Abstract

Virtualization technology is the underlying element of cloud computing. Traditionally, cloud computing has employed virtual machines to distribute available resources and provide isolated environments among users. Multiple virtual machines, with their own operating system and services, can be deployed and run simultaneously on the same physical machine on the cloud infrastructure. Recently, a more lightweight virtualization technology is being rapidly adopted and it is based on containers. A key difference between virtual machines and containers, is that containers share the same underlying operating system.In this work, we studied the combination of these two virtualization technologies by running containers on top of virtual machines. This synergy aims to enhance containers’ main drawback, which is isolation and, among others, to simplify the system management and upgrade, and to introduce the new functionalities of containerized applications to virtual machines. The benefits of this method have been recognized by big cloud companies, which have been employing this approach for years.With this paper, we aimed to present the advantages of running containers on virtual machines and to explore how various virtualization techniques and configurations affect the performance of this method. Although, in bibliography there are a few papers that used this method partially to conduct experiments, there is not any research which considers this method from our integral aspect of view. In this study, we ran Docker containers and evaluated their performances, not only on KVM and XEN virtual machines, but also we ran Linux containers on Windows Server. We adopted an empirical approach, to quantify the performance overhead introduced by the additional virtualization layer of virtual machines, by executing various benchmarks and deploying real world applications as use cases. Furthermore, we presented for first time, how isolation is applied on virtual machines and containers, we evaluated different operating systems optimized to host containers, mechanisms of storing persistent data and, last but not least, we experimentally quantified the power and energy consumption overhead of containers running on virtual machines.

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