Cloud computing has emerged as a new and alternative approach for providing computing services. Customers acquire and release resources by requesting and returning virtual machines to the cloud. Different service models and pricing schemes are offered by cloud service providers. This can make it difficult for customers to compare cloud services and select an appropriate solution. Cloud Infrastructure-as-a-Service vendors offer a t-shirt approach for Virtual Machines (VMs) on demand. Customers can select from a set of fixed size VMs and vary the number of VMs as their demands change. Private clouds often offer another alternative, called time-sharing, where the capacity of each VM is permitted to change dynamically. With this approach each virtual machine is allocated a dynamic amount of CPU and memory resources over time to better utilize available resources. We present a tool that can help customers make informed decisions about which approach works most efficiently for their workloads in aggregate and for each workload separately. A case study using data from an enterprise customer with 312 workloads demonstrates the use of the tool. It shows that for the given set of workloads the t-shirt model requires almost twice the number of physical servers as the time share model. The costs for such infrastructure must ultimately be passed on to the customer in terms of monetary costs or performance risks. We conclude that private and public clouds should consider offering both resource sharing models to meet the needs of customers.
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