Patterns of multi-container composition for service orchestration with Docker Compose

IF 3.5 2区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING Empirical Software Engineering Pub Date : 2024-05-03 DOI:10.1007/s10664-024-10462-8
Kalvin Eng, Abram Hindle, Eleni Stroulia
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Abstract

Software design patterns present general code solutions to common software design problems. Modern software systems rely heavily on containers for running their constituent service components. Yet, despite the prevalence of ready-to-use Docker service images ready to participate in multi-container service compositions of applications, developers do not have much guidance on how to compose their own Docker service orchestrations. Thus in this work, we curate a dataset of successful projects that employ Docker Compose as an orchestration tool to run multiple service containers; then, we engage in qualitative and quantitative analysis of Docker Compose configurations. The collection of data and analysis enables the identification and naming of repeating multi-container composition patterns that are used in numerous successful open-source projects, much like software design patterns. These patterns highlight how software systems are orchestrated in the real-world and can give examples to anybody wishing to compose their own service orchestrations. These contributions also advance empirical research in software engineering patterns as evidence is provided about how Docker Compose is used.

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使用 Docker Compose 进行服务协调的多容器组合模式
软件设计模式为常见的软件设计问题提供了通用代码解决方案。现代软件系统在很大程度上依赖容器来运行其组成服务组件。然而,尽管有很多随时可用的 Docker 服务映像可以参与应用程序的多容器服务组合,开发人员在如何组成自己的 Docker 服务编排方面却没有太多指导。因此,在这项工作中,我们收集了使用 Docker Compose 作为协调工具来运行多个服务容器的成功项目数据集;然后,我们对 Docker Compose 配置进行了定性和定量分析。通过收集数据和分析,我们识别并命名了在众多成功开源项目中使用的重复多容器组成模式,就像软件设计模式一样。这些模式强调了软件系统在现实世界中的协调方式,并为任何希望构建自己的服务协调的人提供了范例。由于提供了有关 Docker Compose 如何使用的证据,这些贡献还推动了软件工程模式的实证研究。
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来源期刊
Empirical Software Engineering
Empirical Software Engineering 工程技术-计算机:软件工程
CiteScore
8.50
自引率
12.20%
发文量
169
审稿时长
>12 weeks
期刊介绍: Empirical Software Engineering provides a forum for applied software engineering research with a strong empirical component, and a venue for publishing empirical results relevant to both researchers and practitioners. Empirical studies presented here usually involve the collection and analysis of data and experience that can be used to characterize, evaluate and reveal relationships between software development deliverables, practices, and technologies. Over time, it is expected that such empirical results will form a body of knowledge leading to widely accepted and well-formed theories. The journal also offers industrial experience reports detailing the application of software technologies - processes, methods, or tools - and their effectiveness in industrial settings. Empirical Software Engineering promotes the publication of industry-relevant research, to address the significant gap between research and practice.
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