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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 ...
Frequent merging of several small changes into a main branch. Continuous delivery Producing software in short cycles with high speed and frequency so that reliable software can be released at any time, with a simple and repeatable deployment process when deciding to deploy. Continuous deployment Automatic rollout of new software functionality.
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 ...
The main difference between agile and iterative development is that agile methods complete small portions of the deliverables in each delivery cycle (iteration), [126] while iterative methods evolve the entire set of deliverables over time, completing them near the end of the project. Both iterative and agile methods were developed as a ...