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|Paradigms and models|
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DevOps (a clipped compound of "development" and "operations") is a software development methodology that combines software development (Dev) with information technology operations (Ops). The goal of DevOps is to shorten the systems development life cycle while also delivering features, fixes, and updates frequently in close alignment with business objectives. The DevOps approach is to include automation and event monitoring at all steps of the software build.
Academics and practitioners have not developed a unique definition for the term "DevOps".
From an academic perspective, Len Bass, Ingo Weber, and Liming Zhu--computer science researchers from the Software Engineering Institute--suggested to define DevOps as "a set of practices intended to reduce the time between committing a change to a system and the change being placed into normal production, while ensuring high quality".
The term DevOps, however, has been used in multiple contexts.
As DevOps is intended to be a cross-functional mode of working, rather than a single DevOps tool, there are sets (or "toolchains") of multiple tools. Such DevOps tools are expected to fit into one or more of these categories, reflective of key aspects of the development and delivery process:
Note that there exist different interpretations of the DevOps toolchain (e.g. Plan, Create, Verify, Package, Release, Configure, and Monitor).
The need for DevOps arose from the increasing success of agile software development, as that led to organizations wanting to release their software faster and more frequently. As they sought to overcome the strain this put on their release management processes, they had to adopt patterns such as application release automation, continuous integration tools, and continuous delivery.
Another practice that rose from DevOps is BizDevOps which inserts business drivers as aspect equal to development and operations.
While continuous delivery is focused on automating the processes in software delivery, DevOps also focuses on the organization change to support great collaboration between the many functions involved.
DevOps and continuous delivery share a common background in agile methods and lean thinking: small and frequent changes with focused value to the end customer. They are well communicated and collaborated internally, thus helping achieve faster time to market, with reduced risks.
The application of continuous delivery and DevOps to data analytics has been termed DataOps. DataOps seeks to integrate data engineering, data integration, data quality, data security, and data privacy with operations. It applies principles from DevOps, Agile Development and the statistical process control, used in lean manufacturing, to improve the cycle time of extracting value from data analytics.
OpsDev emphasizes operations over development.
In 2003, Google developed site reliability engineering, a new approach for releasing new features continuously into large-scale high-availability systems while maintaining high-quality end user experience. While SRE predates the development of DevOps, they are generally viewed as being related to each other. Some aspects of DevOps have taken a similar approach.
WinOps is the term used for DevOps practices for a Microsoft-centric view.
The goals of DevOps span the entire delivery pipeline. They include:
Simple processes become increasingly programmable and dynamic, using a DevOps approach. DevOps aims to maximize the predictability, efficiency, security, and maintainability of operational processes. Very often, automation supports this objective.
DevOps integration targets product delivery, continuous testing, quality testing, feature development, and maintenance releases in order to improve reliability and security and provide faster development and deployment cycles. Many of the ideas (and people) involved in DevOps came from the enterprise systems management and agile software development movements.
Companies that practice DevOps have reported significant benefits, including: significantly shorter time to market, improved customer satisfaction, better product quality, more reliable releases, improved productivity and efficiency, and the increased ability to build the right product by fast experimentation.
However, a study released in January 2017 by F5 of almost 2,200 IT executives and industry professionals found that only one in five surveyed think DevOps had a strategic impact on their organization despite rise in usage. The same study found that only 17% identified DevOps as key, well below software as a service (42%), big data (41%) and public cloud infrastructure as a service (39%).
DevOps initiatives can create cultural change in companies  by transforming the way operations, developers, and testers collaborate during the development and delivery processes. Getting these groups to work cohesively is a critical challenge in enterprise DevOps adoption.
DevOps principles demand strong interdepartmental communication--team-building and other employee engagement activities are often used--to create an environment that fosters this communication and cultural change, within an organization. Team-building activities can include board games, trust activities, and employee engagement seminars.
Companies with very frequent releases may require a DevOps awareness or orientation program. For example, the company that operates the image hosting website Flickr developed a DevOps approach, to support a business requirement of ten deployments per day; this daily deployment cycle would be much higher at organizations producing multi-focus or multi-function applications. This is referred to as continuous deployment or continuous delivery  and has been associated with the lean startup methodology.Working groups, professional associations and blogs have formed on the topic since 2009.
To practice DevOps effectively, software applications have to meet a set of architecturally significant requirements (ASRs), such as: deployability, modifiability, testability, and monitorability. These ASRs require a high priority and cannot be traded off lightly.
Although in principle it is possible to practice DevOps with any architectural style, the microservices architectural style is becoming the standard for building continuously deployed systems. Because the size of each service is small, it allows the architecture of an individual service to emerge through continuous refactoring, hence reducing the need for a big upfront design and allows for releasing the software early and continuously.
Some articles in the DevOps literature assume, or recommend, significant participation in DevOps initiatives from outside an organization's IT department, e.g.: "DevOps is just the agile principle, taken to the full enterprise."
A survey published in January 2016 by the SaaS cloud-computing company RightScale, DevOps adoption increased from 66 percent in 2015 to 74 percent in 2016. And among larger enterprise organizations, DevOps adoption is even higher -- 81 percent.
Adoption of DevOps is being driven by many factors -- including:
DevOps automation can be achieved by repackaging platforms, systems, and applications into reusable building blocks through the use of technologies such as virtual machines and containerization. 
DevOps transformation is the process of transforming and adapting a software development methodology in accordance with agile development methods and extending this across the full organisation value stream. DevOps transformation usually covers at least the following three dimensions: people, technology and process. The people dimension covers culture, technology includes automation and process includes governance.
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