Module 1: Foundations of DevOps and Gen AI

• Introduction to DevOps & AI Integration
• AI Basics for DevOps Engineers
• Tools Overview: ChatGPT, LangChain, Ollama, Terraform, AWS
• GitOps, IaC, CI/CD, Monitoring – Where AI Fits
• Intro to Prompt Engineering for Infrastructure

Module 2: AI + Infrastructure as Code

• Generating Terraform code with LLMs
• Code Validation: Linting, Testing using AI Agents
• Auto-generating Variables & Modules
• Real-World: 2-tier architecture with AI-generated Terraform
• On-demand infra generation from high-level description
• Custom LangChain agent to convert JSON→Terraform
• Convert existing infra to Terraform using AI + Recon Tools
• AI for multi-cloud Terraform code generation (AWS, Azure, GCP)
• CI/CD pipelines to run Terraform dynamically
• Review: Build complete 2-tier infra from voice/text input

Module 3: AI in CI/CD and SRE

• Using AI to generate CI/CD pipeline templates (GitHub/GitLab/Azure)
• AI to fix failed CI/CD builds automatically
• Monitoring Overview: Prometheus, Grafana, CloudWatch
• Monitoring Overview: Prometheus, Grafana, CloudWatch
• Generate runbooks using AI
• Self-healing infra via AI recommendations
• GenAI for reliability scoring & chaos analysis
• SRE ChatOps: AI responding to real-time failures
• Auto-documenting infra & pipelines via AI
• Review: Smart CI/CD + Monitoring with AI tools

Module 4: Agentic AI Workflows & Automation

• LangChain Agents vs OpenAI Functions
• Build AI agent to plan and apply Terraform
• Agent to handle ticket → root cause → resolution
• Multi-step agents for app deployment
• Build LLM assistant to generate monitoring dashboards
• Orchestrating workflows with tools like CrewAI or LangGraph
• Human-in-the-loop (HITL) automation patterns
• LLM + GitOps agent for PRs, merges, test validation
• Chaining AI agents for full environment provisioning
• End-to-end project: AI agent provisioning + CI/CD + monitor

Module 5: Advanced Integrations & Real-Time Projects

• Create voice-based infra-assistant using Whisper + LLM
• Vision-to-Infrastructure (diagram → terraform)
• AI for Cloud Cost Optimization & Budgeting
• LLMs + Security Automation
• Infra Drift Detection & Resolution using AI
• Build: Self-service portal with AI infra requests
• Evaluation: Students present automation bots
• Open Q&A: Debugging, Custom Use Cases
• Final Project Presentation & Certification

Module 6: Working with Infra as a Code (IaC)

• Create voice-based infra-assistant using Whisper + LLM
• Vision-to-Infrastructure (diagram → terraform)
• AI for Cloud Cost Optimization & Budgeting
• Terraform – Your infrastructure sculptor 🛠 — learn how to build cloud resources declaratively, manage them consistently, and scale like a pro across AWS, Azure, and GCP.
• Ansible – Your automation wizard 🛠 — master how to configure, deploy, and manage servers effortlessly with agentless automation.
• Understand state management, providers, and modules in Terraform.
• Write idempotent playbooks in Ansible to ensure systems always stay exactly how you want them.
• Learn how Terraform provisions infrastructure and Ansible breathes life into it with configurations.
• Hands-on labs to spin up real cloud environments and automate application deployments.
• Enterprise tips for scalable, repeatable, and secure infrastructure setups.
• Troubleshooting secrets for both tools to handle real-world DevOps challenges.
• See them in action together — infrastructure + configuration = DevOps Superpower!

Module 7: Getting Started with Pipeline as Code in Jenkins

• Learn what Pipeline as Code means and why it’s better than manual builds.
• Understand the role of Jenkins in automating software delivery.
• Create a Jenkinsfile to define your build steps in code.
• Explore the difference between Declarative and Scripted pipelines.
• Add simple stages like Build, Test, and Deploy.
• Connect Jenkins with Git so pipelines run automatically on code changes.
• See how to use Groovy syntax for pipeline steps.
• Learn how to store and manage credentials securely.
• Trigger pipelines manually or automatically.
• Get a basic hands-on demo to run a complete pipeline from commit to deployment.

Module 8: Getting Started with Docker

• Understand what Docker is and why it’s changing how we run applications.
• Learn the difference between containers and virtual machines (and why containers are faster).
• Install Docker and get familiar with Docker CLI commands.
• Pull and run pre-built Docker images from Docker Hub.
• Build your own Docker images using a Dockerfile.
• Learn about layers in images and why they make builds faster.
• Learn how to tag, push, and pull images from a registry.
• Understand container lifecycle: create → start → stop → remove.
• Practice deploying a sample app in Docker.

Module 9: Mastering Git Basics for SCM

• Understand what SCM (Source Control Management) is and why it’s essential in modern software development.
• Learn what Git is and why it’s the most popular version control tool.
• Install Git and configure your username & email for tracking changes.
• Create your first Git repository (local & remote).
• Understand commits and commit messages.
• Learn how to clone, pull, and push code to GitHub/GitLab/Bitbucket.
• Work with branches for parallel development.
• Merge code and understand merge conflicts (and how to resolve them).
• Use Git log and Git diff to track changes.
• Learn Git status and Git add to keep your work organized.
• Explore tags for marking releases.
• Practice a team workflow with pull requests (PRs).

Module 10: Mastering kubernetes

• Introduction to Kubernetes – What is Kubernetes and why do we need it in modern application development?
• Kubernetes Architecture – Nodes, Pods, Deployments, Services, Control Plane, and Worker Nodes.
• Setting up Kubernetes – Installing Kubernetes using terraform on aws (step-by-step).
• Cluster Initialization – Bootstrapping the control plane and joining worker nodes.
• Installing a Pod Network (CNI Plugin) – Calico/Flannel setup for pod communication.
• Verifying the Cluster – Checking node status, pods, and cluster health.
• First Application Deployment – Deploying a sample NGINX application using a Deployment manifest.
• Scaling Applications – Horizontal scaling of pods with kubectl scale.
• Exposing Applications – Using NodePort/LoadBalancer/Ingress to make the app accessible.
• Hands-On Demo – Deploying and accessing the NGINX web page from Kubernetes cluster.

Real Time Concepts:

• Day to Day Admin Activities
• Frequently Occurring Issues
• Roles and Responsibilities
• Resume Preparation Guidance

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