DevOps Tutorial: A Step-by-Step Guide for Beginners in 2025

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DevOps Tutorial: A Step-by-Step Guide for Beginners in 2025

Last updated on July 5th, 2025

DevOps Tutorial: A Step-by-Step Guide for Beginners in 2025

The Grand View Research study forecasts that the DevOps market will reach US$12.85 billion by 2025. According to the rankings of Glassdoor 50 Best Jobs in America for 2021, DevOps engineer stands in the 5th position. “The role of DevOps Engineer has seen a 225% jump in postings on Indeed,” according to an SD Times report. According to Indeed and AngelList, 80% of the companies pay more than $90,000 starting salary to a DevOps Engineer. Also, 35% pay at least $115,000, and 17% pay more than $125,000. So this blog on DevOps Tutorial will be helpful in covering all the major concepts of DevOps.

What is DevOps?

The word DevOps is a combination of two words Development and Operations. Before getting into what DevOps is, let us get an idea about the two teams involved in software development. The development team is responsible for developing, designing, and building the application. The operation team deals with the deployment and testing of the application. If there are problems with the application, the operation team also provides feedback to the development team. Now let us get to the history of DevOps.

Principal Advantages:

  •  Quicker updates and releases of software
  •  Enhanced cooperation among groups
  •  Early problem identification through ongoing observation
  •  Improved security using DevSecOps techniques

Increased stability and scalability in production settings

DevOps is used by companies like Netflix, Amazon, and Google to ship code hundreds of times a day, guaranteeing uptime and quick innovation

DevOps Tutorial for Beginners | Learn DevOps in 7 Hours – Full Course | DevOps Training | Edureka

This Edureka DevOps Tutorial for Beginners will help you learn DevOps concepts and DevOps tools.

History of DevOps

Let us see some important events of DevOps :

  • 2007-2008: The DevOps idea was started
  • 2009: In the initial stage the first conference was ” Deploys a day: Dev and Ops cooperation of flicker.” Another conference called “DevOps Days in Ghent, Belgium” also happened.
  • 2010: DevOps days conference happened in the United States at mount view, calif.
  • 2012: Allana browns at puppet creates a state of DevOps report
  • 2014: Publishing the annual “State of DevOps report”
  • 2017: Forrester Research calls 2017 “The Year of DevOps”
  • 2018: 30 DevOps day conferences were scheduled across the united states.

DevOps Lifecycle: An Overview of the Phases

The various stages of the DevOps lifecycle are all intended to produce software consistently and dependably:

  1. Activities for Continuous Development: Coding, Planning
    • Tools: Visual Studio Code, Jira, Confluence, and Git
    • Objective: Facilitate regular code updates and teamwork
  2. Activities for Continuous Development: Coding, Planning
    • Tools: Visual Studio Code, Jira, Confluence, and Git
    • Objective: Facilitate regular code updates and teamwork
  3. Activities for Continuous Development: Coding, Planning
    • Tools: Visual Studio Code, Jira, Confluence, and Git
    • Objective: Facilitate regular code updates and teamwork

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Why did we need DevOps?

As we know about the problems faced in traditional models like in the waterfall model, there is a problem of a one-way stream of work, due to which if there is any mistake, the whole process repeats, and there is no interaction with customers. Now, this is solved in agile by splitting the whole development plan into several iterations for better production efficiency. The agile model also includes customer interaction with the company to rectify mistakes. But there is another problem faced in Agile too.

Here, the problem arises when the development team continuously changes the code for better performance and sends the code to the operations team for testing. But there may be a delay in the operations team feedback in situations like if the developers sent code for review at night but due to the unavailability of the operations team, there will be a delay in the project feedback.

So, DevOps is the solution to this problem. DevOps is a practice or a methodology in which the development and operations teams work together by including automation at the initial stages. So they can work on rapidly changing systems, fix bugs, and help to deliver a good quality of software in time.

As DevOps practices continue to evolve, many organizations are transitioning from SVN (Subversion) to Git to enable faster development cycles, better branching strategies, and improved CI/CD integration. However, migrating a large SVN repository (1.4TB or more) into Git can be a challenging process that requires careful planning.

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Waterfall Model

Let’s consider traditionally developing software using a Waterfall Model in this Devops Tutorial.

Essential DevOps Tools and Hands-On Labs

Here’s a breakdown of critical tools used in each DevOps phase with example labs:

Phase Tool Hands-On Example
Source Code Mgmt Git, GitHub Push/pull code, manage branches, pull requests
CI/CD Jenkins, GitHub Actions Create Jenkinsfile, trigger builds
Containerization Docker Create Dockerfile, run and deploy a container
Orchestration Kubernetes Deploy app using kubectl and Helm

Waterfall Model Challenges

The Water-fall model worked fine and served well for many years however it had some challenges. In the following diagram the challenges of Waterfall Model are highlighted.

In the above diagram in this Devops Tutorial you can see that both Development and Operations had challenges in the Waterfall Model. From Developers point of view there were majorly two challenges:

  • After Development, the code deployment time was huge.
  • Pressure of work on old, pending and new code was high because development and deployment time was high. On the other hand, Operations was also not completely satisfied.

There were four major challenges they faced as per the above diagram in this Devops Tutorial:

  1. It was difficult to maintain ~100% uptime of the production environment.
  2. Infrastructure Automation tools were not very affective.
  3. Number of severs to be monitored keeps on increasing with time and hence the complexity.
  4. It was very difficult to provide feedback and diagnose issue in the product.

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