ZMedia Purwodadi

Decoding DevOps – From Basics to Advanced Projects with AI

Table of Contents
Master DevOps with AI, AWS, Linux, Scripts, Jenkins, Gitlab, GitActions, Docker, Kubernetes, Terraform, Ansible & GitOps

Decoding DevOps – From Basics to Advanced Projects with AI

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This course is designed for anyone who wants to start or advance their DevOps career through hands-on, project-based learning.

You’ll begin with Linux, networking, and scripting fundamentals, then progress through key DevOps tools — Git, Jenkins, GitHub Actions, GitLab, Terraform, Ansible, Docker, Kubernetes, and AWS Cloud.

Each step builds on the last with real projects, like setting up the Vprofile application across multiple DevOps stages — from on-premise to AWS to Kubernetes.

The course also introduces AI-powered tools such as GitHub Copilot, Amazon Q, and AI-integrated Helm, helping you automate faster, code smarter, and build intelligent DevOps pipelines.

By the end, you’ll master both the core DevOps practices and modern AI-driven workflows, preparing you for real-world cloud and automation environments.



Step 1

Basics of Linux



Basics of networking

Project

Vprofile Project Intro & Setup on VM’s



Step 3

YAML & JSON


Basics of scripting

Variables, Conditions, Loops etc

Automating day to day admin tasks

Github Copilot as AI Code assistants for Scripting



Step 3




SSM & CloudShell Intro

AWS CLI

S3

Cloudwatch

RDS

Autoscaling

Route53

Project

AWS Cloud For Project Set Up Lift & Shift

Re-Architecting Web App on AWS Cloud [PAAS & SAAS]



Step 4

Version control system = Git & GitHub

Build Tools | Build & Test Java Code = Maven

Continuous Integration Intro

Jenkins

Jenkins as a Build Server

Jenkins Jobs | Build , Test, Deploy, Notify

Jenkins Master/Slave, Nexus, Sonarqube

Jenkins CI Pipeline

Jenkins Administration

GitHub Actions

What GitHub Actions is and how it fits into DevOps workflows

Core concepts: workflows, jobs, steps, and actions

Triggers and events (push, pull request, schedule, etc.)

Security scans in GitHub Actions

Conditions, permissions, and runners for flexible pipelines

Hands-on examples to build and run pipelines directly from GitHub

Gitlab

What GitLab CI/CD is and how it fits into modern DevOps workflows

Core concepts — pipelines, jobs, stages, runners, variables and artifacts

Writing and understanding .gitlab-ci.yml files

Setting up build, test, and deploy stages with rules

Integrating Docker, security scans, and notifications




Step 5

Python Scripting

Basics of python programming

vars, datatypes, conditions, loops, function, modules etc

Pythons for automating OS tasks

Python for AWS using Amazon Q code assistant(AI)


Step 6

Terraform code structure

Variables

Plan, Apply, Update & Destroy

Provisioners

Outputs

Backends

Modules

Terraform for VPC Setup


Step 7

Ansible Intro

Ad Hoc commands

Modules

YAML into

Playbooks

vars, conditions, loops,

handlers, templates etc etc etc

Variables deep dive

Roles

Ansible for AWS



Step 8

AWS Part 2

VPC in depth

Log management and custom metrics

AWS Lambda

Project

Vprofile on Beanstalk & RDS

Code Commit, Code Build & Code Pipeline

CI & CD on AWS Cloud for Vprofile Project

Beanstalk, RDS, CodePipeline etc



Step 9

Docker Intro

Understanding and Implementing Containers

Volumes, Network, logs etc

Building Images for Vprofile project

Docker compose to run vprofile multi containers

Kubernetes Intro

Kubernetes setup for production Env

Kubernetes objects

Pods, Services, Controllers, Deployment

Replication, Autoscaling, Resource quotas, secret, configmap, namespace.

Ingress

Helm with AI

Lens

Project

Vprofile Project deployment on Kubernetes



Step 10

Project on GitOps