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Robustness Indicators for Cloud-Based Systems Topologies

机译:基于云的系统拓扑的稳健性指标

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Various services are now available in the Cloud, ranging from turnkey databases and application servers to high-level services such as continuous integration or source version control. To stand out of this diversity, robustness of service compositions is an important selling argument, but which remains difficult to understand and estimate as it does not only depend on services but also on the underlying platform and infrastructure. Yet, choosing a specific service composition may fail to deliver the expected robustness, but reverting early choices may jeopardise the success of any Cloud project. Inspired by existing models used in Biology to quantify the robustness of ecosystems, we show how to tailor them to obtain early indicators of robustness for cloud-based deployments. This technique helps identify weakest services in the overall architecture and in turn mitigates the risk of having to revert key architectural choices. We illustrate our approach by comparing the robustness of four alternative deployments of the Sens App application, which includes a Mongo DB database, four REST services and a graphical web-front end.
机译:云中现在可以使用各种服务,从交钥匙数据库和应用程序服务器到高级服务(例如持续集成或源版本控制)。为了脱颖而出,服务组合的健壮性是一个重要的卖点,但由于它不仅依赖于服务而且依赖于基础平台和基础结构,因此仍然难以理解和估计。但是,选择特定的服务组合可能无法提供预期的鲁棒性,但是恢复早期选择可能会损害任何Cloud项目的成功。受生物学中用于量化生态系统健壮性的现有模型的启发,我们展示了如何定制它们以获取基于云的部署的健壮性的早期指标。此技术有助于确定整个体系结构中最弱的服务,从而减轻必须还原关键体系结构选择的风险。我们通过比较Sens App应用程序的四个替代部署的健壮性来说明我们的方法,该应用程序包括一个Mongo DB数据库,四个REST服务和一个图形化Web前端。

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