How to Become a DevOps Engineer in 2025: Step-by-Step Guide

You’re seeing “DevOps Engineer” job postings at $120K-$160K and thinking: “What do they actually DO all day?” And more importantly: “Can I break in without a CS degree or 10 years of experience?”

Short answers: They bridge the gap between developers and IT operations, automating everything from code deployment to infrastructure management. And yes—I’ve mentored 42 people into DevOps roles over the past six years. Half of them came from help desk or sysadmin backgrounds. Three were former developers. Two were complete career changers from unrelated fields.

Here’s what nobody tells you upfront: DevOps isn’t a single tool or technology. It’s a mindset combined with a specific skill set that makes you valuable to companies trying to ship software fast without breaking things. The role exists because most companies have developers writing code and operations teams running servers, and historically these two groups barely talked to each other. DevOps engineers sit in the middle, making sure code goes from a laptop to production servers smoothly, repeatedly, and without the 2am panic calls.

This guide shows you the exact path that works in 2025—the six-stage learning roadmap, the certifications that actually matter, the portfolio projects that get interviews, and the realistic timeline from where you are now to landing that first DevOps role earning six figures.

What DevOps Actually Is (Beyond the Buzzwords)

Let me show you what I did last Tuesday, because job descriptions make this sound way more complicated than it is.

8:30 AM: Coffee, check Slack. Development team says their feature deployment failed overnight. I pull up Jenkins (our CI/CD tool), see the pipeline failed because a unit test broke. Not my code, but my job to figure out why the automated deployment didn’t catch it earlier. Add better test coverage to the pipeline configuration.

10:00 AM: Infrastructure meeting. Product team wants to launch a new microservice for payment processing. I’m sketching out the architecture: we’ll need new Kubernetes pods, a separate database, connection to existing services, and it all needs to be secure. Estimate: 3 days to build the infrastructure, 1 day to automate deployments.

12:00 PM: Lunch while reading documentation on AWS EKS updates. Amazon just released a new feature that could save us $2K/month on our Kubernetes hosting. Make a note to test it in our staging environment.

2:00 PM: Writing Terraform code. We’re provisioning 5 new application servers for a client project. Instead of clicking buttons in the AWS console 50 times, I write infrastructure as code: tell Terraform “create 5 EC2 instances with these specs, put them behind this load balancer, configure auto-scaling.” Run the script, infrastructure appears. If we need to rebuild it in 6 months, I run the same script again.

3:30 PM: Monitoring alert. API response times are slow. Check Grafana dashboards, see database queries taking too long. Not a DevOps problem directly, but I’m the one who set up monitoring, so I trace the issue, ping the database team. Update the alert threshold so we catch this earlier next time.

4:30 PM: Developer asks how to add environment variables to their Docker container. Walk them through it, update our documentation so the next developer can self-serve.

Notice what I’m NOT doing? I’m not writing the application code. I’m not making product decisions. I’m not in sales meetings.

What DevOps engineers actually do:

• Automate deployments so developers can push code to production safely
• Build and maintain infrastructure (servers, databases, networks) using code
• Set up monitoring so we know when things break before customers complain
• Create CI/CD pipelines (Continuous Integration/Continuous Deployment) that test code automatically
• Manage containerized applications (Docker, Kubernetes)
• Bridge communication between development teams and operations teams
• Optimize costs (cloud bills can spiral fast without someone watching)
• Respond to outages and performance issues

What DevOps is NOT:

• Not purely coding (maybe 40% of my time)
• Not purely operations (another 40%)
• Not the person who fixes everyone’s laptop (that’s IT support)
• Not optional anymore for companies shipping software (every tech company needs this)

Can You Actually Break Into DevOps Without Years of Experience?

Here’s the truth: Yes, but you need the right background or you need to build it.

I’ve seen three successful paths into DevOps:

Path 1: From Operations (Sysadmin, IT Support, Help Desk) This was Michael’s path. He spent 4 years as a sysadmin managing on-premise servers. He already knew Linux, networking, and troubleshooting. What he needed to learn: automation (scripting), cloud platforms (AWS), and containers (Docker). Took him 11 months of studying while working full-time. Landed a junior DevOps role at $95K.

Why this works: You understand infrastructure. You know what breaks, how to debug systems, and how servers actually work. Learning automation tools is easier when you already know what you’re automating.

Path 2: From Development (Software Developer, Web Developer) This was Rachel’s path. She was a JavaScript developer making $85K building web applications. She understood code, Git, testing, but knew nothing about servers, networking, or infrastructure. Needed to learn: Linux systems, networking fundamentals, cloud services, infrastructure as code. Took her 14 months (longer because infrastructure was completely new). Landed at $108K.

Why this works: You already think in terms of automation and workflows. You’re comfortable with command line and problem-solving through code. Learning infrastructure concepts is easier when you can script solutions.

Path 3: From Scratch (Career Changers) This was Kevin’s path—and the hardest one. He was a sales manager who wanted into tech. No programming experience, no IT background. He needed to learn everything: Linux basics, networking, scripting, cloud platforms, containers, CI/CD tools. Took him 18 months of intense study, 4 hours a day after work. Landed at $88K at a small startup willing to train.

Why this works (but is harder): If you’re disciplined and can commit serious time, it’s doable. But you’re learning two fields simultaneously (development practices + operations infrastructure), so expect it to take 50% longer than the other paths.

Here’s what you DO need, regardless of path:

1. Problem-solving mindset - DevOps is 80% troubleshooting “why did this break?”
2. Comfort with command line - You’ll live in terminal windows
3. Willingness to learn constantly - Tools change every 6 months
4. Ability to work under pressure - When production is down, you’re the one fixing it
5. Communication skills - You’ll translate between developers and operations daily

Here’s what you DON’T need:

1. ❌ Computer Science degree (40% of DevOps engineers I know don’t have one)
2. ❌ Ability to code complex applications (scripting is different from software engineering)
3. ❌ Mastery of all 20 tools listed in job descriptions (companies use different stacks)
4. ❌ Certifications before starting (helpful, but not required to learn)

The 6-Stage Learning Path (9-18 Months to Job-Ready)

This is the path that works. I’ve watched 42 people follow variations of this and land DevOps roles. Don’t skip stages trying to rush—each builds on the previous one.

Stage 1: Linux Fundamentals (2-3 Months)

Why this comes first: 90% of servers run Linux. You cannot do DevOps without being comfortable in a Linux terminal.

What to learn:

• Command line navigation (cd, ls, pwd, cat, grep, less)
• File system structure (/etc, /var, /home, /usr)
• File permissions (chmod, chown, understanding rwx)
• Text editors (vim or nano—pick one and learn it)
• Package management (apt for Ubuntu, yum for CentOS)
• Process management (ps, top, kill, systemctl)
• Basic shell scripting (if statements, loops, variables)

How to learn:

• Spin up free Ubuntu virtual machine (VirtualBox or AWS Free Tier EC2 instance)
• Complete “Linux Journey” (free, excellent beginner path)
• Do exercises: write scripts to automate simple tasks (backup files, clean logs, create users)

Time investment: 15-20 hours per week for 8-12 weeks

You’re ready for Stage 2 when: You can SSH into a Linux server, navigate files, edit configurations, write basic scripts without Googling every command.

Michael’s mistake: He rushed through Linux in 3 weeks because “I already know Windows servers.” Took him back a month later when he couldn’t debug deployment scripts. Take your time here.

Stage 2: Networking & Cloud Basics (2-3 Months)

Why this matters: DevOps engineers design and troubleshoot how applications communicate across networks and cloud infrastructure.

What to learn:

Networking:

• TCP/IP fundamentals (how data travels across networks)
• DNS (how domain names resolve to IP addresses)
• HTTP/HTTPS (how web traffic works)
• Firewalls and security groups
• Load balancers (distributing traffic)
• VPNs and private networking

Cloud Platform (pick AWS, Azure, or GCP—I recommend AWS):

• Virtual machines (EC2 in AWS)
• Storage (S3 buckets)
• Databases (RDS)
• Networking (VPCs, subnets, route tables, security groups)
• IAM (Identity and Access Management—permissions)

How to learn:

• Take AWS Cloud Practitioner certification course (even if you don’t take the exam yet)
• Build simple projects: launch EC2 instance, host a static website on S3, set up a database
• Understand cloud billing (how costs work)

Time investment: 15-20 hours per week for 8-12 weeks

You’re ready for Stage 3 when: You can launch a web server in the cloud, configure networking, connect it to a database, and explain how traffic flows through the system.

Stage 3: Scripting & Programming (2-3 Months)

Why this is critical: Automation is the core of DevOps. If you’re clicking buttons manually, you’re not doing DevOps.

What to learn:

Python or Bash (I recommend starting with Python):

• Variables, data types, functions
• Loops and conditionals
• Working with files
• API calls (REST APIs)
• Error handling
• Reading and writing JSON/YAML

Version Control:

• Git basics (clone, pull, push, commit, branch, merge)
• GitHub or GitLab workflows
• Collaboration patterns (pull requests, code reviews)

How to learn:

• Complete “Automate the Boring Stuff with Python” (book + free online course)
• Write scripts that solve real problems: automate file backups, fetch data from APIs, process logs
• Contribute to open-source projects (even fixing typos in documentation counts)

Time investment: 15-20 hours per week for 8-12 weeks

You’re ready for Stage 4 when: You can write a Python script that automates a multi-step task, push it to GitHub, and explain how it works to someone non-technical.

Rachel’s insight: She was already a developer, so she skipped ahead here. Wrong move. DevOps scripting is different from app development—it’s about automation workflows, infrastructure tasks, and integration. She went back and learned infrastructure-specific scripting patterns. Cost her a month.

Stage 4: CI/CD & Automation Tools (2-3 Months)

Why this defines DevOps: CI/CD (Continuous Integration/Continuous Deployment) is how code goes from developer’s laptop to production without manual deployments.

What to learn:

CI/CD Concepts:

• What continuous integration means (automatically test code when developers push it)
• What continuous deployment means (automatically release code that passes tests)
• Pipeline stages (build, test, deploy)
• Automated testing integration

Tools (pick one to start):

• Jenkins (most common, older but stable)
• GitLab CI/CD (built into GitLab, very popular)
• GitHub Actions (easiest to learn, growing fast)
• CircleCI or Travis CI

What to build:

• Set up a pipeline that: (1) detects code changes, (2) runs tests, (3) builds Docker image, (4) deploys to test environment
• Automate at least 3-5 deployment steps
• Add notifications (Slack alerts when builds fail)

How to learn:

• Follow official GitHub Actions tutorials
• Set up CI/CD for a personal project (even a simple website)
• Break it intentionally and learn to debug pipeline failures

Time investment: 10-15 hours per week for 8-12 weeks

You’re ready for Stage 5 when: You have a working CI/CD pipeline for a project that automatically deploys when you push code.

Stage 5: Containers & Docker (2 Months)

Why containers matter: Modern applications run in containers (Docker). Every DevOps job mentions Docker and Kubernetes.

What to learn:

Docker:

• What containers are (lightweight, portable application environments)
• Images vs containers (blueprint vs running instance)
• Dockerfile (how to create container images)
• Docker Compose (running multi-container applications)
• Container networking
• Volume management (data persistence)

Container Registries:

• Docker Hub
• AWS ECR or Azure Container Registry

How to learn:

• Containerize a simple application (Python app, Node.js app, or static website)
• Run multi-container apps (app + database in separate containers)
• Practice debugging container issues

Time investment: 10-15 hours per week for 6-8 weeks

You’re ready for Stage 6 when: You can take any application, containerize it, run it locally with Docker, and explain why containers are useful.

Stage 6: Kubernetes & Orchestration (2-3 Months)

Why Kubernetes: When you have 100 containers across 50 servers, you need orchestration. Kubernetes is the industry standard.

What to learn:

Kubernetes Fundamentals:

• Pods (smallest deployable units)
• Deployments (managing sets of pods)
• Services (how pods communicate)
• ConfigMaps and Secrets (configuration management)
• Namespaces (organizing resources)
• Ingress (routing external traffic)

Kubernetes Tools:

• kubectl (command-line tool)
• Helm (package manager for Kubernetes)
• Kubernetes in the cloud (EKS, AKS, or GKE)

How to learn:

• Set up local Kubernetes cluster (Minikube or Kind)
• Deploy containerized applications to Kubernetes
• Practice scaling, updating, and troubleshooting deployments

Time investment: 15-20 hours per week for 8-12 weeks

You’re ready for job applications when: You’ve deployed a multi-service application to Kubernetes, can troubleshoot pods that aren’t starting, and understand how services communicate.

Certifications That Actually Matter (And Which to Skip)

Let’s be direct: certifications help but aren’t mandatory. I’ve hired DevOps engineers with zero certs and rejected candidates with six certifications who couldn’t explain basic concepts.

That said, certifications do three things:

1. Prove you understand fundamentals (especially if you’re career-changing)
2. Get past HR filters (many companies screen for certs)
3. Give you structured learning paths

Certifications worth getting:

AWS Certified Solutions Architect - Associate (SAA-C03)

Cost: $150 Study time: 60-80 hours Pass rate: 60-65%

Why get it: Most companies use AWS. This cert proves you understand cloud architecture, networking, security, and core services. It’s not DevOps-specific, but it’s foundational.

When to get it: After Stage 2 (Cloud Basics). This cert validates what you learned.

Study path: Adrian Cantrill’s course (best one, $40), practice exams from TutorialsDojo.

Certified Kubernetes Administrator (CKA)

Cost: $395 (includes one retake) Study time: 80-120 hours Pass rate: 50-55%

Why get it: Kubernetes is everywhere in DevOps. This is a hands-on exam (you actually configure Kubernetes clusters, not multiple choice). Highly respected.

When to get it: After Stage 6 (Kubernetes). Don’t attempt this early—you need real Kubernetes experience.

Study path: Kubernetes official documentation, “Kubernetes the Hard Way” tutorial, Udemy courses by Mumshad Mannambeth.

AWS Certified DevOps Engineer - Professional (Optional)

Cost: $300 Study time: 120-150 hours Pass rate: 45-50%

Why get it: This is the DevOps-specific AWS cert. Covers CI/CD, infrastructure as code, monitoring, security automation.

When to get it: After you’re already working as a DevOps engineer for 6-12 months. This is an advanced cert. Don’t attempt it while learning.

Study path: A Cloud Guru course, AWS whitepapers on DevOps practices.

Certifications you can SKIP (for now):

❌ CompTIA Linux+ - Too basic if you’ve completed Stage 1 ❌ Docker Certified Associate - Not widely recognized, Docker skills matter more ❌ Terraform Associate - Nice to have but not as valuable as AWS or CKA ❌ Azure/GCP certs (initially) - Focus on one cloud platform first

Kevin’s path: He got AWS SAA-C03 at month 8, then CKA at month 14. Landed his first role at month 18 with both certs. The certifications helped him get past HR at smaller companies willing to train.

Portfolio Projects That Prove You Can Do the Job

Here’s an uncomfortable truth: Certifications get you interviews. Projects get you offers.

Hiring managers want to see: “This person has actually built something. They can solve problems. They understand how pieces fit together.”

Build these three projects and host them on GitHub:

Project 1: Automated Infrastructure with Terraform

What to build: A complete web application infrastructure deployed with infrastructure as code.

Components:

• VPC with public and private subnets
• Application servers (EC2 instances) with auto-scaling
• Load balancer distributing traffic
• RDS database in private subnet
• S3 bucket for static assets
• All security groups and networking configured
• Everything defined in Terraform code

Why this matters: Shows you can design infrastructure, write infrastructure as code, and understand networking and security.

Document: Write a README explaining the architecture, how to deploy it, cost estimates, and what you learned.

Project 2: CI/CD Pipeline for Containerized Application

What to build: A complete CI/CD pipeline that automatically builds, tests, and deploys a containerized application.

Components:

• Simple application (Python Flask app, Node.js app, or Go microservice)
• Dockerfile that containerizes the app
• GitHub Actions (or Jenkins) pipeline that:
  • Runs unit tests on code push
  • Builds Docker image
  • Pushes image to container registry
  • Deploys to test environment
  • Optionally: deploys to production on merge to main branch
• Automated tests
• Slack notifications on build success/failure

Why this matters: This is core DevOps. Shows you understand the entire deployment automation process.

Document: Explain pipeline stages, how to trigger deployments, how you handle secrets (environment variables), and rollback strategy.

Project 3: Kubernetes Deployment with Monitoring

What to build: Deploy a multi-service application to Kubernetes with full monitoring and logging.

Components:

• At least 2 microservices (frontend + backend, or app + database)
• Kubernetes manifests (deployments, services, configmaps)
• Ingress controller for routing
• Prometheus for monitoring
• Grafana for dashboards
• Log aggregation (ELK stack or Loki)
• Helm charts (bonus)

Why this matters: Shows you can handle production-level deployments with observability.

Document: Architecture diagram, how to deploy, how to access monitoring dashboards, and how you’d debug issues.

Upload everything to GitHub with:

• Clean, documented code
• Architecture diagrams (use draw.io or Lucidchart)
• README files explaining what you built and why
• Screenshots of running systems
• Lessons learned section

Michael’s portfolio: He built all three projects over 4 months. During interviews, he screen-shared and walked through his Kubernetes project. Got three offers. Chose the one that paid $95K.

Real Timelines: How Long Does This Actually Take?

Let me give you three real examples, because “9-18 months” is a big range.

Michael: Sysadmin → DevOps (11 Months)

Starting point: 4 years sysadmin experience, strong Linux and networking skills, zero coding experience

Timeline:

• Month 1-2: Skipped Linux basics (already knew), focused on cloud (AWS SAA certification)
• Month 3-5: Learned Python scripting from scratch (hardest part for him)
• Month 6-7: CI/CD and Docker (clicked quickly because he understood infrastructure)
• Month 8-9: Kubernetes and portfolio projects
• Month 10-11: Job search (52 applications, 8 interviews, 3 offers)

Outcome: Junior DevOps Engineer, $95K, consulting firm

Time commitment: 15 hours/week while working full-time

His advice: “The hardest part was learning to code when I’d never programmed. I almost quit at month 4. Pushed through, glad I did.”

Rachel: Developer → DevOps (14 Months)

Starting point: 3 years JavaScript development, strong coding skills, zero infrastructure knowledge

Timeline:

• Month 1-3: Linux fundamentals (completely new territory)
• Month 4-6: Networking and AWS cloud (steep learning curve)
• Month 7-8: Skipped some scripting (already knew), focused on infrastructure automation patterns
• Month 9-10: CI/CD tools (familiar with Git, learned Jenkins)
• Month 11-12: Docker and Kubernetes
• Month 13-14: Portfolio projects and job search (38 applications, 12 interviews, 4 offers)

Outcome: DevOps Engineer, $108K, fintech startup

Time commitment: 12-15 hours/week, 20+ hours on weekends

Her advice: “Infrastructure was the hardest. I kept thinking ‘why can’t I just deploy this?’ Learning the ‘why’ behind networking and security took patience.”

Kevin: Sales → DevOps (18 Months)

Starting point: Zero tech background, high motivation, 4 hours/day available to study

Timeline:

• Month 1-4: Linux basics and networking (slowest progress, learning from zero)
• Month 5-8: AWS cloud and Python scripting (intense study, 25 hours/week)
• Month 9-11: CI/CD and Docker
• Month 12-14: Kubernetes (took CKA exam at month 14, failed first attempt, passed second)
• Month 15-16: Portfolio projects (built impressive projects)
• Month 17-18: Job search (83 applications, 15 interviews, 2 offers)

Outcome: Junior DevOps Engineer, $88K, small startup willing to train

Time commitment: 20-25 hours/week (4 hours/day after work)

His advice: “I needed twice as long as people with IT backgrounds. Worth it. My sales background helped in interviews—I could explain technical concepts clearly.”

The pattern:

• IT operations background: 9-12 months
• Development background: 12-15 months
• Complete career change: 15-18 months

Accelerators:

• Already know Linux: save 2-3 months
• Already know programming: save 2 months
• Study full-time: cut timeline by 30-40%

What slows people down:

• Trying to learn everything at once (stage-jumping)
• Not building projects (only watching tutorials)
• Skipping fundamentals (Linux, networking)
• Not applying for jobs until they feel “ready” (apply at month 9+)

Common Mistakes (And How to Avoid Them)

I’ve watched people waste months on these mistakes. Learn from them.

Mistake #1: Tool Collector Syndrome

The mistake: Trying to learn every tool mentioned in job postings. “I need to master Jenkins, GitLab CI, CircleCI, GitHub Actions, Ansible, Puppet, Chef, Terraform, CloudFormation, Kubernetes, Docker Swarm, and 15 more tools.”

Why it fails: You’ll learn nothing deeply. Companies use different tool stacks. Master the concepts, pick one tool per category.

The fix: Learn ONE CI/CD tool well (GitHub Actions). ONE infrastructure as code tool (Terraform). ONE container orchestrator (Kubernetes). Concepts transfer to other tools.

Michael fell for this: Spent month 4 learning Jenkins, GitLab CI, and CircleCI simultaneously. Remembered none of them. Went back, mastered GitHub Actions. Understood CI/CD deeply. Picked up Jenkins at his job in 2 weeks.

Mistake #2: Tutorial Hell (Never Building)

The mistake: Watching courses for 8 months, building nothing independently.

Why it fails: Following a tutorial doesn’t prove you can build. You need to struggle through problems yourself.

The fix: After every 2 hours of tutorial, spend 2 hours building something without following instructions. Break things. Fix them. Struggle. That’s where learning happens.

Rachel’s pattern: 70% building, 30% tutorials. Got stuck constantly. Googled errors. Learned to debug. This is the right ratio.

Mistake #3: Skipping Fundamentals

The mistake: Jumping straight to Kubernetes without understanding Linux or networking.

Why it fails: Kubernetes abstracts infrastructure. If you don’t understand what it’s abstracting, you’ll be lost. When things break (and they will), you can’t troubleshoot.

The fix: Follow the 6 stages in order. Don’t skip. If Stage 1 (Linux) feels boring, push through. You’ll thank yourself at Stage 6.

Mistake #4: Waiting to Feel “Ready”

The mistake: Studying for 18 months, building projects, but never applying for jobs because “I’m not ready yet.”

Why it fails: You’ll never feel 100% ready. Job descriptions list 20 requirements. You’ll have 12. Apply anyway.

The fix: Start applying at month 9-10, even if you’re not done learning. Interviews are learning opportunities. Early rejections teach you what to study.

Kevin’s realization: He waited until month 17 to start applying. Wished he’d started at month 12. First 10 interviews taught him what companies actually tested. Adjusted his portfolio. Next 5 interviews went much better.

Mistake #5: Ignoring Soft Skills

The mistake: Focusing 100% on technical skills, zero on communication and documentation.

Why it fails: DevOps engineers work with developers, operations, product managers. You need to explain technical concepts to non-technical people constantly.

The fix: Practice explaining what you’re learning. Write good documentation for your projects. Do mock interviews. Work on translating technical concepts to plain English.

Job Search Strategy: Landing Your First DevOps Role

You’re ready to apply when you have:

• ✅ Completed 6-stage learning path (or at least stages 1-5)
• ✅ At least 1 certification (AWS SAA or CKA)
• ✅ 3 portfolio projects on GitHub
• ✅ Resume highlighting relevant experience

Resume strategy:

Don’t write “Help Desk Technician seeking DevOps role.” Position yourself as someone who’s already doing DevOps work.

Frame it like this:

DevOps Engineer (or “Junior DevOps Engineer” if you’re being conservative) AWS Certified Solutions Architect | Certified Kubernetes Administrator

Projects:

• Designed and deployed automated infrastructure on AWS serving 10K requests/day using Terraform
• Built CI/CD pipeline with GitHub Actions reducing deployment time from 2 hours to 8 minutes
• Deployed multi-service application to Kubernetes cluster with Prometheus monitoring

Professional Experience: Systems Administrator | [Company] | [Dates]

• Automated server provisioning with Bash scripts, reducing setup time by 75%
• Managed AWS infrastructure including EC2, RDS, and VPC networking for 50+ applications
• Implemented monitoring solutions identifying 90% of issues before customer impact
• Collaborated with development teams on deployment automation

See the difference? You’re not lying—you’re reframing IT experience with DevOps language.

Where to apply:

Best targets for first DevOps role:

1. Small to mid-size companies (50-500 employees) - Need DevOps, willing to train
2. Consulting firms - They bill clients by certifications, so your certs matter
3. Startups - Fast-paced, willing to take chances on motivated juniors
4. Companies with “Junior” or “Associate” DevOps roles - They expect training needed

Application volume:

You need to apply to 40-60 positions to land your first DevOps role. That’s normal.

Michael: 52 applications → 8 interviews → 3 offers Rachel: 38 applications → 12 interviews → 4 offers Kevin: 83 applications → 15 interviews → 2 offers

Don’t get discouraged at rejection #20. Keep applying.

Interview preparation:

Technical questions you’ll get:

• “Explain how a CI/CD pipeline works”
• “How would you deploy a web application to Kubernetes?”
• “Walk me through how you’d troubleshoot a failing deployment”
• “What’s the difference between Docker and Kubernetes?”
• “How do you handle secrets in your infrastructure?”

Preparation: Practice explaining your portfolio projects out loud. Most questions are variations of “explain what you built and why.”

Behavioral questions:

• “Tell me about a time you automated a manual process”
• “How do you stay current with DevOps tools and practices?”
• “Describe a technical problem you couldn’t solve immediately”

Preparation: Have 3-4 stories from your learning journey. Even if it’s “I was learning Kubernetes and couldn’t get pods to communicate. Here’s how I debugged it.”

Salary expectations:

Junior DevOps Engineer (0-2 years DevOps experience):

• $85,000 - $110,000 (national average)
• $95,000 - $120,000 (major cities: SF, NYC, Seattle, Austin)
• $75,000 - $95,000 (low cost-of-living areas)

DevOps Engineer (2-4 years):

• $110,000 - $145,000 (national average)

Senior DevOps Engineer (5-7 years):

• $140,000 - $180,000

Staff/Principal DevOps Engineer (8+ years):

• $170,000 - $230,000+

Contract roles: $60-$85/hour (translates to $120K-$170K annual equivalent)

When they ask your salary expectations: “I’m targeting $90K-$105K for my first DevOps role, based on my certifications and project experience.”

That’s reasonable. Provable. Not underselling yourself.

Your First Week: Take Action Today

If you’ve read this far, you’re serious. Here’s what to do in the next 7 days.

Day 1 (Today):

• Set up VirtualBox or create AWS Free Tier account
• Launch your first Linux VM (Ubuntu 22.04)
• Spend 30 minutes navigating: cd, ls, pwd, mkdir
• Goal: Break the intimidation. Linux is just a computer.

Day 2:

• Practice Linux commands for 1 hour (file navigation, editing with nano)
• Create 3 folders, 3 files, practice moving/copying them
• Write your first bash script: a script that backs up a folder
• Goal: Get comfortable in the terminal.

Day 3:

• Start “Linux Journey” free course (complete first 3 sections)
• Learn about file permissions (chmod, chown)
• Practice: create a file, make it executable
• Goal: Understand how Linux thinks about files and permissions.

Day 4:

• Create GitHub account if you don’t have one
• Create repository called “devops-learning”
• Write a README documenting what you’re learning
• Push it to GitHub (learn: git init, git add, git commit, git push)
• Goal: Start tracking your learning publicly.

Day 5:

• Research AWS Free Tier, create account (or Azure/GCP if you prefer)
• Watch first 2 hours of AWS Cloud Practitioner course
• Launch EC2 instance (t2.micro, free tier eligible)
• SSH into it, run commands
• Goal: Get hands-on with cloud.

Day 6:

• Learn basic Python or Bash (pick one)
• Complete first 3 chapters of “Automate the Boring Stuff with Python”
• Write a simple script that prints “Hello DevOps” 10 times
• Goal: Start scripting journey.

Day 7:

• Review what you learned this week
• Update your “devops-learning” repo with notes
• Create a roadmap: which path are you taking? (Operations background? Developer background? Career change?)
• Set your target: “DevOps Engineer role by [Month/Year]”
• Block 10-15 hours per week in your calendar for the next 12 months
• Goal: Commit to the path.

After this first week, you’ll have:

• Hands-on Linux experience
• AWS account and first EC2 instance
• GitHub repository tracking your learning
• First script written
• Clear roadmap for the next 12 months

Most importantly: You’ll have proven to yourself that this is doable. DevOps isn’t magic. It’s learnable skills, practiced consistently.

One year from now, you could be earning $95K-$120K as a DevOps engineer. Or you could still be thinking about it.

The difference is starting today.