Applying Computational Intelligence for enhancing the dependability of multi-cloud systems using Docker Swarm

Abstract

Multi-cloud systems have been gaining popularity due to the several benefits of the multi-cloud infrastructure such as lower level of vendor lock-in and minimize the risk of widespread data loss or downtime. Thus, the multi-cloud infrastructure enhances the dependability of the cloud-based system. However, it also poses many challenges such as nonstandard and inherent complexity due to different technologies, interfaces, and services. Consequently, it is a challenging task to design multi-cloud dependable systems. Virtualization is the key technology employed in the development of cloud-based systems. Docker has recently introduced its container-based virtualization technology for the development of software systems. It has newly launched a distributed system development tool called Swarm, which allows the development of a cluster of multiple Swarm nodes on multiple clouds. Docker Swarm has also incorporated several dependability attributes to support the development of a multi-cloud dependable system. However, making Swarm cluster always available requires minimum three active manager nodes which can safeguard one failure. This essential condition for the dependability is one of the main limitations because if two manager nodes fail suddenly due to the failure of their hosts, then Swarm cluster cannot be made available for routine operations. Therefore, this paper proposes an intuitive approach based on Computational Intelligence (CI) for enhancing its dependability. The proposed CI-based approach predicts the possible failure of the host of a manager node by observing its abnormal behaviour. Thus, this indication can automatically trigger the process of creating a new manager node or promoting an existing node as a manager for enhancing the dependability of Docker Swarm.