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Hubbub-Scale: Towards Reliable Elastic Scaling under Multi-tenancy

机译:Hubbub级:在多租户下可靠的弹性缩放

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Elastic resource provisioning is used to guarantee service level objective (SLO) with reduced cost in a Cloud platform. However, performance interference in the hosting platform introduces uncertainty in the performance guarantees of provisioned services. Existing elasticity controllers are either unaware of this interference or over-provision resources to meet the SLO. In this paper, we show that assuming predictable performance of VMs to build an elasticity controller will fail if interference is not modelled. We identify and control the different sources of unpredictability and build Hubbub-Scale, an elasticity controller that is reliable in the presence of performance interference. Our evaluation with Redis and Memcached show that Hubbub-Scale efficiently conforms to the SLO requirements under scenarios where standard modelling approaches fail.
机译:弹性资源配置用于保证云平台中降低成本的服务水平目标(SLO)。但是,托管平台的性能干扰在供应服务的性能保证中引入了不确定性。现有的弹性控制器要么没有意识到这种干扰或过度提供资源,以满足SLO。在本文中,我们表明假设VM的可预测性能构建弹性控制器如果没有建模干扰,则会失败。我们识别和控制不同的不可预测性和构建喧哗级的来源,这是在性能干扰的存在下可靠的弹性控制器。我们与Redis和Memcached的评估表明,Hubbub-Scale在标准建模方法失败的情况下有效地符合SLO要求。

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