What you'll learn:
- Learn DevOps from total scratch
- Linux and Server Management (Gemini CLI)
- Networking fundamentals & Vagrant setup
- YAML, JSON, and Bash scripting with GitHub Copilot (AI)
- AWS Cloud (IAM, EC2, S3, RDS, EBS, ELB, Systems Manager, Lambda, VPC, Amazon Q, CloudWatch, Auto Scaling, Route 53)
- Build & Test Automation using Git, Maven, Jenkins, GitHub Actions, and GitLab CI/CD
- CI/CD Pipelines and DevOps Projects with Nexus, SonarQube & Slack integration
- Python scripting Basics and for Automation and AWS tasks with Amazon Q (AI code assistant)
- Infrastructure as Code using Terraform (VPC, modules, backends)
- Configuration Management using Ansible
- Monitoring & Observability with Prometheus, Grafana, Loki, Alert manager & Alloy
- Docker and Kubernetes (production-grade setup, Helm with AI, Lens)
- AWS DevOps Services: CodeCommit, CodeBuild, CodePipeline, Beanstalk, Lambda
- GitOps Project — end-to-end CI/CD workflow with Git as the single source of truth
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.
And now — introducing the brand-new Monitoring & Observability section, where you’ll learn how to collect, visualize, and analyze metrics, logs, and traces using tools like Prometheus, Grafana, Loki, and Alloy.
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-by-Step Learning Path
Step 1
Basics of Linux
Server Management in Linux
Vagrant
Basics of Networking
Project: VProfile Project Intro & Setup on VMs
Step 2
YAML & JSON
Bash Scripting (Variables, Conditions, Loops)
Automating Admin Tasks
GitHub Copilot as AI Assistant for Scripting
Step 3
Cloud Computing Intro
IAM, EC2, EBS, ELB
SSM & CloudShell Intro
AWS CLI, S3, CloudWatch, RDS, Auto Scaling, Route53
Project: Lift & Shift Web App to AWS
Re-Architecting Web App on AWS (PaaS & SaaS)
Step 4
Git & GitHub
Maven Build Tools
Jenkins (CI/CD Pipelines, Master/Slave, Nexus, SonarQube)
GitHub Actions (Workflows, Runners, Security Scans)
GitLab CI/CD (Pipelines, Stages, Docker Integration)
Step 5
Python Scripting
Automating OS Tasks
Python for AWS using Amazon Q (AI)
Step 6
Terraform Fundamentals (Variables, Modules, Backends)
Infrastructure as Code for VPC Setup
Step 7 – Monitoring & Observability
Introduction to Monitoring & Observability
Why Monitoring is Essential for DevOps
Setting up Prometheus, Grafana, Loki, and Alloy
Writing Queries with PromQL
Connecting Grafana Data Sources
Building Dashboards and Alerts
Slack Integrations for Real-Time Notifications
Integrating Loki and Alloy for Logs and Metrics
Step 8
Ansible Intro
Ad Hoc Commands, Modules, YAML Basics
Playbooks, Variables, Conditions, Loops
Handlers, Templates, Roles
Ansible for AWS Automation
Step 9
AWS (VPC Deep Dive, Lambda, Logging, Custom Metrics)
Project: CI/CD on AWS – Beanstalk, RDS, CodePipeline
Step 10
Project: Google cloud platform for multi tier app setup
GCP Cloud shell
VPC
Firewalls
VMs
Cloud SQL & Memorystore
Cloud DNS
Managed Instance groups
Secure HTTPS Load Balancers
Certificate Manager
Step 11
Docker (Containers, Images, Volumes, Networks)
Kubernetes (Setup, Objects, Autoscaling, Ingress, ConfigMaps)
Helm with AI, Lens
Project: VProfile Deployment on Kubernetes
Step 12
Project on GitOps
