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Testing large-scale cloud management

Authors: Daniel Citron; Aviad Zlotnick;

Testing large-scale cloud management

Abstract

Testing for correctness and reliability is a major challenge in the development and deployment of cloud computing platforms. Testing a cloud composed of hundreds to thousands of servers is often cost-prohibitive because of the extensive amount of hardware required. Simulation and emulation, i.e., traditional alternatives to hardware, are too abstract or too slow for testing production code in environments with many servers. We propose a testing approach that combines simulation and emulation in a cloud simulator that runs on a single processor yet enables testing of cloud management software as if the software were managing hundreds of servers and thousands of virtual machine instances. This approach alleviates a significant obstacle on the path to high-quality cloud computing systems.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Average
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