While a multitude of cloud vendors exist today offering flexible application hosting services, the application adaptation capabilities provided in terms of autoscaling are rather limited. In most cases, a static adaptation action is used having a fixed scaling response. In the cases that a dynamic adaptation action is provided, this is based on a single scaling variable. We propose Severity, a novel algorithmic approach aiding the adaptation of cloud applications. Based on the input of the DevOps, our approach detects situations, calculates their Severity and proposes adaptations which can lead to better application performance. Severity can be calculated for any number of application QoS attributes and any type of such attributes, whether bounded or unbounded. Evaluation with four distinct workload types and a variety of monitoring attributes shows that QoS for particular application categories is improved. The feasibility of our approach is demonstrated with a prototype implementation of an application adaptation manager, for which the source code is provided.

中文翻译：

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严重性：云应用程序弹性的 QoS 感知方法

虽然当今存在众多云供应商提供灵活的应用托管服务，但在自动缩放方面提供的应用适配能力相当有限。在大多数情况下，使用具有固定缩放响应的静态适应动作。在提供动态适应动作的情况下，这基于单个缩放变量。我们提出了严重性，这是一种有助于适应云应用程序的新颖算法方法。基于 DevOps 的输入，我们的方法检测情况，计算它们的严重性并提出可以导致更好的应用程序性能的调整。可以针对任意数量的应用 QoS 属性和任意类型的此类属性（无论是有界还是无界）计算严重性。对四种不同的工作负载类型和各种监控属性的评估表明，特定应用程序类别的 QoS 得到了改进。我们的方法的可行性通过应用程序适配管理器的原型实现来证明，为此提供了源代码。