Analysis of SaaS Business Platform Workloads for Sizing and Collocation

Sharing of physical infrastructure using virtualization presents an opportunity to improve the overall resource utilization. It is extremely important for a Software as a Service (SaaS) provider to understand the characteristics of the business application workload in order to size and place the virtual machine (VM) containing the application. A typical business application has a multi-tier architecture and the application workload is often predictable. Using the knowledge of the application architecture and statistical analysis of the workload, one can obtain an appropriate capacity and a good placement strategy for the corresponding VM. In this paper we propose a tool iCirrus-WoP that determines VM capacity and VM collocation possibilities for a given set of application workloads. We perform an empirical analysis of the approach on a set of business application workloads obtained from geographically distributed data centers. The iCirrus-WoP tool determines the fixed reserved capacity and a shared capacity of a VM which it can share with another collocated VM. Based on the workload variation, the tool determines if the VM should be statically allocated or needs a dynamic placement. To determine the collocation possibility, iCirrus-WoP performs a peak utilization analysis of the workloads. The empirical analysis reveals the possibility of collocating applications running in different time-zones. The VM capacity that the tool recommends, show a possibility of improving the overall utilization of the infrastructure by more than 70% if they are appropriately collocated.