A Survey of DevOps Concepts and Challenges

Leite, Leonardo; Rocha, Carla; Kon, Fábio; Milojicic, Dejan; Meirelles, Paulo

doi:10.1145/3359981

Cited by 316 publications

(219 citation statements)

References 67 publications

(203 reference statements)

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“…The goals of DevOps include business outcomes such as organization vision and organizational interest. 83 We grouped all the challenging factors related to business dimension of DevOps in the business category ( Figure 6), which illustrates that DevOps could achieve the desired goals by tackling all the related factors in the business category.…”

Section: Businessmentioning

confidence: 99%

“…Similarly, the DevOps practices are based on the ideas of developing a pool of people from the development and operations teams through a collaborative culture. 83 The people-centric DevOps challenging factors are grouped in the people category. It demonstrates the DevOps process intended to develop collaborative organizational culture and bridge the gap of knowledge and data sharing across the DevOps silos.…”

Section: Peoplementioning

confidence: 99%

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Multicriteria decision‐making taxonomy for DevOps challenging factors using analytical hierarchy process

Khan

Shameem²

2020

J Software Evolu Process

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Development and operations (DevOps) practices significantly accelerate and automate the continuous delivery and deployment of software systems. However, adopting DevOps concepts is not a straightforward job. Most organizations are not able to keep pace with the rhythm of continuous delivery and deployment, which are key DevOps attributes. Despite the significance of DevOps programs, it is still unknown why software development firms are demotivated or unable to adopt them. We tried to fill this gap by investigating, prioritizing, and developing the taxonomy of the key factors that could impact the adaptation and implementation of DevOps practices. We extracted a total of 16 factors from the available literature and empirically assessed them using the survey approach. The identified factors are further classified into three core categories of the software process improvement (SPI) manifesto. The analytical hierarchy process (AHP) approach was used to calculate the prioritization weight for each factor and present it as a taxonomy. The developed taxonomy provides a roadmap to tackle the key challenges to implementing DevOps and offers suggestions for streamlining DevOps practices.

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Section: Businessmentioning

confidence: 99%

Section: Peoplementioning

confidence: 99%

Multicriteria decision‐making taxonomy for DevOps challenging factors using analytical hierarchy process

Khan

Shameem²

2020

J Software Evolu Process

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“…Tensions frequently arise as developers try to meet customer demands by pushing new software releases while operations tries to maintain stability and reliability of software in production [4,5]. Yet, business increasingly demands more frequent releases and cannot afford for delivery of software into production to be a time-consuming, stressful and errorprone process [6].…”

Section: Introductionmentioning

confidence: 99%

A Survey of DevOps in the South African Software Context

Rowse¹,

Cohen²

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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This study investigated DevOps practices and experiences in the South African software development context, along with associated perceptions of benefits and challenges. Survey data collected from a sample of 80 software development professionals showed that more frequent builds, earlier detection of bugs and reduced project lead times were the top three benefits, while getting DevOps capable members into a team, finding experienced professionals to support DevOps practice and changing deep-seated company culture to support DevOps were the top three challenges. DevOps practices are still emerging. Although 85% of respondents report continuous integration as a frequent practice, only 54% report using continuous deployment frequently. The biggest reported impacts of DevOps on software development culture were in making development team members aware of operational faults, responsible for quality assurance, and responsible for deployments. Realisation of benefits from DevOps depends largely on a culture change. Results are useful for guiding organisations considering DevOps adoption.

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“…Over the last decade, DevOps methods and tools have been successfully implemented and adopted by companies to boost automation and efficiency of the engineering process. The term DevOps was coined in 2009 [7] and became popular among companies and practitioners [25] and, subsequently, among researchers and academia. Jabbari et al [23] define DevOps as " [...]…”

Section: Introductionmentioning

confidence: 99%

DevOpsML

Colantoni

Berardinelli

Wimmer

2020

Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedi

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DevOps and Model Driven Engineering (MDE) provide differently skilled IT stakeholders with methodologies and tools for organizing and automating continuous software engineering activities-from development to operations, and using models as key engineering artifacts, respectively. Both DevOps and MDE aim at shortening the development life-cycle, dealing with complexity, and improve software process and product quality. The integration of DevOps and MDE principles and practices in low-code engineering platforms (LCEP) are gaining attention by the research community. However, at the same time, new requirements are upcoming for DevOps and MDE as LCEPs are often used by non-technical users, to deliver fully functional software. This is in particular challenging for current DevOps processes, which are mostly considered on the technological level, and thus, excluding most of the current LCEP users. The systematic use of models and modeling to lowering the learning curve of DevOps processes and platforms seems beneficial to make them also accessible for non-technical users. In this paper, we introduce DevOpsML, a conceptual framework for modeling and combining DevOps processes and platforms. Tools along with their interfaces and capabilities are the building blocks of DevOps platform configurations, which can be mapped to software engineering processes of arbitrary complexity. We show our initial endeavors on DevOpsML and present a research roadmap how to employ the resulting DevOpsML framework for different use cases. CCS CONCEPTS • Software and its engineering → Abstraction, modeling and modularity; Integration frameworks; Software configuration management and version control systems.

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A Survey of DevOps Concepts and Challenges

Cited by 316 publications

References 67 publications

Multicriteria decision‐making taxonomy for DevOps challenging factors using analytical hierarchy process

Multicriteria decision‐making taxonomy for DevOps challenging factors using analytical hierarchy process

A Survey of DevOps in the South African Software Context

DevOpsML

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