Introducing software performance antipatterns in cloud computing environments: Does it help or hurt?

Abstract

Performance assessment of cloud-based big data applications require new methodologies and tools to take into consider- ation on one hand the volume, the variability and the com- plexity of big data, and on the other hand the intrinsic dy- namism of cloud environments. To this end, we introduce software performance antipatterns as reference knowledge to capture the well-known bad design practices that lead to software products sufiering by poor performance. This paper discusses some of the challenges and oppor- tunities of research while introducing software performance antipatterns in cloud computing environments. We present a model-based framework that makes use of software perfor- mance antipatterns to improve the Quality-of-Service (QoS) objectives of cloud-based big data applications.