DevOps is a set of practices that combines software development (Dev) and IT operations (Ops). It aims to shorten the systems development life cycle and provide continuous delivery with high software quality. DevOps is complementary with Agile software development; several DevOps aspects came from the Agile methodology.
Other than it being a cross-functional combination of the terms and concepts for "development" and "operations," academics and practitioners have not developed a unique definition for the term "DevOps".[a][b][c][d] The idea behind this practice is to make delivery teams responsible for the production issues and fixes, whether legacy or new. In traditional practices, delivery would only be responsible for the changes put in by them, within the warranty period.
From an academic perspective, Len Bass, Ingo Weber, and Liming Zhu--three computer science researchers from the CSIRO and the Software Engineering Institute--suggested defining 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".
This section may lend undue weight to certain ideas, incidents, or controversies. (December 2018)
In 1993 the Telecommunications Information Networking Architecture Consortium (TINA-C) defined a Model of a Service Lifecycle that combined software development with (telecom) service operations. Some say that DevOps emerged in part as a reaction to the "top-down" proscriptive approach of ITIL in the 1990s. DevOps, as a "bottom-up" approach, gained traction and persisted because it was created by software engineers for software engineers, and is a flexible practice rather than a rigid framework.
In 2014, Lisa Crispin and Janet Gregory wrote the book More Agile Testing, containing a chapter on testing and DevOps.
The DevOps taxonomy was refined and made publicly available in 2021 through the release of a white paper titled, "The DevOps: A Concise Understanding to the DevOps Philosophy and Science". The DevOps taxonomy consists of Philosophy and Science, their respective branches (Epistemology and Ontology; Social and Applied) and sub-domains (Belief, Knowledge, and Truth; Sociology, Psychology, Economics, and Engineering) with provided instantiations (Agile, Quality Assurance, Lean; Culture Transformation, Faster Time to Market, and Automation).
As DevOps is intended to be a cross-functional mode of working, those who practice the methodology use different sets of tools--referred to as "toolchains"--rather than a single one. These toolchains are expected to fit into one or more of the following categories, reflective of key aspects of the development and delivery process.
Many of the ideas fundamental to DevOps practices are inspired by, or mirror, other well known practices such as Lean and Deming's Plan-Do-Check-Act cycle, through to The Toyota Way and the Agile approach of breaking down components and batch sizes.
The motivations for what has become modern DevOps and several standard DevOps practices such as automated build and test, continuous integration, and continuous delivery originated in the Agile world, which dates (informally) to the 1990s, and formally to 2001. Agile development teams using methods such as Extreme Programming couldn't "satisfy the customer through early and continuous delivery of valuable software" unless they subsumed the operations / infrastructure responsibilities associated with their applications, many of which they automated. Because Scrum emerged as the dominant Agile framework in the early 2000s and it omitted the engineering practices that were part of many Agile teams, the movement to automate operations / infrastructure functions splintered from Agile and expanded into what has become modern DevOps. Today, DevOps focuses on the deployment of developed software, whether it is developed via Agile or other methodologies.
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 organizational 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. Lean management and continuous delivery are fundamental to delivering value faster, in a sustainable way. Continuous delivery focuses on making sure the software is always in a releasable state throughout its lifecycle.
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.
DevSecOps is an augmentation of DevOps to allow for security practices to be integrated into the DevOps approach. The traditional centralized security team model must adopt a federated model allowing each delivery team the ability to factor in the correct security controls into their DevOps practices. Shifting security left is an approach to software security whereby security practices and testing are performed earlier in the development lifecycle.
BizOps is contrasted with DevOps because of its more integrated approach. While DevOps is more focused on IT and software development, BizOps integrates technology into daily organizational decisions and business operations.
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 is as much about culture, as it is about the toolchain.
Organizational culture is a strong predictor of IT and organizational performance. Cultural practices such as information flow, collaboration, shared responsibilities, learning from failures and new ideas are central to DevOps. Team-building and other employee engagement activities are often used to create an environment that fosters this communication and cultural change within an organization. DevOps as a service approach allows developers and operations teams to take greater control of their applications and infrastructure without hindering speed. It also transfers the onus of owning a problem on to the development team, making them much more careful in their stride.
The 2015 State of DevOps Report discovered that the top seven measures with the strongest correlation to organizational culture are:
1. Organizational investment
2. Team leaders' experience and effectiveness
3. Continuous delivery
4. The ability of different disciplines (development, operations, and infosec) to achieve win-win outcomes
5. Organizational performance
6. Deployment pain
7. Lean management practices
Companies with very frequent releases may require knowledge on DevOps. For example, the company that operates image hosting website Flickr developed a DevOps approach to support ten deployments a day. Daily deployment cycles would be much higher at organizations producing multi-focus or multi-function applications. Daily deployment is referred to as continuous deployment
To practice DevOps effectively, software applications have to meet a set of architecturally significant requirements (ASRs), such as: deployability, modifiability, testability, and monitor-ability.
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. Small size service allows the architecture of an individual service to emerge through continuous refactoring,.
Implementation of DevOps automation in the IT-organization is heavily dependent on tools, which are to cover different areas of the systems development lifecycle (SDLC):
DevOps practices, and their dependencies include a dependency network which connects potential benefits to an ordered chain of practices. Using this network organizations can choose a path that enables fulfillment of their goals.
Adoption of DevOps is being driven by many factors - including: