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DevOps (a clipped compound of "development" and "operations") is a software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). The main characteristic of the DevOps movement is to strongly advocate automation and monitoring at all steps of software construction, from integration, testing, releasing to deployment and infrastructure management. DevOps aims at shorter development cycles, increased deployment frequency, and more dependable releases, in close alignment with business objectives.
- 1 Definitions and history
- 2 DevOps toolchain
- 3 Relationship to other approaches
- 4 Goals
- 5 Cultural change
- 6 Deployment
- 7 See also
- 8 References
- 9 Further reading
Definitions and history
At the 2008 Agile Toronto conference, Andrew Shafer and Patrick Debois introduced the term in their talk on "Agile Infrastructure". From 2009, the DevOps term has been steadily promoted and brought into more mainstream usage through a series of "devopsdays", which started in Belgium and has now spread to other countries.
The term DevOps has been used in multiple contexts.
A definition proposed by Bass, Weber, and Zhu, is:
DevOps is 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.
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:
- Code — code development and review, source code management tools, code merging
- Build — continuous integration tools, build status
- Test — continuous testing tools that provide feedback on business risks
- Package — artifact repository, application pre-deployment staging
- Release — change management, release approvals, release automation
- Configure — infrastructure configuration and management, Infrastructure as Code tools
- Monitor — applications performance monitoring, end–user experience
Note that there exist different interpretations of the DevOps toolchain (e.g. Plan, Create, Verify, Package, Release, Configure, and Monitor).
Relationship to other approaches
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.
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.
SciOps (Scientific DevOps)
Scientific DevOps refers to DevOps practices applied in the context of scientific computing. While the tools and methodologies are the same, the goals are different: DevOps delivers a software product, while SciOps delivers scientific insights. An alternative interpretation of the term is as a specialization of DevOps.
ResOps (Research DevOps)
Research DevOps groups together all the tools and techniques used to deliver and support research operations in cloud environments (i.e., data transfer or data storage). In addition, ResOps also focuses on the optimisation of research workloads for clouds, defining two main approaches: legacy, where on-prem infrastructure is replicated in the cloud environment, and cloud-first, where cloud computing paradigms are fully adopted when designing the workloads. Both approaches have their own advantages and disadvantages, and impact the efficiency of the designed solution.
Site reliability engineering
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 independent trends. Some aspects of DevOps have taken a similar approach.
The goals of DevOps span the entire delivery pipeline. They include:
- Improved deployment frequency;
- Faster time to market;
- Lower failure rate of new releases;
- Shortened lead time between fixes;
- 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.
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.
Views on the benefits claimed for DevOps
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%).
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DevOps is more than just a tool or a process change; it inherently requires an organizational culture shift. This cultural change is especially difficult, because of the conflicting nature of departmental roles:
- Operations — seeks organizational stability
- Developers — seek change
- Testers — seek risk reduction
DevOps as a job title
- Cattle not Pets: the paradigm of disposable server infrastructure.
- 10 deployments per day: the story of Flickr adopting DevOps.
Building a DevOps culture
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.
Architecturally significant requirements
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.
Scope of adoption
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:
- Use of agile and other development processes and methods;
- Demand for an increased rate of production releases — from application and business unit stakeholders;
- Wide availability of virtualized and cloud infrastructure — from internal and external providers;
- Increased usage of data center automation and configuration management tools;
- Increased focus on test automation and continuous integration methods;
- A critical mass of publicly–available best practices.
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.
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