成本-可用性意识扩展:实现云服务的优化扩展

IF 3.6 2区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Andre Bento, Filipe Araujo, Raul Barbosa
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引用次数: 0

摘要

云服务因其提供的丰富资源,在开发大型应用程序方面越来越受欢迎。这些资源的可扩展性和可访问性使各种规模的组织更容易开发和实施复杂、高要求的应用程序,以即时满足需求。由于云的使用涉及货币费用,应用程序开发人员和运营商面临的挑战之一是如何在预算限制和关键质量属性(如可用性)之间取得平衡。行业标准通常默认采用简化的解决方案,无法同时考虑相互竞争的目标。为了应对这一挑战,我们的研究提出了一种成本-可用性感知扩展(CAAS)方法,该方法使用可用性和成本的多目标优化。我们使用两个开源微服务应用对 CAAS 进行了评估,与基于 CPU 的行业标准自动分级器(AS)相比,结果有所改进。CAAS 可以找到最佳系统配置,第一个应用的可用性平均在 1 到 2 个 9 之间,成本平均降低了 6%;第二个应用的可用性平均为 1 个 9,成本平均降低了 18%。我们的模型与默认 AS 之间的结果差距表明,运营商可以显著改善其应用程序的运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cost-Availability Aware Scaling: Towards Optimal Scaling of Cloud Services

Cloud services have become increasingly popular for developing large-scale applications due to the abundance of resources they offer. The scalability and accessibility of these resources have made it easier for organizations of all sizes to develop and implement sophisticated and demanding applications to meet demand instantly. As monetary fees are involved in the use of the cloud, one of the challenges for application developers and operators is to balance their budget constraints with crucial quality attributes, such as availability. Industry standards usually default to simplified solutions that cannot simultaneously consider competing objectives. Our research addresses this challenge by proposing a Cost-Availability Aware Scaling (CAAS) approach that uses multi-objective optimization of availability and cost. We evaluate CAAS using two open-source microservices applications, yielding improved results compared to the industry standard CPU-based Autoscaler (AS). CAAS can find optimal system configurations with higher availability, between 1 and 2 nines on average, and reduced costs, 6% on average, with the first application, and 1 nine of availability on average, and reduced costs up to 18% on average, with the second application. The gap in the results between our model and the default AS suggests that operators can significantly improve the operation of their applications.

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来源期刊
Journal of Grid Computing
Journal of Grid Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
8.70
自引率
9.10%
发文量
34
审稿时长
>12 weeks
期刊介绍: Grid Computing is an emerging technology that enables large-scale resource sharing and coordinated problem solving within distributed, often loosely coordinated groups-what are sometimes termed "virtual organizations. By providing scalable, secure, high-performance mechanisms for discovering and negotiating access to remote resources, Grid technologies promise to make it possible for scientific collaborations to share resources on an unprecedented scale, and for geographically distributed groups to work together in ways that were previously impossible. Similar technologies are being adopted within industry, where they serve as important building blocks for emerging service provider infrastructures. Even though the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines, including not only multiple domains of computer science (networking, middleware, programming, algorithms) but also application disciplines themselves, as well as such areas as sociology and economics, is needed to broaden the applicability and scope of the current body of knowledge.
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