in a cloud environment. We describe this architecture for placement services and orchestration, and present some results from a prototype implementation.