DevOps requires a cycle of delivery that includes preparation, development tests, deployment release, as well as monitoring and active collaboration between the various members of the team.
To understand the process further we'll take a closer take a look at the fundamental practices that make up DevOps:
Agile planning
In contrast to traditional methods of managing projects, Agile planning organizes work by dividing it into short iterations (e.g. sprints) to increase the frequency of releases. The team only has basic goals to be defined, while creating detailed plans for two iterations prior to. This allows flexibility and pivots after the ideas have been tested in an early increment of the product. If you want to master DevOps Models then consider taking DevOps Post Graduate Program.
Continuous development
The idea that continuous "everything" is a way of embracing the continuous or iterative process of software development in which all development work is split into smaller chunks to ensure faster and better quality production. Engineers write code in smaller pieces frequently throughout the day in order to make it quickly testable. Builds as well as unit test are also automated.
Continuous automated testing
A quality assurance team conducts the goal of committing code testing with automation tools such as Selenium, Ranorex, UFT and more. If vulnerabilities and bugs occur the code is sent back to engineers. This also involves the control of versions to identify problems with integration ahead of time. The Version Control System (VCS) lets developers record changes to files and then share the changes with others in the team regardless of location.
Continuous integration, continuous delivery (CI/CD)
The code that has passed automated tests is put into a shared repository that is hosted on servers. Continuous code submissions avoid a known as "integration hell" in which the differences between the individual codes and mainline files get so significant over time that integration is more time-consuming than the actual process of coding.
Continuous delivery, as described in our article dedicated to it, is a strategy that blends development tests, deployment, and testing into a more efficient process since it heavily depends on the automation. This allows for the automated transfer of updates to an environment for production.
Continuous deployment
At this point the code is distributed to run in production the public server. Code should be deployed in a manner that doesn't interfere with existing features and is accessible to an extensive number of users. Regular deployments allow the possibility of the use of a "fail quickly" method, which means that all new functions are tested, and validated in the early stages. There are many automated tools to help engineers to deploy an increment of a product. The most well-known are Puppet, Chef Azure Resource Manager, and Google Cloud Deployment Manager.
Continuous monitoring
The last stage that is part of the DevOps lifecycle is focused on the evaluation of the entire process. The purpose of monitoring is finding the weak points of an operation and then analyzing the feedback of the team as well as users to highlight any errors and enhance the functionality of the product.
Code for infrastructure
The concept of infrastructure as a code (IaC) is an approach to managing infrastructure that allows continual delivery as well as DevOps feasible. It involves using scripts to change your deployment environments (networks and virtual machines etc.).) to the desired configuration regardless of the initial state.
Without IaC engineers would have to manage each target environment separately which can become a difficult task when you're dealing with multiple environments to use for development as well as testing and production use.
With the environment set in a way that you can code it,
Test it in the same manner it tests the code source and
Make use of a virtual system which behaves as the production environment in order to test early.
If the need to scale occurs, the script will automatically set the necessary number of environments that are identical to the one.
Containerization
Virtual machines mimic hardware behavior to share computing resources with the physical machine. This lets you run multiple application environments and operating system (Linux as well as Windows Server) on a single physical server , or spreading an application over several physical devices.
Containers On the other hand are lighter and come with all the runtime components (files libraries, files etc.) however, they do not include complete operating systems, but only the necessary resources. Containers are employed in DevOps to deploy applications instantly across different environments. They are ideal for combining with the IaC method described previously. Containers can be evaluated in a single unit prior to deployment. Presently, Docker provides the most well-known container toolset.
Microservices
The microservice architectural model involves developing a single application as a collection of separate services that interact with each the other, yet are set up independently. When you build an application this way will allow you to separate the underlying issues, and ensure that the failure of one component will not impact the other functionality of the application. Due to the speed that they are deployed, the microservices are a great option for keeping the entire system in good order, and fix the issues on their own. Find out further about microservices and how they can modernize monolithic systems that are outdated by reading our blog post.
Cloud infrastructure
Nowadays, the majority of organizations utilize cloud hybrids that are a mixture of private and public ones. However, the trend towards cloud services that are fully public (i.e. that are managed and controlled by an external service like AWS and Microsoft Azure) continues. Although cloud infrastructure isn't an absolute necessity to DevOps implementation, it does provide the flexibility, toolsets, and the ability to scale applications. With the introduction of cloud-based serverless architectures DevOps-focused teams can significantly reduce their work by eliminating the server-management functions.
A key component of these processes is automation tools that help in the process. Here we will discuss the reasons and how to do it.
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