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DevOps Roadmap

DevOps Engineer

DevOps is not a tool, it is shortening the loop between writing code and running it safely in production. The sequence that works is Linux and networking first, then Git and scripting, then containers, then CI/CD, then one cloud, then infrastructure as code, and only then Kubernetes — which is where people who skipped the foundations get stuck.

Intermediate~8 months6 stages33 steps

By the end: Take an application from a repository to a monitored production deployment.

The DevOps Engineer Roadmap

1

Linux and Networking~2 months

Understand the machine before automating it. Everything later assumes this.

  1. Linux command line

    Files, permissions, processes and logs. You will live here, mostly over SSH with no GUI.

  2. Processes and services

    systemd, daemons and what actually happens when something will not start.

  3. Networking fundamentals

    IP, DNS, TCP, TLS and ports. Most "the deploy is broken" turns out to be one of these.

  4. SSH and remote access

    Keys not passwords, config files, tunnels and agent forwarding.

  5. Shell scripting

    Automate the repetitive work. Your first pipelines will be shell whether you plan that or not.

  6. Scheduling with cron

    Recurring jobs, and why the environment inside cron is not the one in your shell.

2

Git and Collaboration~1 month

Source control is the entry point for every pipeline you will build.

  1. Git in depth

    Beyond commit and push: rebase, cherry-pick, bisect and recovering from a bad reset.

  2. Branching strategy

    Trunk-based or GitFlow — pick one deliberately, because it shapes your release process.

  3. Versioning and releases

    Semantic versioning and conventional commits, so changelogs and releases can be automated.

  4. One scripting language

    Python or Go for the tools that outgrow bash — which happens sooner than expected.

3

Containers~1 month

Package an application so it runs identically everywhere.

  1. Docker fundamentals

    Images, layers, volumes and networks. Build one by hand before generating any.

  2. Writing a good Dockerfile

    Multi-stage builds, cache-friendly layer order and a non-root user.

  3. Docker Compose

    Run an app with its database and cache locally, in one file.

  4. Registries and image security

    Push, tag, scan. A base image with known CVEs is a supply-chain problem you inherited.

  5. Reverse proxies

    Nginx in front: TLS termination, routing and static files.

4

CI/CD~1 month

Make going to production boring.

  1. Pipeline fundamentals

    Build, test, scan, deploy. Every tool differs in syntax and agrees on the shape.

  2. GitHub Actions

    Workflows, runners, matrices and caching, on the platform most teams already use.

  3. Another CI system

    GitLab CI or Jenkins, so you can read a pipeline you did not write.

  4. Deployment strategies

    Blue-green, canary and rolling — and how each one rolls back.

  5. Secrets in pipelines

    Injected at runtime, masked in logs, rotated on a schedule. Never committed.

  6. Feature flags

    Optional

    Separate deploy from release, so shipping code and enabling it are different decisions.

5

Cloud and Infrastructure as Code~2 months

Stop configuring servers by hand.

  1. One cloud, properly

    AWS by default. Compute, storage, networking and identity — the four primitives everything else sits on.

  2. Cloud IAM

    Least privilege, roles over long-lived keys. The most commonly misconfigured thing in cloud.

  3. Cloud networking

    VPCs, subnets, security groups and why your instance cannot reach the internet.

  4. Terraform

    Declare infrastructure, review the plan, apply. State management is the part that bites.

  5. Configuration management

    Ansible for the machines that are not immutable — and there are always some.

  6. Cost awareness

    Know what your architecture costs. Nobody else on the team is going to check.

6

Kubernetes and Observability~1 month

Only now — with Linux, containers and one cloud already understood.

  1. Kubernetes fundamentals

    Pods, deployments, services and the reconciliation loop that drives all of it.

  2. Kubernetes networking and storage

    Services, ingress, persistent volumes — where most real cluster problems live.

  3. Helm and configuration

    Package and template manifests instead of copying YAML between environments.

  4. GitOps

    The repository is the desired state and a controller reconciles the cluster to it.

  5. Monitoring and alerting

    Prometheus and Grafana, with alerts that fire on symptoms rather than on causes.

  6. Incident response and SRE

    On-call, postmortems and error budgets. The cultural half of the job, and the half that lasts.

Frequently Asked Questions

Can I get into DevOps without being a developer first?

Yes, and many arrive from system administration or support. You do need to write code — scripting, pipeline definitions and infrastructure as code are all code, and get reviewed like code. What you do not need is years of application development.

Do I need to learn Kubernetes straight away?

No, and starting there is the classic mistake. Kubernetes is a distributed system that assumes you already understand Linux, networking, containers and process management. Learn Docker and deploy something to a plain server first; Kubernetes then makes sense instead of feeling like magic.

Which cloud should I learn?

AWS has the largest market share and the most job postings, so it is the safe default. Azure dominates in enterprises with Microsoft estates and GCP is strong in data and ML. Learn one deeply — the second cloud takes weeks, because the concepts are identical and only the names change.

Is DevOps a good first job?

It is a difficult first job, because you are trusted with production on day one and the blast radius of a mistake is large. A common and effective route is one to two years in development, support or sysadmin work first, then a move across.

Related Reading

#DevOpsEngineer#DevOps#CICD#Docker#Kubernetes#Linux#InfrastructureAsCode#Infrastructure#Automation#SiteReliability#Roadmap#CareerPath#LearningPath#SkillVeris#Intermediate#DevopsRoadmap#DevopsSkills#KubernetesRoadmap

Frequently Asked Questions

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What is a learning path on SkillVeris and how does it work?
A learning path is a structured sequence of courses that takes you from beginner to job-ready in a specific career, such as AI Engineer or DevOps Engineer. Each path orders courses logically so every topic builds on the last, and each course inside it includes 24–40 lessons, module assessments and a final exam.
Which career roadmaps does SkillVeris offer for free?
SkillVeris offers free career roadmaps including AI Engineer, DevOps Engineer, Cloud Engineer, Data Engineer, Full Stack Java Developer, Frontend Engineer, MERN Stack, Data Scientist, Web & Cloud Security Engineer and Mobile Developer. Every path is completely free, with structured courses, assessments and certificates, making them practical options for learners in India and worldwide.
How do I become an AI engineer using the SkillVeris AI Engineer path?
Follow the AI Engineer path in order: start with Python for AI and ML, then progress through Large Language Models, Retrieval-Augmented Generation, AI Agents, PyTorch, TensorFlow and Keras, Hugging Face Transformers and MLOps. Each course has 24–40 lessons plus assessments, so you build skills progressively and earn certificates as proof.
Is structured learning better than random tutorials for becoming a developer?
Yes, structured learning usually works better because topics are sequenced so each concept builds on the previous one, which random tutorials rarely guarantee. SkillVeris paths remove the guesswork of what to learn next, add assessments to confirm understanding, and give you a clear finish line with a certificate at the end of each course.
How long does it take to complete a career roadmap on SkillVeris?
It depends on the path length and your weekly study time. Each structured course contains 24–40 lessons with listed estimated hours, and a full career roadmap typically spans several courses. Many learners studying a few hours a week complete individual courses in weeks; consistency matters far more than speed.
Do I need a computer science degree to follow a career roadmap?
No, you do not need a computer science degree. SkillVeris learning paths start from beginner-friendly foundations and progress step by step, so career changers and self-taught learners can follow them fully. The Learn Through Hobbies method also explains concepts using cricket, music, gaming, cooking and more, which helps non-CS backgrounds grasp ideas quickly.
Are SkillVeris learning paths really free, even for Indian students?
Yes, every learning path on SkillVeris is completely free, including all 37 live courses, assessments and certificates. There are no hidden fees, trials or paywalls, which makes the platform especially useful for students and freshers in India who want a structured career roadmap without spending on expensive bootcamps or subscriptions.
Which learning path should a complete beginner start with?
Start with the path matching your goal, not the trendiest one. If you enjoy building websites, pick Full-Stack or Frontend Developer; if AI excites you, begin the AI Engineer path with Python for AI and ML. Every path begins with beginner-level courses, so any of them is a valid first step for a newcomer.
Does the DevOps Engineer roadmap cover cloud and automation skills?
Yes, the DevOps Engineer path is built around the skills the role actually demands, including automation, deployment and cloud-adjacent tooling, drawn from SkillVeris courses across DevOps, cloud and programming categories. As with all paths, each course carries 24–40 lessons, module assessments and a final exam with a certificate on passing.
Can I switch between learning paths without losing progress?
Yes, you can switch paths at any time, and progress in completed courses stays with you. Because several paths share foundational courses, work you finish in one roadmap often counts toward another. This makes it low-risk to explore, for example, moving from Frontend Engineer to the AI Engineer path later.
Do learning paths include assessments and certificates?
Yes, every structured course inside a path includes module assessments and a final exam, and you need 80 percent to pass. On passing, you receive a certificate for that course. Completing a full path therefore leaves you with a set of certificates demonstrating each skill along your chosen career roadmap.
How is a SkillVeris roadmap different from a YouTube playlist?
A SkillVeris roadmap is a verified, structured learning system rather than a loose video list. Courses are sequenced deliberately, each with 24–40 lessons, assessments requiring 80 percent to pass, and certificates. You also get an AI Mentor available 24/7, study notes, cheat sheets and a glossary, none of which a playlist provides.
Can working professionals follow a career roadmap part-time?
Yes, learning paths are self-paced, so working professionals can study evenings or weekends without deadlines. Lessons show estimated minutes, letting you plan short sessions, and the AI Mentor is available 24/7 whenever you get stuck. Many learners upskill alongside full-time jobs by completing a lesson or two per day consistently.
What is the best structured learning route to become a full-stack developer?
Follow the Full Stack Java Developer path on SkillVeris, which sequences frontend, backend and supporting courses in a logical order. You learn interface skills, server-side development and the glue between them step by step, with 24–40 lessons per course, assessments to verify understanding and certificates on passing, all free of charge.
Does SkillVeris have a roadmap for machine learning beginners?
Yes, the AI Engineer path serves machine learning beginners well. It starts with Python for AI and ML, then moves through deep learning with PyTorch, TensorFlow and Keras, Hugging Face Transformers, LLMs, RAG, AI agents and MLOps, giving you a complete beginner-to-production machine learning roadmap without any cost.
How do I stay motivated while following a long career roadmap?
Break the roadmap into small wins: complete one lesson daily, pass each module assessment, and celebrate every course certificate. The Learn Through Hobbies method keeps studying enjoyable by explaining concepts through cricket, music, gaming or cooking analogies you can switch instantly, and the AI Mentor helps you past sticking points before frustration builds.
Are the learning paths updated for current industry skills?
Yes, the paths reflect current industry demand, most visibly in the AI Engineer path, which covers modern topics like Large Language Models, Retrieval-Augmented Generation, AI agents and MLOps. With 37 live courses spanning AI/ML, web development, DevOps, cloud, security and databases, the roadmaps stay aligned with skills employers actually ask for.
Can I follow a learning path to prepare for tech interviews?
Yes, complete your chosen path to build the core skills, then use SkillVeris interview questions with readiness scoring to check whether you are prepared. Pairing a roadmap with the interview bank, Code Lab practice and study notes gives you a complete preparation loop from learning to job-ready confidence.
What does a structured course inside a path actually contain?
Each structured course contains 24–40 lessons organised into modules, with a module assessment after each stage, a final exam requiring 80 percent to pass, and a certificate on passing. Lessons include explanations, code examples, quizzes and hobby-based analogies, and the AI Mentor is available 24/7 for questions at any depth.
Is there a roadmap for cloud or security careers on SkillVeris?
Yes, SkillVeris includes Cloud Engineer and Web & Cloud Security Engineer learning paths alongside its developer and AI roadmaps. Each path arranges relevant courses from the platform's 37 live courses into a logical progression, and every course carries assessments and a certificate, so you can build cloud or security skills with clear structure for free.
How many learning paths does SkillVeris currently offer?
SkillVeris currently offers 10 career learning paths: AI Engineer, DevOps Engineer, Cloud Engineer, Data Engineer, Full Stack Java Developer, Frontend Engineer, MERN Stack, Data Scientist, Web & Cloud Security Engineer and Mobile Developer. Each path sequences relevant free courses in a logical order for that specific role.

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