Managing Shared Resource Pools for Enterprise Applications Diplom-Informatiker Univ.

In the past, data centers typically consisted of a small number of large mainframes, each hosting several application workloads. With the advent of distributed computing, new applications were assigned to their own smaller servers. Capacity planners often anticipated application demands years in advance and equipped each new server with sufficient capacity so that the workload could grow into it. However, the explosive growth in enterprise computing has led to server sprawl and today’s data centers are typically full of lightly utilized servers that incur greater management, facility, and power costs than necessary. Server virtualization technology now supports the creation of shared resource pools of servers. Applications can be dynamically consolidated onto servers in such pools thereby enabling a more efficient use of resources. However, there are challenges that must be overcome before such efficiencies can be achieved. There may be many workloads with differing demands; each physical server can only host a finite number of workloads; and, each workload has capacity requirements that may frequently change based on business needs. This thesis presents a comprehensive management approach for shared resource pools that helps to enable the efficient use of server resources while managing the resource acces