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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. [1] DevOps is complementary to agile software development; several DevOps aspects came from the agile approach.
DevOps is a software engineering approach that centers around cultural change, specifically the collaboration of the various teams involved in software delivery (developers, operations, quality assurance, management, etc.), as well as automating the processes in software delivery.
Modern-day DevOps practices involve: continuous development, continuous testing, continuous integration, continuous deployment, and; continuous monitoring; of software applications throughout its development life cycle. The CI/CD practice, or CI/CD pipeline, forms the backbone of modern day DevOps operations.
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.
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]
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 .
Within a project life cycle, there are generally one or more phases that are associated with the development of the product, service, or result. These are called a development life cycle (...) Adaptive life cycles are agile, iterative, or incremental. The detailed scope is defined and approved before the start of an iteration.
DataOps is a set of practices, processes and technologies that combines an integrated and process-oriented perspective on data with automation and methods from agile software engineering to improve quality, speed, and collaboration and promote a culture of continuous improvement in the area of data analytics. [1]
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