Exploring the DevOps Lifecycle Phases

Exploring the DevOps Lifecycle phases

Traditional life cycle phases and associated problems

The traditional development life cycle follows the typical development, testing, integration, and deployment flow. This typical approach is simple to follow, but crops up complexities in later phases leading to over budgeting and delay in the release

How the DevOps Lifecycle is different from the traditional one

DevOps takes the “continuous” approach where Exploring the DevOps Lifecycle Phasesin each phase is repeated until the release. It has phases such as continuous development, integration, testing, deployment, and monitoring.

Let’s explore these –

Exploring the DevOps Lifecycle Phases
Exploring the DevOps Lifecycle Phases
  1. Continuous Development

This phase includes project planning and code development. The project plan should consider the needs of all the stakeholders and plan for the necessities like resources, scope, a schedule, budget, and risk management. Developers then start their development according to planning. Programming languages, Version control tools, and packaging tools play a role in this phase.

2. Continuous Testing –

Developed code is continuously tested for bug creeps. Testing is automated. Various testing automation tools include Selenium (Automated testing), TestNG(Test report generation), and JUnit. These tools allow QAs to test multiple code bases thoroughly in parallel to ensure no flaws in the functionality. In this phase, Docker Containers can simulate the test environment. The entire testing process can be automated with Jenkins.

3. Continuous Integration –

This stage has proven revolutionary as the traditional cycle involved integration as an end phase. This approach leads to late detection of various problems leading to late delivery and increased cost. In DevOps, when new code is ready, it is tested and integrated with the existing code. This keeps the application up-to-date, and changes are reflected in the end users. Jenkins plays an important role in the phase by fetching the code from the repository and building it. The build is then sent to either the test or production servers.

4. Continuous Deployment –

This is the stage where the code is deployed to the production servers.t Configuration management and Containerization tools play a vital role in this phase. This set of tools here helps in achieving Continuous Deployment (CD). Configuration Management is the act of establishing and maintaining consistency in an application’s functional requirements and performance. Some popular tools are Puppet, Chef, SaltStack, and Ansible.

Containerization tools also play an equally important role in the deployment stage. Docker and Vagrant are the popular tools used for this purpose. Containerization eliminates this problem by bundling the application code with the related configuration files, libraries, and dependencies required to run. This single software package or “container” is removed from the host operating system. Hence, it stands alone and becomes portable—able to run across any platform or cloud, free of issues.

5. Continuous Monitoring –

This is a crucial stage of the DevOps life cycle, where you continuously monitor the performance of your application. Monitoring encompasses the functionality and performance analysis of the application. The root cause behind the issues is identified and fixed. It involves the Operations team, who will monitor the user activity for bugs or improper system behaviour. The popular tools used are Splunk, ELK Stack, Nagios, NewRelic, and Sensu. These tools help you closely monitor the application’s performance and the servers and enable you to check the system’s health proactively.

6. Benefits and takeaway –

These DevOps stages are continuously carried out until you achieve the desired product quality. Therefore, almost all major IT companies have shifted to DevOps for building their products. They can also improve productivity and increase the systems’ reliability, reducing IT support costs. Any major issues, if found, are reported to the development team so that they can be fixed in the continuous development phase. This leads to a faster resolution of the problems.

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