Improving system and software deployment on a large-scale cloud data center

In the cloud computing paradigm, the public cloud services provide end-users on-demand computational resources in a pay-as-you-go manner. Those computing resources are usually organized and located at one place, namely a cloud data center. As a cloud data center involves the issue of managing a large number of computing nodes, it requires a monitoring mechanism, which can observe the important events of each node as well classify the information, such that the system can use the mechanism to achieve automatic computing. In addition to the management issue, a cloud data center requires a fast cloud software deployment mechanism that facilitates establishment and management of various cloud services atop the cloud data center. In this study, we investigate three cloud OS deployment architectures to improve the deployment of Cloud OS. We describe how to design these architectures and use simulation tools to observe their performance values based on real observations. We also propose a mechanism based on Puppet to manage software installation and version control.