The term DevOps was first coined by Patrick Debois in the year 2009 and is formed by the combination of two words “Development” and “Operations”. It gives us a fair idea of what it means when we talk about the term “DevOps”.

An enterprise software development phrase, DevOps represents a type of agile relationship between development and IT operations. It aims to enhance and change this relationship between development and operations by facilitating better communication and collaboration between these two business processes.

Prior to DevOps, developers write the code as per the business requirements, a separate QA team quality tests the program in a remote development environment and if the requirements are matched the code is released to operations for deployment. Then groups for networking and databases are formed out of deployment teams. Every time a software program is given to a team it adds some blockages. The problem with this pattern is that when the teams work individually:

• Dev is often unacquainted with QA and Ops barriers that prevent the software program from working as required.
• QA and Ops usually work across many structures and have little knowledge of the business purpose and significance of the software.
• Each team has differing goals that can lead to incompetence and finger-pointing at each other when something goes wrong.

DevOps establishes collaborative cross-functional teams to address these challenges. These teams mutually share the responsibility of maintaining the system that runs the software and also prepares the software to operate on that system with better feedback.

DevOps addresses all of the above challenges by establishing collaborative cross-functional teams that share responsibility for maintaining the system that runs the software and preparing the software to run on that system with increased quality feedback and automation issues.

• Improve deployment frequency
• Achieve faster time to market
• Lower failure rate of new releases
• Shorten the lead time between fixes
• Improve mean time to recovery

Several phases to DevOps maturity are as follows:-

Before continuous integration, development teams would write a bunch of code for three to four months. Then those teams would merge their code in order to release it. The different versions of code would be so different and have so many changes that the actual integration step could take months. This process was very unproductive.

Continuous integration is the practice of quickly integrating newly developed code with the main body of code that is to be released, thus saving a lot of time when the team is ready to release the code.

Automation is required to successfully execute continuous integration. Continuous integration is often the first step down the path toward DevOps maturity.
Continuous integration process from a DevOps perspective involves checking your code in, compiling it into usable (often binary executable) code and running some basic validation testing.

Continuous delivery is an extension of continuous integration.
When executing continuous delivery, you add additional automation and testing so that you don’t just merge the code with the main code line frequently, but you get the code nearly ready to deploy with almost no human intervention.

It’s the practice of having the code base continuously in a ready-to-deploy state.

Continuous deployment, not to be confused with continuous delivery, is a practice of deploying all the way into production without any human intervention.

Teams that utilize continuous delivery don’t deploy untested code; instead, newly created code runs through automated testing before it gets pushed out to production. There’s an automated feedback loop that monitors quality and usage before the code is propagated further.

DevOps focuses heavily on establishing a collaborative culture and improving efficiency through automation with DevOps tools. While some organizations and people tend to value one more than the other, the reality is it takes a combination of both culture and tools to be successful.

DevOps culture is characterized by increased collaboration, decreasing silos, shared responsibility, autonomous teams, improving quality, valuing feedback and increasing automation

Here are some of the key tools and practices:-

A source code repository is a place where developers check-in and change code. It manages various versions of code that are checked in, so developers don’t write over each other’s work.

Source control has probably been around for forty years and it’s a major component of continuous integration. Popular source code repository tools are Git, Subversion, Cloudforce, Bitbucket and TFS.

A build server is an automation tool that compiles the code in the source code repository into an executable code base. Popular tools are Jenkins, SonarQube and Artifactory.

Configuration management defines the configuration of a server or an environment. Popular configuration management tools are Puppet and Chef.

Amazon Web Services and Microsoft Azure are examples of virtual infrastructures. Virtual infrastructures are provided by cloud vendors that sell infrastructure or platform as a service (PaaS). These infrastructures have APIs that allows you to programmatically create new machines with configuration management tools such as Puppet and Chef.

Virtual infrastructures combined with automation tools to empower organizations practising DevOps with the ability to configure a server without any fingers on the keyboard. If you want to test your brand-new code, you can automatically send it to your cloud infrastructure, build the environment and then run all of the tests without human intervention.

DevOps focuses on automated testing within your build pipeline to ensure that by the time that you have a deployable build, you are confident it is ready to be deployed. You can’t get to the point of continuous delivery where you’re fairly confident without any human intervention that your code is deployable without an extensive automated testing strategy. Popular tools are Selenium and Water.

A pipeline is like a manufacturing assembly line that happens from the time a developer says, “I think I’m done,” to the time that the code gets deployed in the production or a late-stage pre-production environment.