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

机译:Hubbub规模:在多租户下实现可靠​​的弹性扩展

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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:弹性资源供应用于在云平台中以降低的成本来保证服务水平目标(SLO)。但是,托管平台中的性能干扰会在预配置服务的性能保证中引入不确定性。现有的弹性控制器要么没有意识到这种干扰,要么没有满足SLO的超额配置资源。在本文中,我们表明,如果不对干扰进行建模,则假设虚拟机的可预测性能来构建弹性控制器将失败。我们确定并控制了不可预测性的不同来源,并构建了Hubbub-Scale,这是一种在存在性能干扰的情况下可靠的弹性控制器。我们对Redis和Memcached的评估表明,在标准建模方法失败的情况下,Hubbub-Scale有效地满足了SLO要求。

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