Cloud computing has established itself as the support for the vast majority of emerging technologies, mainly due to the characteristic of elasticity it offers. Auto-scalers are the systems that enable this elasticity by acquiring and releasing resources on demand to ensure an agreed service level. In this article we present FLAS (Forecasted Load Auto-Scaling), an auto-scaler for distributed services that combines the advantages of proactive and reactive approaches according to the situation to decide the optimal scaling actions in every moment. The main novelties introduced by FLAS are (i) a predictive model of the high-level metrics trend which allows to anticipate changes in the relevant SLA parameters (e.g. performance metrics such as response time or throughput) and (ii) a reactive contingency system based on the estimation of high-level metrics from resource use metrics, reducing the necessary instrumentation (less invasive) and allowing it to be adapted agnostically to different applications. We provide a FLAS implementation for the use case of a content-based publish–subscribe middleware (E-SilboPS) that is the cornerstone of an event-driven architecture. To the best of our knowledge, this is the first auto-scaling system for content-based publish–subscribe distributed systems (although it is generic enough to fit any distributed service). Through an evaluation based on several test cases recreating not only the expected contexts of use, but also the worst possible scenarios (following the Boundary-Value Analysis or BVA test methodology), we have validated our approach and demonstrated the effectiveness of our solution by ensuring compliance with performance requirements over 99% of the time.

云计算已将自身确立为对绝大多数新兴技术的支持，这主要是由于其提供的弹性特性。自动定标器是通过按需获取和释放资源以确保商定的服务水平来实现这种弹性的系统。在这篇文章中，我们目前FLAS（˚F orecasted大号OAD一个uto-小号caling），这是一种用于分布式服务的自动缩放器，根据情况结合了主动和被动方法的优势，可以随时确定最佳缩放操作。FLAS引入的主要新颖之处在于：（i）高级别指标趋势的预测模型，该模型可以预测相关SLA参数（例如，性能指标，例如响应时间或吞吐量）的变化，以及（ii）基于反应性应急系统的根据资源使用指标估算高级指标，减少了必要的手段（侵入性较小），并使其可以不可知论地适用于不同的应用程序。我们为基于内容的发布-订阅中间件（E-SilboPS）的用例提供了FLAS实现，它是事件驱动体系结构的基础。据我们所知，这是第一个基于内容的发布-订阅分布式系统的自动缩放系统（尽管它具有足够的通用性以适合任何分布式服务）。通过基于多个测试用例的评估，不仅重新创建了预期的使用环境，而且还重新创建了可能的最坏情况（遵循边界值分析或BVA测试方法），我们通过验证方法并验证了解决方案的有效性超过99％的时间符合性能要求。