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Seagull: Intelligent Cloud Bursting for Enterprise Applications
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Tian Guo and Upendra Sharma, UMASS Amherst; Timothy Wood, The George Washington University; Sambit Sahu, IBM Watson; Prashant Shenoy, UMASS Amherst
Enterprises with existing IT infrastructure are beginning to employ a hybrid cloud model where the enterprise uses its own private resources for the majority of its computing, but then “bursts” into the cloud when local resources are insufficient. However, current approaches to cloud bursting cannot be effectively automated because they heavily rely on system administrator knowledge to make decisions. In this paper we describe Seagull, a system designed to facilitate cloud bursting by determining which applications can be transitioned into the cloud most economically, and automating the movement process at the proper time. We further optimize the deployment of applications into the cloud using an intelligent precopying mechanism that proactively replicates virtualized applications, lowering the bursting time from hours to minutes. Our evaluation illustrates how our prototype can reduce cloud costs by more than 45% when bursting to the cloud, and the incremental cost added by precopying applications is offset by a burst time reduction of nearly 95%.
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author = {Tian Guo and Upendra Sharma and Timothy Wood and Sambit Sahu and Prashant Shenoy},
title = {Seagull: Intelligent Cloud Bursting for Enterprise Applications},
booktitle = {2012 USENIX Annual Technical Conference (USENIX ATC 12)},
year = {2012},
isbn = {978-931971-93-5},
address = {Boston, MA},
pages = {361--366},
url = {https://www.usenix.org/conference/atc12/technical-sessions/presentation/guo},
publisher = {USENIX Association},
month = jun
}
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