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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 ...
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 ...
Release engineering is often the integration hub for more complex software development teams, sitting at the cross between development, product management, quality assurance and other engineering efforts, also known as DevOps. Release engineering teams are often cast in the role of gatekeepers (e.g. at Facebook, Google, Microsoft) for certain ...
[3] [4] [5] As DevOps is a set of practices that emphasizes the collaboration and communication of both software developers and other information technology (IT) professionals, while automating the process of software delivery and infrastructure changes, its implementation can include the definition of the series of tools used at various stages ...
In software engineering, CI/CD or CICD is the combined practices of continuous integration (CI) and continuous delivery (CD) or, less often, continuous deployment. [1] They are sometimes referred to collectively as continuous development or continuous software development.
The scaled agile framework (SAFe) is a set of organization and workflow patterns intended to guide enterprises in scaling lean and agile practices. [1] [2] Along with disciplined agile delivery (DAD) and S@S (Scrum@Scale), SAFe is one of a growing number of frameworks that seek to address the problems encountered when scaling beyond a single team.