CDA: A Cloud Dependability Analysis Framework for Characterizing System Dependability in Cloud Computing Infrastructures

Cloud computing has become increasingly popular by obviating the need for users to own and maintain complex computing infrastructure. However, due to their inherent complexity and large scale, production cloud computing systems are prone to various runtime problems caused by hardware and software failures. Dependability assurance is crucial for building sustainable cloud computing services. Although many techniques have been proposed to analyze and enhance reliability of distributed systems, there is little work on understanding the dependability of cloud computing environments. As virtualization has been an enabling technology for the cloud, it is imperative to investigate the impact of virtualization on the cloud dependability, which is the focus of this work. In this paper, we present a cloud dependability analysis (CDA) framework with mechanisms to characterize failure behavior in cloud computing infrastructures. We design the failure-metric DAGs (directed a cyclic graph) to analyze the correlation of various performance metrics with failure events in virtualized and non-virtualized systems. We study multiple types of failures. By comparing the generated DAGs in the two environments, we gain insight into the impact of virtualization on the cloud dependability. This paper is the first attempt to study this crucial issue. In addition, we exploit the identified metrics for failure detection. Experimental results from an on-campus cloud computing test bed show that our approach can achieve high detection accuracy while using a small number of performance metrics.