Related papers: A Survey of DevOps Concepts and Challenges
This manuscript focuses on the environmental, social, and individual sustainability dimensions within the modern software development lifecycle, aiming to establish a holistic approach termed Sustainable DevOps (SusDevOps). Moving beyond…
Business success of companies heavily depends on the availability and performance of their client applications. Due to modern development paradigms such as DevOps and microservice architectural styles, applications are decoupled into…
Although there is consensus that software defined networking and network functions virtualization overhaul service provisioning and deployment, the community still lacks a definite answer on how carrier-grade operations praxis needs to…
For companies developing web-based applications, the Dev and the Ops refer to different groups with either operational or development focus. Therefore, DevOps help these companies streamline software development and operations activities by…
Many organizations adopt DevOps practices and tools in order to break down silos within the organization, improve software quality and delivery, and increase customer satisfaction. However, the impact of the individual practices on the…
Background: Security tools play a vital role in enabling developers to build secure software. However, it can be quite challenging to introduce and fully leverage security tools without affecting the speed or frequency of deployments in the…
Machine learning and AI have been recently embraced by many companies. Machine Learning Operations, (MLOps), refers to the use of continuous software engineering processes, such as DevOps, in the deployment of machine learning models to…
The demand for rapid software delivery in the Information Technology (IT) industry has significantly intensified, emphasising the need for faster software products and service releases with enhanced features to meet customer expectations.…
In this paper, we propose the integration of approaches to Engineering Multi-Agent Systems (EMAS) with the Developer Operations (DevOps) industry best practice. Whilst DevOps facilitates the organizational autonomy of software teams, as…
Scientists are increasingly leveraging advances in instruments, automation, and collaborative tools to scale up their experiments and research goals, leading to new bursts of discovery. Various scientific disciplines, including…
Background. DevOps is a set of practices and cultural values that aims to reduce the barriers between development and operations teams. Due to its increasing interest and imprecise definitions, existing research works have tried to…
Software services play a crucial role in daily life, with automated actions determining access to resources and information. Trusting service providers to perform these actions fairly and accurately is essential, yet challenging for users…
This paper is an overview of the Machine Learning Operations (MLOps) area. Our aim is to define the operation and the components of such systems by highlighting the current problems and trends. In this context, we present the different…
The visions and ideas of Industry 4.0 require a profound interconnection of machines, plants, and IT systems in industrial production environments. This significantly increases the importance of software, which is coincidentally one of the…
Even though demonstrating extraordinary capabilities in code generation and software issue resolving, AI agents' capabilities in the full software DevOps cycle are still unknown. Different from pure code generation, handling the DevOps…
DevOps responds the growing need of companies to streamline the software development process and, thus, has experienced widespread adoption in the past years. However, the successful adoption of DevOps requires companies to address…
DevOps has emerged as one of the most rapidly evolving software development paradigms. With the growing concerns surrounding security in software systems, the DevSecOps paradigm has gained prominence, urging practitioners to incorporate…
The final goal of all industrial machine learning (ML) projects is to develop ML products and rapidly bring them into production. However, it is highly challenging to automate and operationalize ML products and thus many ML endeavors fail…
The DevOps phenomenon is gaining popularity through its ability to support continuous value delivery and ready accommodation of change. However, given the relative immaturity and general confusion about DevOps, a common view of expectations…
This report presents a first sketch of the Service Provider DevOps concept including four major management processes to support the roles of both service and VNF developers as well as the operator in a more agile manner. The sketch is based…