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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 ...
[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 ...
Top level Configuration Management Activity model. Configuration management (CM) is a management process for establishing and maintaining consistency of a product's performance, functional, and physical attributes with its requirements, design, and operational information throughout its life.
Gartner describes CCA as “Embodying lean, agile and collaborative concepts core to DevOps initiatives, CCA tools bring a newly found level of precision, efficiency and flexibility to the challenges of infrastructure and application configuration management.” [4]
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, a software development process or software development life cycle (SDLC) is a process of planning and managing software development.It typically involves dividing software development work into smaller, parallel, or sequential steps or sub-processes to improve design and/or product management.
A systems development life cycle is composed of distinct work phases that are used by systems engineers and systems developers to deliver information systems.Like anything that is manufactured on an assembly line, an SDLC aims to produce high-quality systems that meet or exceed expectations, based on requirements, by delivering systems within scheduled time frames and cost estimates. [3]
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 ...