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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 ...
Version Control is an important link in a DevOps toolchain and a component of software configuration management. Version Control is the management of changes to documents, computer programs, large web sites, and other collections of information. [8] A summary of Version Control related activities are: Non-linear development; Distributed development
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 ...
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.
Software engineering is a field within computer science focused on designing, developing, testing, and maintaining of software applications. It involves applying engineering principles and computer programming expertise to develop software systems that meet user needs. [1] [2] [3] [4]