Snooze: A Scalable and Autonomic Cloud Management System

Abstract : With the advent of cloud computing and the need to satisfy growing customers resource demands, cloud providers now operate increasing amounts of large data centers. In order to ease the creation of private clouds, several open source and commercial Infrastructure-as-a- Service cloud management frameworks have been proposed during the past years. However, all these systems are either highly centralized or have limited fault tolerance support. Consequently, they all share common drawbacks: scalability and Single Point of Failure. In this paper, we present the design, implementation and evaluation of a novel scalable and autonomic virtual machine (VM) management framework called Snooze. For scalability the system utilizes a self-configuring hierarchical architecture and performs distributed VM management. Moreover, fault tolerance is provided at all levels of the hierarchy, thus allowing the system to self-heal in the event of failures. Our large-scale evaluation conducted across multiple geographically distributed clusters of the Grid’5000 experimentation testbed shows that the system scales to over ten thousand system services and can easily manage hundreds of VMs. Moreover, it is robust enough to automatically recover the hierarchy in the event of thousands of concurrent system services failures.
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Submitted on : Monday, December 8, 2014 - 3:25:30 PM
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Eugen Feller, Matthieu Simonin, Yvon Jégou, Anne-Cécile Orgerie, David Margery, et al.. Snooze: A Scalable and Autonomic Cloud Management System. [Research Report] RR-8649, Inria Rennes; INRIA. 2014, pp.31. ⟨hal-01091755⟩

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