Introduction to DevOps: Practices and Tools

DevOps necessitates a delivery cycle that includes planning, development, testing, deployment, release, and monitoring, as well as active collaboration among team members.

Let's take a look at the fundamental practices that make up DevOps to further break down the process:

Agile planning

Sharing is a form of caring. This term, more than any other, encapsulates the DevOps concept by emphasizing the significance of teamwork. Sharing feedback, best practices, and knowledge among teams is critical because it fosters transparency, fosters collective intelligence, and removes restrictions. You don't want to put the entire development process on hold because the sole individual who understands how to accomplish particular jobs is on vacation or has quit.

Continuous development

Continuous "everything" refers to iterative or continuous software development, in which all development effort is separated into small chunks for better and faster results. Engineers contribute code in small bits several times a day so that it can be tested quickly. Additionally, code builds and unit testing are automated.

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Continuous automated testing

A quality assurance team uses automation tools like as Selenium, Ranorex, and UFT to perform committed code testing. Bugs and vulnerabilities that are discovered are reported to the engineering staff. This stage also includes version control in order to spot integration issues ahead of time. Developers can use a Version Control System (VCS) to track changes to files and share them with other team members regardless of their location.

Continuous integration and continuous delivery (CI/CD)

The code that passes automated tests is stored on a server in a single, shared repository. Frequent code contributions avoid "integration hell," which occurs when the differences between different development branches and the mainline code get so great over time that integrating them takes longer than actually developing.

Continuous delivery, as described in our dedicated article, is a method for combining development, testing, and deployment processes into a simplified process based on automation. This stage permits the distribution of code updates to a production environment on a regular basis.

Continuous deployment

At this point, the code is deployed to a public server for production use. Code must be delivered in a method that does not disrupt existing functionalities and can be accessed by a large number of people. Frequent deployment enables a "fail fast" strategy, in which new features are evaluated and certified as soon as possible. Engineers can use a variety of automated technologies to assist them to release a product increment. Chef, Puppet, Azure Resource Manager, and Google Cloud Deployment Manager are the most popular.

Continuous monitoring

The final stage of the DevOps lifecycle is dedicated to evaluating the entire process. Monitoring's purpose is to identify problematic areas of a process and analyze feedback from the team and users in order to disclose inaccuracies and improve the product's functionality.

Infrastructure as a code

Infrastructure as a code (IaC) is a method for managing the infrastructure that enables continuous delivery and DevOps. It comprises the use of scripts to set the deployment environment (networks, virtual machines, and so on) to the required configuration regardless of its original condition.

Engineers would have to treat each target environment separately without IaC, which would be a time-consuming operation given the number of diverse settings used for development, testing, and production.

Having the environment configured as code, you

It's possible to test it in the same way that you'd test the source code, and to test early, use a virtual computer that mimics a production environment.

When the requirement for scaling arises, the script can set the required number of environments to be consistent with each other automatically.

Containerization

Virtual machines imitate hardware behavior to share a real machine's computational resources, allowing various application environments or operating systems (Linux and Windows Server) to run on a single physical server or the distribution of an application across numerous physical computers.

Containers, on the other hand, are smaller and come with all runtime components (files, libraries, and so on), but they don't include entire operating systems, only the bare minimum. Containers are commonly used in DevOps to deploy apps quickly across multiple environments, and they work well with the IaC approach outlined above. Before deployment, a container can be tested as a whole. Docker is currently the most popular container toolkit.

Microservices

The microservice architecture approach comprises creating a single application out of a collection of distinct services that communicate with one another but are configured separately. You may isolate any emergent difficulties by building an application in this manner, ensuring that a failure in one service does not affect the remainder of the application's functionality. Microservices enable the entire system to remain stable while addressing problems in isolation, thanks to their high deployment pace. In our essay, we go over microservices and how to modernize legacy monolithic architectures.

Cloud infrastructure

Most businesses now employ hybrid clouds, which are a mix of public and private clouds. However, the trend toward completely public clouds (those maintained by a third-party provider such as Amazon Web Services or Microsoft Azure) continues. While cloud infrastructure isn't required for DevOps adoption, it does give apps more flexibility, toolkits, and scalability. DevOps-driven teams can drastically cut their work by essentially removing server-management activities thanks to the recent development of serverless designs on clouds.

Automation solutions that help with workflow are an important aspect of these operations. We'll explain why and how it's done further down.