Predictive Model for Dynamically Provisioning Resources in Multi-Tier Web Applications

Abstract

In the competitive world of modern web applications, performance plays a crucial role. An e-commerce company estimated that every 100ms delay reduces sales by 1 percent, and a popular search engine reported that every 500ms delay in search reduces earnings by 20 percent. The demands from users for these services can vary widely based on factors such as the time-of-day and unexpected events that can trigger flash crowds. To meet these demands web applications can be organized using a multi-tier architecture to make them modular and scalable in a cloud environment. However, a highly dynamic workload and different types of resource requirements in each tier can make it difficult to model the behavior of these applications. This presents two significant challenges to infrastructure providers: 1) to model the behavior of an application workload and provide responsive resources using dynamic resource provisioning, and 2) to maintain performance-based (response time) Service Level Agreements (SLAs). In this paper, we formulate a convex optimization problem for resource allocation, and offer a strict SLA for performance. We adopt an SLA violation cost model to formulate our optimization problem and derive the solution for dynamic resource provisioning. To achieve a strict SLA for the response time of an application, we propose a predictive model that seeks to dynamically provision resources using a Feedback-based Control System (FCS). Our model is applicable for a broad range of multi-tier applications. We demonstrate the effective use of our model through experiments that analyze the behavior of an online auction application using a common workload benchmark.