Roadmap you need get 45 LPA as a DevOps Engineer in 2026 (Beginner to Advanced)

Summary

The video presents a staged DevOps learning roadmap for beginners, emphasizing that DevOps is a connected workflow—not a checklist of tools to memorize. The goal is to understand how an application moves from a developer’s computer into a reliable, automated production environment.

The presenter cites a 2026 CNCF survey, saying that 98% of surveyed organizations have adopted cloud technologies and 82% of container users run Kubernetes in production. The central advice is to learn each technology well enough to use it in a practical project, then build on that knowledge in sequence.

Phase 1: Foundations

1. Understand basic computing and applications

   • Learn what a server is, how applications run, how files are stored, and how applications communicate with other systems.
   • Programming expertise is not required, but basic familiarity is useful.

2. Learn Linux

   • Practice navigating directories, creating and editing files, installing software, managing users and permissions, controlling processes, and using environment variables.
   • Learn to connect to another machine using SSH.
   • Practice project: Set up a Linux machine and manage it entirely from the terminal.

3. Learn networking fundamentals

   • Understand IP addresses, domain names, DNS, ports, and the basics of HTTP and HTTPS.
   • Be able to describe, at a high level, how a browser finds and communicates with a web server.

4. Learn Git and GitHub

   • Practice commits, branches, merges, pull requests, and remote repositories.
   • Focus on the everyday collaboration workflow rather than advanced commands.

5. Learn Bash scripting

   • Start automating routine terminal tasks with variables, conditionals, loops, functions, and simple scripts.
   • Add Python later if more capable automation is needed.

Milestone: Set up and connect to a Linux machine, run a program, track its code with Git, and automate a small task with a script.

Phase 2: Cloud Deployment and Automation

1. Learn one cloud platform

   • The presenter recommends AWS, while noting Azure and Google Cloud as alternatives.
   • Focus on virtual machines, storage, users and permissions, networking, and making an application accessible over the internet.
   • Learn what services do and how they fit together; don’t try to memorize every cloud offering.

2. Learn Docker

   • Understand images and containers.
   • Write a Dockerfile, expose ports, use environment variables, and store data in volumes.
   • Learn Docker Compose to run multiple components—such as an application and its database—together.

3. Learn CI/CD with GitHub Actions

   • Understand how a pipeline receives code changes, runs tests, builds the application, and deploys it.
   • Practice building a Docker image, securely handling sensitive values, and triggering deployment after a successful pipeline.

4. Learn infrastructure as code with Terraform

   • Learn the basics of resources, variables, outputs, and state.
   • Understand the plan and apply workflow.
   • Start with simple infrastructure rather than advanced modules.

Milestone: Build an end-to-end workflow: keep application code in GitHub, package it with Docker, provision AWS infrastructure with Terraform, and automate testing and deployment with GitHub Actions.

Phase 3: Managing Applications at Scale

1. Learn Kubernetes after Docker

   • Understand clusters, nodes, pods, deployments, and services.
   • Learn how Kubernetes supports scaling, self-healing, and rolling updates.
   • Deploy a small containerized application; prioritize understanding the components over memorizing commands.
   • Explore Helm afterward for packaging and managing Kubernetes applications.

2. Learn observability

   • Logs show what happened.
   • Metrics describe the system’s condition.
   • Traces follow a request across application services.
   • Explore Prometheus and Grafana for metrics and dashboards, and OpenTelemetry for collecting telemetry.
   • The aim is to diagnose problems in a running system, not necessarily to become a monitoring specialist.

3. Build security into everyday work

   • Never commit passwords or API keys to GitHub.
   • Learn to manage secrets and apply the principle of least privilege.
   • Keep applications and dependencies updated, and scan container images.
   • Apply these practices in projects rather than treating them as definitions to memorize.

4. Understand GitOps

   • In GitOps, the desired system configuration is stored in Git, and tools such as Argo CD work to keep the running environment aligned with it.
   • It is presented as a useful approach to understand, especially for seeing how larger teams manage deployments—not as a first topic to master.

Overall Lesson

The roadmap culminates in understanding the full application lifecycle: write code, track it in Git, package it with Docker, provision infrastructure with Terraform, deploy through CI/CD, run it on Kubernetes, and monitor and secure it.

The presenter advises learning through hands-on projects and experimentation rather than memorizing tool definitions or collecting courses. At the end, the presenter promotes a full AI DevOps masterclass on the channel as a resource for studying and practicing the roadmap in more depth.

Speakers and Sources Featured

• Speaker: The video’s presenter/narrator; no personal name is stated in the subtitles.
• Source cited by the presenter: The 2026 CNCF survey, referenced for cloud-adoption and Kubernetes-usage figures.
• Other named products and tools: AWS, Azure, Google Cloud, Linux, SSH, Git, GitHub, Bash, Python, Docker, Docker Compose, GitHub Actions, Terraform, Kubernetes, Helm, Prometheus, Grafana, OpenTelemetry, and Argo CD.