GitOps: The Evolution of DevOps?

Beetz, Florian; Harrer, Simon

doi:10.1109/ms.2021.3119106

Cited by 25 publications

(16 citation statements)

References 8 publications

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“…Academics recommend that future work should include the GitOps process [10], which involves not only development but also CI/CD and observability [11], because it is utilized as a study material. It is critical that there be solutions that can cover the complete software lifecycle [12], especially for firms that wish to implement continuously [9].…”

Section: Argo CDmentioning

confidence: 99%

“…FluxCD is also an open source, developed by the Cloud Native Computing Foundation. It is described as a GitOps operator for Kubernetes [10] that synchronizes the state of manifest in a Git repository to what is running in a cluster [13]. It runs in the cluster, and its principal scope is to monitor a remote Git repository to apply changes in Kubernetes manifests.…”

Section: Fluxcdmentioning

confidence: 99%

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Method for Continuous Integration and Deployment Using a Pipeline Generator for Agile Software Projects

Donca

Stan

Misaros

et al. 2022

Sensors

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Lately, the software development industry is going through a slow but real transformation. Software is increasingly a part of everything, and, software developers, are trying to cope with this exploding demand through more automation. The pipelining technique of continuous integration (CI) and continuous delivery (CD) has developed considerably due to the overwhelming demand for the deployment and deliverability of new features and applications. As a result, DevOps approaches and Agile principles have been developed, in which developers collaborate closely with infrastructure engineers to guarantee that their applications are deployed quickly and reliably. Thanks to pipeline approach thinking, the efficiency of projects has greatly improved. Agile practices represent the introduction to the system of new features in each sprint delivery. Those practices may contain well-developed features or can contain bugs or failures which impact the delivery. The pipeline approach, depicted in this paper, overcomes the problems of delivery, improving the delivery timeline, the test load steps, and the benchmarking tasks. It decreases system interruption by integrating multiple test steps and adds stability and deliverability to the entire process. It provides standardization which means having an established, time-tested process to use, and can also decrease ambiguity and guesswork, guarantee quality and boost productivity. This tool is developed with an interpreted language, namely Bash, which offers an easier method to integrate it into any platform. Based on the experimental results, we demonstrate the value that this solution currently creates. This solution provides an effective and efficient way to generate, manage, customize, and automate Agile-based CI and CD projects through automated pipelines. The suggested system acts as a starting point for standard CI/CD processes, caches Docker layers for subsequent usage, and implements highly available deliverables in a Kubernetes cluster using Helm. Changing the principles of this solution and expanding it into multiple platforms (windows) will be addressed in a future discussion.

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Section: Argo CDmentioning

confidence: 99%

Section: Fluxcdmentioning

confidence: 99%

Method for Continuous Integration and Deployment Using a Pipeline Generator for Agile Software Projects

Donca

Stan

Misaros

et al. 2022

Sensors

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“…GitOps is defined as a model for operating Kubernetes clusters or cloud-native applications using the Version Control System Git as the single source of truth [10]. One of the features GitOps envisions declarative descriptions of an environment to be stored as infrastructureas-code in a Git repository.…”

Section: Gitopsmentioning

confidence: 99%

Collaborative Computing Support for Analysis Facilities Exploiting Software as Infrastructure Techniques

Flechas¹,

Attebury²,

Bloom³

et al. 2022

Preprint

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Prior to the public release of Kubernetes it was difficult to conduct joint development of elaborate analysis facilities due to the highly non-homogeneous nature of hardware and network topology across compute facilities. However, since the advent of systems like Kubernetes and OpenShift, which provide declarative interfaces for building fault-tolerant and self-healing deployments of networked software, it is possible for multiple institutes to collaborate more effectively since resource details are abstracted away through various forms of hardware and software virtualization. In this whitepaper we will outline the development of two analysis facilities: "Coffea-casa" at University of Nebraska Lincoln and the "Elastic Analysis Facility" at Fermilab, and how utilizing platform abstraction has improved the development of common software for each of these facilities, and future development plans made possible by this methodology.

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“…Nessa camada, contêineres são configurados pelo componente Gerenciador de Imagens para atender múltiplas func ¸ões da aplicac ¸ão que está sendo desenvolvida (Passo 6 na Figura 1): (i) orquestrac ¸ão de tarefas (e.g., Apache Airflow), processamento distribuído (e.g., Apache Spark), consultas a dados (e.g., Apache Hive) e visualizac ¸ão (e.g., Apache Superset). O Gerenciador de Imagens segue o conceito de GitOps [Beetz and Harrer 2022] para acessar o catálogo de imagens (Passo 5 na Figura 1). A ideia do GitOps é que tenhamos um repositório Git contendo as descric ¸ões declarativas da infraestrutura e um processo automatizado para fazer o ambiente de produc ¸ão corresponder ao estado descrito no repositório.…”

Section: Figura 1 Arquitetura Do Orbiterunclassified

ORBITER: um Arcabouço para Implantação Automática de Aplicações Big Data em Arquiteturas Serverless

Loureiro

Oliveira

2022

Anais Do XXXVII Simpósio Brasileiro De Banco De Dados (SBBD 2022)

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Tem se tornado cada vez mais comum a oferta de mecanismos de computação serverless em nuvens públicas. Embora o desenvolvimento de uma aplicação seguindo uma arquitetura serverless apresente vantagens, o mesmo ainda traz consigo alguns desafios como a baixa portabilidade. Além disso, a arquitetura serverless também acaba adicionando um certo nível de morosidade na construção da arquitetura de aplicações distribuídas, que já é algo complexo. Este artigo propõe um arcabouço para implantação de aplicações em uma arquitetura serverless, de forma fácil para o desenvolvedor. O arcabouço proposto foi desenvolvido utilizando ferramentas de código aberto, e foi avaliado com uma aplicação de análise de dados de acidentes de trânsito da ANTT.

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GitOps: The Evolution of DevOps?

Cited by 25 publications

References 8 publications

Method for Continuous Integration and Deployment Using a Pipeline Generator for Agile Software Projects

Method for Continuous Integration and Deployment Using a Pipeline Generator for Agile Software Projects

Collaborative Computing Support for Analysis Facilities Exploiting Software as Infrastructure Techniques

ORBITER: um Arcabouço para Implantação Automática de Aplicações Big Data em Arquiteturas Serverless

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