{"title":"ContainerVisor: Customized Control of Container Resources","authors":"Tianlin Li, Kartik Gopalan, Ping Yang","doi":"10.1109/IC2E.2019.00033","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":226094,"journal":{"name":"2019 IEEE International Conference on Cloud Engineering (IC2E)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Cloud Engineering (IC2E)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC2E.2019.00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
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.