Characterizing network performance of single-node large-scale container deployments

Conrado Boeira, M. Neves, T. Ferreto, I. Haque
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Abstract

Cloud services have shifted from complex monolithic designs to hundreds of loosely coupled microservices over the last years. These microservices communicate via pre-defined APIs (e.g., RPC) and are usually implemented on top of containers. To make the microservices model profitable, cloud providers often co-locate them on a single (virtual) machine, thus achieving high server utilization. Despite being overlooked by previous work, the challenge of providing high-quality network connectivity to multiple containers running on the same host becomes crucial for the overall cloud service performance in this scenario. For that reason, this paper focuses on identifying the overheads and bottlenecks caused by the increasing number of concurrent containers running on a single node, particularly from a networking perspective. Through an extensive set of experiments, we show that the networking performance is mostly restricted by the CPU capacity (even for I/O intensive workloads), that containers can largely suffer from interference originated from packet processing, and that proper core scheduling policies can significantly improve connection throughput. Ultimately, our findings can help to pave the way towards more efficient large-scale microservice deployments.
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描述单节点大规模容器部署的网络性能
在过去的几年里,云服务已经从复杂的单片设计转变为数百个松散耦合的微服务。这些微服务通过预定义的api(例如RPC)进行通信,并且通常在容器之上实现。为了使微服务模型有利可图,云提供商通常将它们共同定位在单个(虚拟)机器上,从而实现高服务器利用率。尽管以前的工作忽略了这一点,但在这种情况下,为运行在同一主机上的多个容器提供高质量网络连接的挑战对整体云服务性能至关重要。出于这个原因,本文着重于识别单个节点上运行的并发容器数量不断增加所造成的开销和瓶颈,特别是从网络的角度来看。通过大量的实验,我们发现网络性能主要受到CPU容量的限制(即使是I/O密集型工作负载),容器可能很大程度上受到来自数据包处理的干扰,适当的核心调度策略可以显著提高连接吞吐量。最终,我们的发现有助于为更高效的大规模微服务部署铺平道路。
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