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.
In 2009 Patrick Debois coined the term[failed verification] by naming a conference "devopsdays" which started in Belgium and has now spread to other countries.
Illustration showing stages in a DevOps toolchain
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:
ArchOps presents an extension for DevOps practice, starting from software architecture artifacts, instead of source code, for operation deployment.. ArchOps states that architectural models are first-class entities in software development, deployment, and operations.
Continuous delivery and DevOps have common goals and are often used in conjunction, but there are subtle differences.
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.
In 2003, Google developed site reliability engineering (SRE), an 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.
This section needs expansion. You can help by adding to it. (June 2018)
Faster mean time to recovery (in the event of a new release crashing or otherwise disabling the current system).
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.
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 changes 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 as a job title
While DevOps describes an approach to work rather than a distinct role (like system administrator), job advertisements are increasingly using terms like "DevOps Engineer".
While DevOps reflects complex topics, the DevOps community uses analogies to communicate important concepts, much like "The Cathedral and the Bazaar" from the open source community.
Cattle not Pets: the paradigm of disposable server infrastructure.
10 deployments per day: the story of Flickr adopting DevOps.
Building a DevOps culture
DevOps T-shirt worn at a computer conference.
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.
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.
This section needs expansion. You can help by adding to it. (June 2018)
DevOps automation is a software engineering practice, which aims at eliminating manual handoffs, aligning siloed Dev and Ops departments, and delivering release-driven systems through the utilization of automation tools in development, test, stage, and production environments. 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. 
Implementation of DevOps automation in the IT-organization is heavily dependent on tools,  which are required to cover different areas of the systems development lifecycle (SDLC):
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:
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