论文标题
了解云工作负载在制作环境中的性能
Understanding Cloud Workloads Performance in a Production like Environment
论文作者
论文摘要
了解Inter-VM干扰对于提供合理的知识并了解当前公共云中的性能退化来自何处至关重要。以此目的，本文设计了一种工作量分类法，该分类法根据主要系统资源如何影响其性能（例如，尾部潜伏期）作为负载水平（例如QPS）的函数。之后，我们提出了三项主要研究，涉及改善云性能的三个主要问题：负载水平对性能的影响，超线程对性能的影响以及限制主要系统资源（例如，最后一级缓存）对性能的影响。在所有这些研究中，我们确定了重要的发现，我们希望帮助云提供商改善其系统利用率。
Understanding inter-VM interference is of paramount importance to provide a sound knowledge and understand where performance degradation comes from in the current public cloud. With this aim, this paper devises a workload taxonomy that classifies applications according to how the major system resources affect their performance (e.g., tail latency) as a function of the level of load (e.g., QPS). After that, we present three main studies addressing three major concerns to improve the cloud performance: impact of the level of load on performance, impact of hyper-threading on performance, and impact of limiting the major system resources (e.g., last level cache) on performance. In all these studies we identified important findings that we hope help cloud providers improve their system utilization.
