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Yash Sonawane
Yash Sonawane

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From Code to Production: A Practical DevOps Roadmap for Developers

#ai #programming #devops #productivity

DevOps is often presented as a huge collection of tools:

Linux → Git → Docker → Kubernetes → Terraform → CI/CD → Cloud → Monitoring

And honestly, it can feel overwhelming.

But you don't need to learn everything at once.

A better approach is to understand how the pieces connect, then build your skills step by step.

In this article, I'll share a practical roadmap for going from a developer who knows how to write code to someone who can build, deploy, automate, and manage applications in production.

1. Start With the Fundamentals

Before jumping into Kubernetes or Terraform, understand the environment where your applications actually run.

You should be comfortable with:

  • Linux
  • Networking basics
  • Processes
  • Filesystems
  • Permissions
  • SSH
  • Shell commands
  • Environment variables
  • Basic security concepts

For example, when you run:

ssh user@server
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you should understand what is actually happening.

Your computer is creating a network connection to another machine, authenticating with that machine, and giving you access to a shell.

That kind of understanding becomes extremely valuable later when troubleshooting servers, containers, and Kubernetes clusters.

2. Learn Git Properly

Git is not just:

git add .
git commit
git push
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If you want to work professionally, understand:

  • Repository architecture
  • Branches
  • Merge vs rebase
  • Pull requests
  • Remote repositories
  • Tags
  • Releases
  • Conflict resolution
  • Git workflows
  • GitHub/GitLab
  • Git hooks

A useful Git workflow might look like:

Create branch
     ↓
Write code
     ↓
Commit
     ↓
Push
     ↓
Pull Request
     ↓
Code Review
     ↓
Merge
     ↓
CI/CD Pipeline
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If you want a structured resource for learning Git, I've also put together:

📘 Git Mastery

Git Mastery: From Zero to Expert — The Complete Guide to Git, GitHub & GitLab

Read the Git Mastery guide

3. Learn a Programming Language

DevOps doesn't mean you have to become a software engineer specializing in algorithms.

But you should be able to write code.

Python is an excellent choice because it's widely useful for:

  • Automation
  • APIs
  • Scripts
  • Infrastructure tooling
  • Cloud automation
  • Data processing
  • DevOps utilities

For example, instead of manually checking 100 servers, you could write a Python script that performs the task automatically.

You should eventually be comfortable writing programs like:

import os

for server in servers:
    check_server(server)
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The important thing isn't becoming a Python expert immediately.

The goal is learning how to automate repetitive work.

I created a complete Python resource for this:

📕 Mastering Python

Mastering Python: The Complete Developer's Masterclass

Learn Python from fundamentals to advanced development

4. Docker: Package Your Application

Now things start getting interesting.

Imagine your application works perfectly on your computer.

Then you deploy it to a server.

Suddenly:

"It works on my machine."

Docker helps solve this problem by packaging your application and its dependencies into a container.

A simplified workflow looks like:

Application
     ↓
Dockerfile
     ↓
Docker Image
     ↓
Docker Container
     ↓
Server
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A simple Dockerfile might look like:

FROM python:3.12

WORKDIR /app

COPY requirements.txt .

RUN pip install -r requirements.txt

COPY . .

CMD ["python", "app.py"]
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Now your application can be packaged consistently.

You should learn:

  • Images
  • Containers
  • Dockerfiles
  • Volumes
  • Networks
  • Docker Compose
  • Registries
  • Container security
  • Image optimization

I also created a dedicated Docker resource:

📗 Docker Mastery

Docker Mastery: From Zero to Certified — The Complete DCA Exam Guide

Learn Docker and prepare for the DCA certification

5. Understand Infrastructure as Code

Now imagine you have to create:

  • 10 servers
  • 3 networks
  • 5 security groups
  • Databases
  • Load balancers

Doing everything manually would be painful.

This is where Infrastructure as Code (IaC) comes in.

Instead of clicking around a cloud console, you describe infrastructure using code.

Terraform is one of the most important tools to learn here.

The workflow becomes:

Terraform Code
      ↓
terraform plan
      ↓
Review Changes
      ↓
terraform apply
      ↓
Infrastructure Created
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For example:

resource "aws_instance" "app" {
  ami           = "ami-example"
  instance_type = "t2.micro"
}
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Now your infrastructure can be:

  • Version controlled
  • Reviewed
  • Reproduced
  • Automated
  • Modified safely

For Terraform certification preparation, I also have:

📙 Terraform Associate Crash Course

Terraform Associate (003) Exam Crash Course

Study Terraform Associate (003)

6. Kubernetes

Once you've learned Docker, the next question becomes:

"What happens when I have hundreds of containers?"

You don't want to manually manage every container.

That's where Kubernetes comes in.

Kubernetes helps orchestrate containers across a cluster.

A simplified architecture:

                 Kubernetes Cluster
                        │
              ┌─────────┴─────────┐
              │                   │
           Node 1               Node 2
              │                   │
        ┌─────┴─────┐       ┌─────┴─────┐
        │           │       │           │
      Pod         Pod     Pod         Pod
        │           │       │           │
    Container   Container Container   Container
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You should learn concepts such as:

  • Pods
  • Deployments
  • Services
  • ConfigMaps
  • Secrets
  • Namespaces
  • Ingress
  • Volumes
  • StatefulSets
  • Jobs
  • CronJobs
  • RBAC
  • Scheduling
  • Networking

Don't just memorize Kubernetes commands.

Understand why Kubernetes exists and how the components communicate.

For Kubernetes certification preparation:

📒 CKA Complete Study Guide

CKA Complete Study Guide — Certified Kubernetes Administrator

Prepare for the CKA

7. Learn Terraform + Kubernetes Together

This is where your skills start connecting.

You can use Terraform to create infrastructure and Kubernetes to run applications on that infrastructure.

For example:

Terraform
    ↓
Cloud Infrastructure
    ↓
Kubernetes Cluster
    ↓
Application Deployment
    ↓
Users
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Now you're no longer learning isolated tools.

You're building an actual system.

8. CI/CD

You don't want to manually deploy every time you change your application.

Imagine this workflow:

Developer pushes code
        ↓
Git repository
        ↓
CI Pipeline
        ↓
Run tests
        ↓
Build Docker image
        ↓
Push image to registry
        ↓
Deploy
        ↓
Kubernetes
        ↓
Production
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That's CI/CD.

You should learn platforms and concepts such as:

  • GitHub Actions
  • GitLab CI/CD
  • Jenkins
  • Build pipelines
  • Automated testing
  • Docker image builds
  • Artifact repositories
  • Deployment strategies
  • Rollbacks
  • Secrets management

The important concept is:

Code should move from development to production through a reliable, repeatable process.

9. Don't Ignore Go

Once you become comfortable with DevOps, you'll eventually encounter tools written in Go.

Kubernetes, Docker and many cloud-native tools have strong connections to the Go ecosystem.

Learning Go can therefore be extremely useful for:

  • Cloud-native development
  • CLI tools
  • Infrastructure tooling
  • Kubernetes operators
  • Backend services
  • High-performance applications

You don't necessarily need Go on day one.

But it's a great language to add after you've built your fundamentals.

📘 Mastering Go

Mastering Go: The Complete Developer's Masterclass

Learn Go

10. Think Like a Problem Solver

There's another skill that doesn't get enough attention in DevOps:

Critical thinking.

When production breaks, there isn't always a tutorial saying:

"Run these three commands."

Sometimes you need to investigate.

For example:

Application is down
       ↓
Is the server reachable?
       ↓
Is DNS working?
       ↓
Is the port open?
       ↓
Is the container running?
       ↓
Is Kubernetes healthy?
       ↓
Are logs showing errors?
       ↓
Is the database reachable?
       ↓
What changed recently?
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This is why troubleshooting is such an important DevOps skill.

Instead of immediately searching for a command, learn to ask:

What do I know? What don't I know? What evidence can I collect?

I've also created a resource focused on this type of thinking:

📔 The Sharp Mind

The Sharp Mind: A Complete System for Mastering Critical Thinking

Develop stronger critical-thinking skills

11. The Complete DevOps Learning Path

If I were starting from zero, I'd follow this order:

Linux
  ↓
Networking
  ↓
Git & GitHub
  ↓
Python / Programming
  ↓
Docker
  ↓
Cloud Fundamentals
  ↓
Terraform
  ↓
CI/CD
  ↓
Kubernetes
  ↓
Monitoring & Logging
  ↓
Security
  ↓
Advanced Cloud & DevOps
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And remember:

Don't learn tools independently.

Connect them through projects.

12. Build One Real Project

This is probably the most important part.

Instead of watching 50 hours of tutorials, build something.

For example:

Project: Deploy a Web Application

Build a simple application and create this pipeline:

Developer
    │
    ▼
GitHub
    │
    ▼
CI/CD
    │
    ▼
Docker
    │
    ▼
Container Registry
    │
    ▼
Terraform
    │
    ▼
Cloud Infrastructure
    │
    ▼
Kubernetes
    │
    ▼
Application
    │
    ▼
Monitoring
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Now you've learned DevOps by actually doing DevOps.

My DevOps Learning Resources

If you're following this roadmap and want structured resources alongside your practical projects, these are the guides I've created:

Final Thoughts

DevOps isn't about memorizing hundreds of commands.

It's about understanding systems.

When you deploy an application, you should be able to reason through the entire journey:

Code
 ↓
Git
 ↓
CI/CD
 ↓
Docker
 ↓
Infrastructure
 ↓
Kubernetes
 ↓
Networking
 ↓
Monitoring
 ↓
Users
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And when something breaks, you should be able to work backward through that system until you find the problem.

That's the skill that separates someone who simply uses DevOps tools from someone who can actually engineer reliable systems.

Learn one concept. Build something with it. Break it. Fix it. Then move to the next layer.

That's how you become good at DevOps.

Top comments (1)

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officialmailkr profile image
오피셜메일 •

마지막의 웹앱 배포 프로젝트에 일부러 실패하는 배포를 한 번 넣으면 학습 범위가 더 명확해지겠네요. 정상 배포 확인뿐 아니라 이전 이미지로 되돌린 뒤 실제 요청이 다시 처리되는지까지 확인하는 식입니다. 장애 점검 목록의 “최근에 무엇이 바뀌었나”를 답하려면 배포된 커밋과 이미지 버전을 로그에서 연결해 두는 연습도 유용하겠습니다.