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This is an accepted version of this page This is the latest accepted revision, reviewed on 5 January 2025. Set of software development practices DevOps is a methodology integrating and automating the work of software development (Dev) and information technology operations (Ops). It serves as a means for improving and shortening the systems development life cycle. DevOps is complementary to ...
The book explores how software development teams using Lean Software and DevOps can measure their performance and the performance of software engineering teams impacts the overall performance of an organization. [36] [14] The book discusses their research conducted as part of the DORA team for the annual State of DevOps Reports. In total, the ...
The DSDM Agile Project Framework is an iterative and incremental approach that embraces principles of Agile development, including continuous user/customer involvement. DSDM fixes cost, quality and time at the outset and uses the MoSCoW prioritisation of scope into musts , shoulds , coulds and will not haves to adjust the project deliverable to ...
Agile software development is an umbrella term for approaches to developing software that reflect the values and principles agreed upon by The Agile Alliance, a group of 17 software practitioners in 2001. [1] As documented in their Manifesto for Agile Software Development the practitioners value: [2] Individuals and interactions over processes ...
A DevOps toolchain is a set or combination of tools that aid in the delivery, development, and management of software applications throughout the systems development life cycle, as coordinated by an organisation that uses DevOps practices.
Mobile DevOps is a set of practices that applies the principles of DevOps specifically to the development of mobile applications. Traditional DevOps focuses on streamlining the software development process in general, but mobile development has its own unique challenges that require a tailored approach. [ 1 ]
MLOps is the set of practices at the intersection of Machine Learning, DevOps and Data Engineering. MLOps or ML Ops is a paradigm that aims to deploy and maintain machine learning models in production reliably and efficiently. The word is a compound of "machine learning" and the continuous delivery practice (CI/CD) of DevOps in the software ...
Release managers are beginning to utilize tools such as application release automation and continuous integration tools to help advance the process of continuous delivery and incorporate a culture of DevOps by automating a task so that it can be done more quickly, reliably, and is repeatable. More software releases have led to increased ...