Evaluating Adaptation Methods for Cloud Applications: An Empirical Study
Marios Fokaefs, Yar Rouf, Cornel Barna, Marin Litoiu · 2017
Web software systems generally reside in highly volatile environments, their incoming traffic may be subject to sharp fluctuations from reasons that cannot always be captured or predicted. Cloud computing provides a solution to this problem by offering flexible resources, like containers, which can be quickly and easily scaled according to the current workload needs. Automating this process is a key aspect for the management of modern web software systems, and there is a plethora of methods to implement autonomic management systems. In this work, we review three of these methods, a threshold-based approach, a control-based approach and a model-based approach. We design and run a number of experiments for all three systems with different workloads to evaluate their ability to manage the software system and how well they do so. Our experiments were conducted on the Amazon EC2 cloud with Docker containers.