Capacity Expansion with a Bundled Supply of Attributes An Application to Cloud Computing
Application to Cloud Computing Over the past decade, technological enhancements led by the rise in cloud computing have revolutionized the IT industry. Cloud computing is on demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. In recent years, we have witnessed a rapid growth in the cloud computing industry (Gartner Press Release 2017) represented by cloud service providers. For cloud providers, such a huge surge in demand for cloud services has created a challenging problem about how to manage their capacity efficiently. Capacity in cloud computing is usually defined by demand for resources. The key resources in the cloud computing industry, referred to as attributes of capacities, are Central Processing Unit (CPU) Random Access Memory (RAM) Network, and Storage. All of these attributes agglomerated in data centers are the hardware infrastructure of cloud services; as demand grows over time, these attributes can potentially become the capacity bottleneck. In the case of a shortage in Storage or Network, capacities of these two attributes can be scaled up individually. Therefore, single resource capacity expansion models can be applied. In contrast, the capacity expansion of RAM and CPU is handled through the acquisition of new servers, which increases both attributes' capacities simultaneously and, depending on the server configuration, increases the fixed ratio of CPU to RAM. Addressing the capacity expansion problems of these two attributes by employment of new servers, instead of individual scaling, occurs primarily for the following two reasons: first, the actual cost of individual scaling, including not only the cost of purchasing new CPU or RAM, but also the cost associated with the old server shut down during upgrading, is exorbitant; second, old server technologies may not be compatible with newer CPU and RAM technologies, making individual scaling of CPU or RAM capacities cumbersome. However, acquisition of new servers to address capacity issues of RAM and CPU poses challenges that not only stem from rapid demand growths of these attributes, but also from the way the supply