Resource Scaling Strategies for Open-Source FaaS Platforms compared to Commercial Cloud Offerings

Q1 Computer Science

IEEE Cloud Computing Pub Date : 2022-07-01 DOI:10.1109/CLOUD55607.2022.00020

Johannes Manner, G. Wirtz

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引用次数: 2

Abstract

Open-source offerings are often investigated when comparing their features to commercial cloud offerings. However, performance benchmarking is rarely executed for open-source tools hosted on-premise nor is it possible to conduct a fair cost comparison due to a lack of resource settings equivalent to cloud scaling strategies.Therefore, we firstly list implemented resource scaling strategies for public and open-source FaaS platforms. Based on this we propose a methodology to calculate an abstract performance measure to compare two platforms with each other. Since all open-source platforms suggest a Kubernetes deployment, we use this measure for a configuration of open-source FaaS platforms based on Kubernetes limits. We tested our approach with CPU intensive functions, considering the difference between single-threaded and multi-threaded functions to avoid wasting resources. With regard to this, we also address the noisy neighbor problem for open-source FaaS platforms by conducting an instance parallelization experiment. Our approach to limit resources leads to consistent results while avoiding an overbooking of resources.

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与商业云产品相比，开源FaaS平台的资源扩展策略

在将开源产品的功能与商业云产品进行比较时，经常会对其进行调查。然而，很少对本地托管的开源工具执行性能基准测试，也不可能进行公平的成本比较，因为缺乏相当于云扩展策略的资源设置。因此，我们首先列出了公共和开源FaaS平台实现的资源扩展策略。在此基础上，我们提出了一种方法来计算一个抽象的性能指标来比较两个平台。因为所有的开源平台都建议部署Kubernetes，所以我们使用这个度量来配置基于Kubernetes限制的开源FaaS平台。我们用CPU密集型函数测试了我们的方法，考虑了单线程和多线程函数之间的差异，以避免浪费资源。为此，我们还通过实例并行化实验解决了开源FaaS平台的噪声邻居问题。我们限制资源的方法导致了一致的结果，同时避免了资源的超额预订。

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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来源期刊

IEEE Cloud Computing Computer Science-Computer Networks and Communications

CiteScore

11.20

自引率

0.00%

发文量

期刊介绍： Cessation. IEEE Cloud Computing is committed to the timely publication of peer-reviewed articles that provide innovative research ideas, applications results, and case studies in all areas of cloud computing. Topics relating to novel theory, algorithms, performance analyses and applications of techniques are covered. More specifically: Cloud software, Cloud security, Trade-offs between privacy and utility of cloud, Cloud in the business environment, Cloud economics, Cloud governance, Migrating to the cloud, Cloud standards, Development tools, Backup and recovery, Interoperability, Applications management, Data analytics, Communications protocols, Mobile cloud, Private clouds, Liability issues for data loss on clouds, Data integration, Big data, Cloud education, Cloud skill sets, Cloud energy consumption, The architecture of cloud computing, Applications in commerce, education, and industry, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), Business Process as a Service (BPaaS)