Hybrid Cloud Storage: Bridging the Gap between Compute Clusters and Cloud Storage

Abhishek K. Gupta, Richard P. Spillane, Wenguang Wang, Maxime Austruy, Vahid Fereydouny, C. Karamanolis
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引用次数: 2

Abstract

Thanks to the compelling economics of public cloud storage, the trend in the IT industry is to move the bulk of analytics and application data to services such as AWS S3 and Google Cloud Storage. At the same time, customers want to continue accessing and analyzing much of that data using applications that run on compute clusters that may reside either on public clouds or on-premise. For VMware customers, those clusters run vSphere (sometimes with vSAN) on-premise and in the future may utilize SDDCaaS. Cloud storage exhibits high latencies and it is not appropriate for direct use by applications. A key challenge for these use cases is determining the subset of the typically huge data sets that need to be moved into the primary storage tier of the compute clusters. This paper introduces a novel approach for creating a hybrid cloud storage that allows customers to utilize the fast primary storage of their compute clusters as a caching tier in front of a slow secondary storage tier. This approach can be completely transparent requiring no changes to the application. To achieve this, we extended VDFS [16], a POSIX-compliant scale-out filesystem, with the concept of caching-tier volumes. VDFS caching-tier volumes resemble regular file system volumes, but they fault-in data from a cloud storage back-end on first access. Cached data are persisted on fast primary storage, close to the compute cluster, like VMware's vSAN. Caching-tier volumes use a write-back approach. The enterprise features of the primary storage ensure the persistence and fault tolerance of new or updated data. Write-back from the primary to cloud storage is managed using an efficient change-tracking mechanism built into VDFS called exo-clones [18]. This paper outlines the architecture and implementation of caching tier volumes on VDFS and reports on an initial evaluation of the current prototype.
混合云存储:弥合计算集群和云存储之间的差距
由于公共云存储令人信服的经济效益,IT行业的趋势是将大量分析和应用程序数据转移到AWS S3和谷歌云存储等服务上。与此同时,客户希望继续使用运行在计算集群上的应用程序访问和分析大部分数据,这些集群可能驻留在公共云或内部部署上。对于VMware客户,这些集群在本地运行vSphere(有时使用vSAN),将来可能会使用SDDCaaS。云存储具有高延迟,不适合应用程序直接使用。这些用例面临的一个关键挑战是确定需要移动到计算集群的主存储层的典型大型数据集的子集。本文介绍了一种用于创建混合云存储的新方法,该方法允许客户利用其计算集群的快速主存储作为慢速二级存储层前面的缓存层。这种方法可以是完全透明的,无需对应用程序进行任何更改。为了实现这一点,我们扩展了VDFS[16],它是一个兼容posix的横向扩展文件系统,具有缓存层卷的概念。VDFS缓存层卷类似于普通文件系统卷,但它们在首次访问时从云存储后端导入数据。缓存的数据持久化在快速主存储上,靠近计算集群,就像VMware的vSAN一样。缓存层卷使用回写方法。主存储的企业特性确保了新数据或更新数据的持久性和容错性。从主存储到云存储的回写使用VDFS内建的一种高效的变更跟踪机制进行管理,该机制称为exo-克隆[18]。本文概述了VDFS上缓存层卷的体系结构和实现,并报告了对当前原型的初步评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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