ContainerVisor:容器资源的自定义控制

Tianlin Li, Kartik Gopalan, Ping Yang
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引用次数: 1

摘要

云平台越来越多地使用容器进行轻量级虚拟化。与每个运行自己的操作系统的完整系统虚拟机(vm)不同,容器共享一个有状态的操作系统,以减少内存占用和执行开销。然而,主流操作系统目前在定制容器内存管理方面的能力有限,因为它们缺乏必要的抽象和机制来准确跟踪和隔离容器的内存占用。我们提出了一种新的抽象,称为容器级地址空间(CLAS),它提供了跨其所有组成进程的容器内存的统一视图。我们介绍了ContainerVisor的设计,这是一个利用CLAS提供定制内存管理服务的每个容器资源管理系统。我们在Linux上描述了一个用于运行未经修改的应用程序的ContainerVisor原型,并演示了三个概念验证的定制服务,即进程级内存限制和保留、特定于容器的页面替换策略和隐私感知的内存取消分配。我们的评估表明,ContainerVisor可以在合理的开销范围内提供这些定制服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ContainerVisor: Customized Control of Container Resources
Cloud platforms are increasingly using containers for lightweight virtualization. Unlike full system virtual machines (VMs) that each runs its own operating system, containers share a stateful operating system to reduce their memory footprint and execution overheads. However, mainstream operating systems are currently limited in their ability to customize a container's memory management, since they lack the necessary abstractions and mechanisms to accurately track and isolate a container's memory footprint. We propose a new abstraction, called the Container-Level Address Space (CLAS), that provides a unified view of a container's memory across all of its constituent processes. We present the design of ContainerVisor, a per-container resource management system that leverages CLAS to provide customized memory management services. We describe a ContainerVisor prototype on Linux for running unmodified applications and demonstrate three proof-of-concept customized services, namely process-level memory limits and reservations, container-specific page replacement policies, and privacy-aware memory de-allocation. Our evaluations show that ContainerVisor can provide these customized services within reasonable overheads.
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