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Proceedings ArticleDOI

CloudCmp: comparing public cloud providers

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TLDR
Applying CloudCmp to four cloud providers that together account for most of the cloud customers today, it is found that their offered services vary widely in performance and costs, underscoring the need for thoughtful provider selection.
Abstract
While many public cloud providers offer pay-as-you-go computing, their varying approaches to infrastructure, virtualization, and software services lead to a problem of plenty. To help customers pick a cloud that fits their needs, we develop CloudCmp, a systematic comparator of the performance and cost of cloud providers. CloudCmp measures the elastic computing, persistent storage, and networking services offered by a cloud along metrics that directly reflect their impact on the performance of customer applications. CloudCmp strives to ensure fairness, representativeness, and compliance of these measurements while limiting measurement cost. Applying CloudCmp to four cloud providers that together account for most of the cloud customers today, we find that their offered services vary widely in performance and costs, underscoring the need for thoughtful provider selection. From case studies on three representative cloud applications, we show that CloudCmp can guide customers in selecting the best-performing provider for their applications.

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References
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Journal Article

Above the Clouds: A Berkeley View of Cloud Computing

TL;DR: This work focuses on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SAAS Users, and uses the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public.
Proceedings ArticleDOI

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Proceedings ArticleDOI

Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds

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Modeling TCP throughput: a simple model and its empirical validation

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Journal ArticleDOI

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TL;DR: In this paper, it is shown that it is impossible to achieve consistency, availability, and partition tolerance in the asynchronous network model, and then solutions to this dilemma in the partially synchronous model are discussed.
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