Contents
Definitions and history
Venn diagram showing DevOps as the intersection of development (software engineering), operations and quality assurance (QA)
The term DevOps has been used in multiple different contexts.[8]
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.[9]In recent years, more tangential DevOps initiatives have also evolved, such as OpsDev,[10] WinOps, [11], DevSecOps, and BizDevOps.[12]
DevOps toolchain
Illustration showing stages in a DevOps toolchain
- 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
Some categories are more essential in a DevOps toolchain than others; especially continuous integration (e.g. Jenkins) and infrastructure as code (e.g. Puppet).[16][17]
Relationship to other approaches
Agile
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.[18][19]Continuous delivery
Continuous delivery and DevOps have common goals and are often used in conjunction, but there are subtle differences.[20][21]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.[20]
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.[22] They are well communicated and collaborated internally, thus helping achieve faster time to market, with reduced risks.[18][23]
DataOps
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.[24] 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.[25]SciOps (Scientific DevOps)
Scientific DevOps refers to DevOps practices applied in the context of scientific computing.[26] While the tools and methodologies are the same, the goals are different: DevOps delivers a software product, while SciOps delivers scientific insights.[citation needed] An alternative interpretation of the term is as a specialization of DevOps.[citation needed]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)[27]. 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.[28]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.[29] While SRE predates the development of DevOps, they are generally viewed as independent trends.[30] Some aspects of DevOps have taken a similar approach.[31]Systems administration
DevOps is often viewed as an approach to applying systems administration work to cloud technology.[32]Goals
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).
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.[34]
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.[18]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%).[35]
Cultural change
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- Operations — seeks organizational stability
- Developers — seek change
- Testers — seek risk reduction[37]
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".[40][41]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.[42]
- 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.
Deployment
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;[45] this daily deployment cycle would be much higher at organizations producing multi-focus or multi-function applications. This is referred to as continuous deployment[46] or continuous delivery [47] and has been associated with the lean startup methodology.[48] Working groups, professional associations and blogs have formed on the topic since 2009.[4][49][50]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.[51] 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.[23] Because the size of each service is small, it allows the architecture of an individual service to emerge through continuous refactoring,[52] hence reducing the need for a big upfront design[citation needed] and allows for releasing the software early[citation needed] 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."[53]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.[54]
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[55] and cloud infrastructure — from internal and external providers;
- Increased usage of data center automation[56] and configuration management tools;
- Increased focus on test automation[57] and continuous integration methods;
- A critical mass of publicly–available best practices.
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