DOML: A new modeling approach to Infrastructure-as-Code

IF 3 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Systems Pub Date : 2024-07-06 DOI:10.1016/j.is.2024.102422

Michele Chiari , Bin Xiang , Sergio Canzoneri , Galia Novakova Nedeltcheva , Elisabetta Di Nitto , Lorenzo Blasi , Debora Benedetto , Laurentiu Niculut , Igor Škof

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引用次数: 0

Abstract

One of the main DevOps practices is the automation of resource provisioning and deployment of complex software. This automation is enabled by the explicit definition of Infrastructure-as-Code (IaC), i.e., a set of scripts, often written in different modeling languages, which defines the infrastructure to be provisioned and applications to be deployed.

We introduce the DevOps Modeling Language (DOML), a new Cloud modeling language for infrastructure deployments. DOML is a modeling approach that can be mapped into multiple IaC languages, addressing infrastructure provisioning, application deployment and configuration.

The idea behind DOML is to use a single modeling paradigm which can help to reduce the need of deep technical expertise in using different specialized IaC languages.

We present the DOML’s principles and discuss the related work on IaC languages. Furthermore, the advantages of the DOML for the end-user are demonstrated in comparison with some state-of-the-art IaC languages such as Ansible, Terraform, and Cloudify, and an evaluation of its effectiveness through several examples and a case study is provided.

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DOML：基础设施即代码的新建模方法

DevOps 的主要实践之一是资源调配和复杂软件部署的自动化。这种自动化是通过明确定义基础设施即代码（IaC）来实现的，即一组脚本，通常用不同的建模语言编写，定义要配置的基础设施和要部署的应用程序。DOML 是一种建模方法，可映射到多种 IaC 语言中，用于解决基础设施调配、应用程序部署和配置问题。DOML 背后的理念是使用单一建模范式，这有助于减少对使用不同专业 IaC 语言的深层次专业技术知识的需求。我们介绍了 DOML 的原理，并讨论了 IaC 语言的相关工作。我们介绍了 DOML 的原理，并讨论了 IaC 语言方面的相关工作。此外，通过与 Ansible、Terraform 和 Cloudify 等最先进的 IaC 语言进行比较，我们展示了 DOML 对最终用户的优势，并通过几个例子和案例研究对其有效性进行了评估。

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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来源期刊

Information Systems 工程技术-计算机：信息系统

CiteScore

9.40

自引率

2.70%

发文量

112

审稿时长

53 days

期刊介绍： Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems. Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.