Escra:事件驱动的亚秒容器资源分配

Greg Cusack, Maziyar Nazari, Sepideh Goodarzy, Erika Hunhoff, Prerit Oberai, Eric Keller, Eric Rozner, Richard Han
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引用次数: 2

摘要

本文探讨了容器环境中自动化资源分配的极限。最近的工作通过根据过去的资源使用情况自动缩放容器来设置容器CPU和内存限制。然而,这些系统是重量级的,并且运行在粗粒度的时间尺度上,当预测不正确时,会导致性能差。我们提出了Escra,这是一个容器编排器,它支持对单个容器进行细粒度的、基于事件的资源分配,并支持对容器集合进行分布式资源分配。Escra在主机内部和主机之间以亚秒的间隔执行资源分配,允许运营商在不影响性能的情况下经济有效地扩展资源。我们在两种类型的容器化应用程序上评估Escra:微服务和无服务器功能。在微服务环境中,与当前技术相比,细粒度和基于事件的资源分配可以将应用程序延迟减少96.9%,并将吞吐量提高3.2倍。Escra可以提高性能,同时减少50%和99%的CPU浪费,分别超过10倍和3.2倍。在无服务器环境中,Escra可以将CPU预留减少2.1倍以上,内存预留减少2倍以上,同时保持类似的端到端性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Escra: Event-driven, Sub-second Container Resource Allocation
This paper pushes the limits of automated resource allocation in container environments. Recent works set container CPU and memory limits by automatically scaling containers based on past resource usage. However, these systems are heavy- weight and run on coarse-grained time scales, resulting in poor performance when predictions are incorrect. We propose Escra, a container orchestrator that enables fine-grained, event- based resource allocation for a single container and distributed resource allocation to manage a collection of containers. Escra performs resource allocation on sub-second intervals within and across hosts, allowing operators to cost-effectively scale resources without performance penalty. We evaluate Escra on two types of containerized applications: microservices and serverless functions. In microservice environments, fine-grained and event- based resource allocation can reduce application latency by up to 96.9% and increase throughput by up to 3.2x when compared against the current state-of-the-art. Escra can increase performance while simultaneously reducing 50th and 99th%ile CPU waste by over 10x and 3.2x, respectively. In serverless environments, Escra can reduce CPU reservations by over 2.1x and memory reservations by more than 2x while maintaining similar end-to-end performance.
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