SLA-driven planning and optimization of enterprise applications

We propose a model-based methodology to size and plan enterprise applications subject to Service Level Agreements (SLAs). Our approach is illustrated using a real-world Enterprise Resource Planning (ERP) application, namely SAP ERP. Firstly, we develop a closed queueing network model with finite capacity regions describing the SAP ERP application performance and show that this model is effective and robust in capturing measured response times and utilizations. Secondly, we propose an analytical cost model that jointly accounts for fixed hardware costs and dynamic operational costs related to power consumption. Based on the developed performance and cost models, we propose to use multi-objective optimization to find the Pareto-optimal solutions that describe the best trade-off solutions between conflicting performance and cost-saving goals. Experimental validation demonstrates the accuracy of the proposed models and shows that the attained Pareto-optimal solutions can be efficiently used by service providers for SLA-driven planning decisions, thus making a strong case in favor of the applicability of our methodology for deployment decisions subject to different SLA requirements.