Towards a benefits dependency network for DevOps based on a systematic literature review

Jabbari, Ramtin; Ali, Nauman bin; Petersen, Kai; Tanveer, Binish

doi:10.1002/smr.1957

Cited by 40 publications

(38 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Depending on the application, organizations can also add staging processes when human validation is needed. Thanks to the automation, development qualities such as traceability come at a substantially lower cost compared to a manual workflow [26]. DevOps has inspired a similar mindset within ML development in the form of MLOps, i.e., the standardization and streamlining of ML lifecycle management [27] -which is a recommended approach to tackle continuous engineering in Software 2.0 [28].…”

Section: Continuous Engineering In the Ai Eramentioning

confidence: 99%

Agility in Software 2.0 -- Notebook Interfaces and MLOps with Buttresses and Rebars

Borg¹

2021

Preprint

View full text Add to dashboard Cite

Artificial intelligence through machine learning is increasingly used in the digital society. Solutions based on machine learning bring both great opportunities, thus coined "Software 2.0," but also great challenges for the engineering community to tackle. Due to the experimental approach used by data scientists when developing machine learning models, agility is an essential characteristic. In this keynote address, we discuss two contemporary development phenomena that are fundamental in machine learning development, i.e., notebook interfaces and MLOps. First, we present a solution that can remedy some of the intrinsic weaknesses of working in notebooks by supporting easy transitions to integrated development environments. Second, we propose reinforced engineering of AI systems by introducing metaphorical buttresses and rebars in the MLOps context. Machine learning-based solutions are dynamic in nature, and we argue that reinforced continuous engineering is required to quality assure the trustworthy AI systems of tomorrow.1 bit.ly/3dKeUEH

show abstract

Section: Continuous Engineering In the Ai Eramentioning

confidence: 99%

Agility in Software 2.0 -- Notebook Interfaces and MLOps with Buttresses and Rebars

Borg¹

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…DevOps is a pretty new concept for developing software that extends agile principles to the entire software delivery process [14]. In most companies, development and operations exist as separate functions, therefore, the collaboration in DevOps seeks to bridge the silos of software development and operations functions, and the idea is that this will reduce the amount of overhead that is usually prevalent in organizations where there are a lot of hierarchies, middle-managers, and inter-team cooperation [17].…”

Section: Devopsmentioning

confidence: 99%

“…To sum up, DevOps highlight principles such as: 1) Knowledge sharing by breaking down barriers between development and operations 2) Automation of build, deployment and test, 3) Embracing shared responsibility and 4) Ensuring continuous software development [14].…”

Section: Devopsmentioning

confidence: 99%

Dependency Management in Large-Scale Agile: A Case Study of DevOps Teams

Stray

Moe

Aasheim³

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

View full text Add to dashboard Cite

Managing dependencies between teams and within teams is critical when running large-scale agile projects. In large-scale software development, work is carried out simultaneously by many developers and development teams. Results are delivered frequently and iteratively, which requires management of dependencies on both the project and team level. This study explores coordination mechanisms in agile DevOps teams in a large-scale project and how the mechanisms address different types of dependencies. We conducted a case study where we observed 38 scheduled meetings and interviewed members of five DevOps teams and two teams supporting the DevOps teams. By using a dependency taxonomy, we identified 20 coordination mechanisms (eleven synchronization activities and nine synchronization artifacts). Eight of these mechanisms seem essential for coordination in large-scale projects because they addressed more than four types of dependencies. The main implication is that project management needs to combine many practices handling all the dependencies in large-scale projects.

show abstract

“…In the literature, we can essentially find studies on DevOps that explore ways to align development teams with operations [15], the benefits that this methodology can bring to organizations [16], and the challenges that are posed [17]. However, there is a research gap in the characterization of the simultaneous adoption of Agile and DevOps in organizations.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Benefits of Combining DevOps and Agile

2022

View full text Add to dashboard Cite

The combined adoption of Agile and DevOps enables organizations to cope with the increasing complexity of managing customer requirements and requests. It fosters the emergence of a more collaborative and Agile framework to replace the waterfall models applied to software development flow and the separation of development teams from operations. This study aims to explore the benefits of the combined adoption of both models. A qualitative methodology is adopted by including twelve case studies from international software engineering companies. Thematic analysis is employed in identifying the benefits of the combined adoption of both paradigms. The findings reveal the existence of twelve benefits, highlighting the automation of processes, improved communication between teams, and reduction in time to market through process integration and shorter software delivery cycles. Although they address different goals and challenges, the Agile and DevOps paradigms when properly combined and aligned can offer relevant benefits to organizations. The novelty of this study lies in the systematization of the benefits of the combined adoption of Agile and DevOps considering multiple perspectives of the software engineering business environment.

show abstract

Towards a benefits dependency network for DevOps based on a systematic literature review

Cited by 40 publications

References 56 publications

Agility in Software 2.0 -- Notebook Interfaces and MLOps with Buttresses and Rebars

Agility in Software 2.0 -- Notebook Interfaces and MLOps with Buttresses and Rebars

Dependency Management in Large-Scale Agile: A Case Study of DevOps Teams

Exploring the Benefits of Combining DevOps and Agile

Contact Info

Product

Resources

About