ICE:用于云服务中干扰缓解的集成配置引擎

A. Maji, S. Mitra, S. Bagchi
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引用次数: 34

摘要

由于缓存、网络和I/O等硬件资源隔离不完善导致的性能下降在公共云平台中经常发生。受到性能干扰的web服务器会降低交互用户体验并导致收入损失。现有的干扰缓解工作试图通过对hypervisor进行侵入性更改来解决这个问题,例如,使用智能调度器或实时迁移,其中许多只对基础设施提供商可用,而对最终消费者无效。在本文中,我们提出了一个管理web服务器集群的框架,其中干扰的影响可以通过智能重新配置来减少。我们的控制器ICE通过执行两次自主重新配置,提高了干扰期间web服务器的性能。首先,它在服务器集群的入口点重新配置负载均衡器,从而减少受影响服务器上的负载。然后,ICE在受影响的服务器上重新配置中间件,以进一步减少其负载。我们在Cloud Suite(一个流行的web应用基准)上实现和评估ICE,并使用两个流行的负载平衡器——HA Proxy和LVS。我们在私有云测试平台上的实验表明,与静态配置的服务器集群相比,ICE可以将web服务器的中位数响应时间提高94%。ICE的性能也比自适应负载均衡器(使用最少的连接调度)高出39%。
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ICE: An Integrated Configuration Engine for Interference Mitigation in Cloud Services
Performance degradation due to imperfect isolation of hardware resources such as cache, network, and I/O has been a frequent occurrence in public cloud platforms. A web server that is suffering from performance interference degrades interactive user experience and results in lost revenues. Existing work on interference mitigation tries to address this problem by intrusive changes to the hyper visor, e.g., Using intelligent schedulers or live migration, many of which are available only to infrastructure providers and not end consumers. In this paper, we present a framework for administering web server clusters where effects of interference can be reduced by intelligent reconfiguration. Our controller, ICE, improves web server performance during interference by performing two-fold autonomous reconfigurations. First, it reconfigures the load balancer at the ingress point of the server cluster and thus reduces load on the impacted server. ICE then reconfigures the middleware at the impacted server to reduce its load even further. We implement and evaluate ICE on Cloud Suite, a popular web application benchmark, and with two popular load balancers - HA Proxy and LVS. Our experiments in a private cloud test bed show that ICE can improve median response time of web servers by up to 94% compared to astatically configured server cluster. ICE also outperforms an adaptive load balancer (using least connection scheduling) by up to 39%.
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