在业务发展比较快的情况下，从几台服务器，到几十台服务器，再到几百台服务器，批量运维的需求很自然就产生了，老板也希望越少的人干越多的活。现在也有不少开源的批量运维工具，也都比较成熟了，比如puppet、chef、ansible（1.8以后变化成rpc了）、saltstack。puppet和chef都是ruby做的，实话实说，ruby的熟手中国市面上很少，比python不是难招一点。我个人比较推荐使用ansible或者saltstack，这两个系统都是python写的，代码质量和社区活跃度都挺不错的。ansible有官方的web ui——Tower，ansible在两年前还是很火的，主要是基于ssh进行socket的shell操作，现在在变化目前地想让其更快一点，实际还不如saltstack好用，所以我们也在重新做一套自己用起来更顺手的WEB UI。
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.
Venn diagram showing DevOps as the intersection of development (software engineering), operations and quality assurance (QA)
In 2009 Patrick Debois coined the term by naming a conference “devopsdays”
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.
In recent years, more tangential DevOps initiatives have also evolved, such as OpsDev,
Illustration showing stages in a DevOps toolchain
Illustration showing stages in a DevOps toolchain
See also: 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.
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).
Some categories are more essential in a DevOps toolchain than others; especially continuous integration (e.g. Jenkins) and infrastructure as code (e.g. Puppet).
Relationship to other approaches
Main article: Agile software development
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.
Main article: Continuous delivery
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.
Main article: 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.
Site reliability engineering
Main article: 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.
This section needs expansion. You can help by adding to it. (June 2018)
DevOps is often viewed as an approach to applying systems administration work to cloud technology.
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%).
DevOps initiatives can create cultural change in companies
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.
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;
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. 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.