Capacity Planning in Virtualised Environments Using Model Driven Engineering

Capacity planning is an important activity in computing for optimising resource usage while avoiding performance degradation. The demand for computing resources is triggered by application workloads running on virtual or physical machines. With today's technology, resource scalability can be achieved through server virtualisation, by having scalable virtual machines running on a physical server. However, these scalable virtual resources run on limited physical resources, especially in small to medium scale data centres. The management of virtual and physical resources impacts upon application performance and introduces a cost for all parties. There is a need to measure the virtual and physical resource requirements in facilitating cost-effective capacity planning. This research identifies three main management phases for a capacity planning process for a data centre implementing server virtualisation: capturing application workloads, managing virtual resources and managing physical resources. This research proposes an approach that leverages domain specific modelling and model transformation to estimate resource requirements based on predicted application workloads for certain time periods. Model-Driven Engineering (MDE) was utilised to automate the identified process. A transparent, automated and repeatable MDE process for generating predictions for resource usage from workload models and sets of Domain Specific Modelling Languages (DSMLs) that allow resource and workloads logs as well as predicted workloads to be precisely captured using models were designed, implemented and evaluated with case studies. The MDE process exploits model transformation, comparison and merging, is modularised so that it can be configured for different kinds of capacity planning applications and technical infrastructures.