Making Serverless Computing More Serverless
Making Serverless Computing More Serverless
复制标题
让无服务器计算更加无服务器
DOI：
10.1109/cloud.2018.00064
复制
发表时间：
2018
期刊：
影响因子：
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通讯作者：
Eric Rozner
中科院分区：
文献类型：
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作者：
Zaid Al;Sepideh Goodarzy;E. Hunter;Sangtae Ha;Richard Han;Eric Keller;Eric Rozner
在无服务器计算中，开发人员定义一个函数来处理事件，而无服务器框架则根据需要水平扩展应用程序。这种基于函数的抽象的缺点是它限制了支持的应用程序的类型，并将函数的约束限制在函数执行的服务器的物理资源限制之内。在本文中，我们提出了一种新的无服务器计算的抽象：开发人员提供一个过程，无服务器框架无缝地扩展了整个数据中心的过程的资源使用。这种抽象使处理不仅具有更通用的目的，而且还允许进程突破单个服务器的限制-使无服务器计算更加无服务器。为了实现这种抽象，我们提出了ServerlessOS，由三个关键组件组成：（i）一个新的分解模型，它利用分解进行抽象，但使资源能够在服务器之间流畅地移动以提高性能;（ii）一个云编排层，通过本地和全局决策在应用程序的整个生命周期中管理细粒度的资源分配和放置;以及（iii）隔离能力，该隔离能力在分解时强制数据和资源隔离，从而有效地将Linux cgroup功能扩展到跨服务器。
In serverless computing, developers define a function to handle an event, and the serverless framework horizontally scales the application as needed. The downside of this function-based abstraction is it limits the type of application supported and places a bound on the function to be within the physical resource limitations of the server the function executes on. In this paper we propose a new abstraction for serverless computing: a developer supplies a process and the serverless framework seamlessly scales out the process's resource usage across the datacenter. This abstraction enables processing to not only be more general purpose, but also allows a process to break out of the limitations of a single server – making serverless computing more serverless. To realize this abstraction, we propose ServerlessOS, comprised of three key components: (i) a new disaggregation model, which leverages disaggregation for abstraction, but enables resources to move fluidly between servers for performance; (ii) a cloud orchestration layer which manages fine-grained resource allocation and placement throughout the application's lifetime via local and global decision making; and (iii) an isolation capability that enforces data and resource isolation across disaggregation, effectively extending Linux cgroup functionality to span servers.