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Systematic scalability assessment for feature oriented multi-tenant services

机译：面向功能的多租户服务的系统可伸缩性评估

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摘要

Recent software engineering paradigms such as software product lines, supporting development techniques like feature modeling, and cloud provisioning models such as platform and infrastructure as a service, allow for great flexibility during both software design and deployment, resulting in potentially large cost savings. However, all this flexibility comes with a catch: as the combinatorial complexity of optional design features and deployment variability increases, the difficulty of assessing system qualities such as scalability and quality of service increases too. And if the software itself is not scalable (for instance, because of a specific set of selected features), deploying additional service instances is a futile endeavor. Clearly there is a need to systematically measure the impact of feature selection on scalability, as the potential cost savings can be completely mitigated by the risk of having a system that is unable to meet service demand. In this work, we document our results on systematic load testing for automated quality of service and scalability analysis. The major contribution of our work is tool support and a methodology to analyze the scalability of these distributed, feature oriented multi-tenant software systems in a continuous integration process. We discuss our approach to select features for load testing such that a representative set of feature combinations is used to elicit valuable information on the performance impact and feature interactions. Additionally, we highlighfhow our methodology and framework for performance and scalability prediction differs from state-of-practice solutions. We take the viewpoint of both the tenant of the service and the service provider, and report on our experiences applying the approach to an industrial use case in the domain of electronic payments. We conclude that the integration of systematic scalability tests in a continuous integration process offers strong advantages to software developers and service providers, such as the ability to quantify the impact of new features in existing service compositions, and the early detection of hidden feature interactions that may negatively affect the overall performance of multi-tenant services.
机译：最近的软件工程范例（例如软件产品线），支持开发技术（例如功能建模）和云供应模型（例如平台和基础架构即服务）在软件设计和部署过程中都具有极大的灵活性，从而可能节省大量成本。但是，所有这些灵活性都具有吸引力：随着可选设计功能和部署可变性的组合复杂性增加，评估系统质量（如可伸缩性和服务质量）的难度也随之增加。而且，如果软件本身不可扩展（例如，由于一组特定的选定功能），则部署其他服务实例将是徒劳的。显然，有必要系统地衡量功能选择对可伸缩性的影响，因为具有系统无法满足服务需求的风险可以完全减轻潜在的成本节省。在这项工作中，我们记录了系统负载测试的结果，以实现自动化服务质量和可伸缩性分析。我们工作的主要贡献是工具支持和一种在连续集成过程中分析这些面向功能的分布式多租户软件系统的可伸缩性的方法。我们讨论了选择用于负载测试的功能的方法，以便使用一组代表性的功能组合来获取有关性能影响和功能交互的有价值的信息。此外，我们重点介绍了用于性能和可伸缩性预测的方法和框架与实践状态解决方案的不同之处。我们从服务的租户和服务提供商的角度出发，并报告我们在电子支付领域将这种方法应用于工业用例的经验。我们得出的结论是，在连续集成过程中集成系统可伸缩性测试为软件开发人员和服务提供商提供了强大的优势，例如能够量化现有服务组合中新功能的影响，以及及早发现可能会隐藏功能交互的功能。对多租户服务的整体性能产生负面影响。

著录项

  • 来源
    《The Journal of Systems and Software》 |2016年第6期|162-176|共15页
  • 作者

    Davy Preuveneers; Thomas Heyman; Yolande Berbers; Wouter Joosen;

  • 作者单位

    iMinds-DistriNet, Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium;

    iMinds-DistriNet, Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium;

    iMinds-DistriNet, Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium;

    iMinds-DistriNet, Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Distributed systems; Scalability; Tool support;

    机译：分布式系统;可扩展性;工具支援;

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