Capacity Planning of Cloud Computing Workloads

Abstract

Cloud computing enables the shared use of computing resources, with costs determined by operational cycles. Given the technical and financial constraints of cloud computing projects, capacity planning processes help identify the need for resources for a given workload so that it functions properly in different contexts. The current industrial paradigm considers historical usage precedents for capacity planning. In addition, current practices do not establish how accurate these plans are. This thesis aims to establish a framework for capacity planning of cloud computing workloads, which includes an architectural meta-model, specification of cloud architecture components based on a subset of non-functional parameters, and abstract classes of resource sizing correlated with computational demand and desired capacity.

Keywords: Cloud Capacity Planning, Cloud Computing, Capacity Planning