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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 ...
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.
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 ...
A research director with research firm Gartner proposed changing the term ALM to ADLM (Application Development Life-cycle Management) to include DevOps, the software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). [3]
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 ...
It combines workload automation and release-management tools as they relate to release packages, as well as movement through different environments within the DevOps pipeline. [5] ARA tools help regulate deployments, how environments are created and deployed, and how and when releases are deployed.