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Modern software development processes are not restricted to the discrete ALM/SDLC steps managed by different teams using multiple tools from different locations. [citation needed] Real-time collaboration, access to the centralized data repository, cross-tool and cross-project visibility, better project monitoring and reporting are the key to developing quality software in less time.
ModelOps (model operations or model operationalization), as defined by Gartner, "is focused primarily on the governance and lifecycle management of a wide range of operationalized artificial intelligence (AI) and decision models, including machine learning, knowledge graphs, rules, optimization, linguistic and agent-based models" in Multi-Agent Systems. [1] "
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 field. Machine learning models are tested and developed in isolated experimental systems.
"Deployment is defined as a specified set of activities designed to put into practice an activity or program of known dimensions. According to this definition, deployment processes are purposeful and are described in sufficient detail such that independent observers can detect the presence and strength of the "specific set of activities ...
CI/CD bridges the gaps between development and operation activities and teams by enforcing automation in building, testing and deployment of applications. CI/CD services compile the incremental code changes made by developers, then link and package them into software deliverables. [ 3 ]
Software as a service (SaaS / s æ s / [1]) is a cloud computing service model where the provider offers use of application software to a client and manages all needed physical and software resources. [2] Unlike other software delivery models, it separates "the possession and ownership of software from its use". [3]
Enterprise modelling is the process of building models of whole or part of an enterprise with process models, data models, resource models and/or new ontologies etc. It is based on knowledge about the enterprise, previous models and/or reference models as well as domain ontologies using model representation languages. [3]
A service delivery framework (SDF) is a set of principles, standards, policies and constraints to be used to guide the designs, development, deployment, operation and retirement of services delivered by a service provider with a view to offering a consistent service experience to a specific user community in a specific business context.