DevOps

Agile and DevOps serve complementary roles: 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.[22] Agile can be viewed as addressing communication gaps between customers and developers, while DevOps addresses gaps between developers and IT operations / infrastructure.[23] Also, DevOps has focus on the deployment of developed software, whether it is developed via Agile or other methodologies.[22].

ArchOps presents an extension for DevOps practice, starting from software architecture artifacts, instead of source code, for operation deployment.[24]. ArchOps states that architectural models are first-class entities in software development, deployment, and operations.

TestOps is to hardware development what DevOps is to software development. The idea is a toolchain that links design and test operations together. In the case of hardware, design means EDA tools and the CAD department, and test means electronic measurement equipment like oscilloscopes and so on.[25]

Continuous delivery and DevOps have common goals and are often used in conjunction, but there are subtle differences.[26][27]

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.[26]

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.[28] Lean management and continuous delivery are fundamental to delivering value faster, in a sustainable way.[14] Continuous delivery focuses on making sure the software is always in a releasable state throughout its lifecycle.[13] This makes it cheaper and less risky to deliver the software.[13]

Improved collaboration and communication both between and within organizational teams can help achieve faster time to market, with reduced risks.[29][30]

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.[31] 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.[32]

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.[33] While SRE predates the development of DevOps, they are generally viewed as being related to each other.[34]

DevOps is often viewed as an approach to applying systems administration work to cloud technology.[35]

WinOps is the term used for DevOps practices for a Microsoft-centric view.

Toyota production system, also known under the acronym TPS, was the inspiration for lean thinking with its focus on continuous improvement, kaizen, flow and small batches. The Andon cord principle to create fast feedback, swarm and solve problems stems from TPS. [36][37]

DevSecOps is an augmentation of DevOps to allow for security practices to be integrated into the DevOps approach. The traditional centralised 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.

While DevOps describes an approach to work rather than a distinct role (like system administrator), job advertisements are increasingly using terms like "DevOps Engineer".[45][46]

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.[47]

• Cattle not Pets: the paradigm of disposable server infrastructure.[48]
• 10 deployments per day: the story of Flickr adopting DevOps.

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.[13] Team-building and other employee engagement activities are often used to create an environment that fosters this communication and cultural change within an organization.[49] Team-building activities can include board games, trust activities, and employee engagement seminars.[50]

The 2015 State of DevOps Report discovered that the top seven measures with the strongest correlation to organizational culture are: 1. Organizational investment in DevOps:[14] 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.

To practice DevOps effectively, software applications have to meet a set of architecturally significant requirements (ASRs), such as: deployability, modifiability, testability, and monitorability.[57] 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.[30] Small size service allows the architecture of an individual service to emerge through continuous refactoring,[58] hence reducing the need for a big upfront design, allows for releasing the software early and continuously.

DevOps automation can be achieved by repackaging platforms, systems, and applications into reusable building blocks[59] through the use of technologies such as virtual machines and containerization.[60][61]

Implementation of DevOps automation in the IT-organization is heavily dependent on tools,[13][62] which are required to cover different areas of the systems development lifecycle (SDLC):

1. Infrastructure as code
2. CI/CD
3. Test automation
4. Containerization
5. Orchestration
6. Software deployment
7. Software measurement

Jabbari et al. [40] identified DevOps practices and their dependencies. They developed a benefits dependency network[63] which connects potential benefits to an ordered chain of practices. Using this network organizations can choose a path that enables fulfillment of their goals.

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."[64]

In 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.[65]

Adoption of DevOps is being driven by many factors – including:

1. Use of agile and other development processes and methods;
2. Demand for an increased rate of production releases – from application and business unit stakeholders;
3. Wide availability of virtualized[66] and cloud infrastructure – from internal and external providers;
4. Increased usage of data center automation[67] and configuration management tools;
5. Increased focus on test automation[68] and continuous integration methods;
6. A critical mass of publicly available best practices.