AI-Driven Infrastructure as Code (IaC) and Cloud Automation

Name: AI-Driven Infrastructure as Code (IaC) and Cloud Automation
Rating: 4.5 (141 reviews)

Build 5 AIOps Projects to learn how to build IaC with GenAI, Vibe Coding, Prompt Engineering and Specs writing.

Highest Rated

Created byGourav J. Shah, School of Devops & AI

Last updated 7/2025

English

English [Auto],

What you'll learn

Use AI-assisted coding workflows to write and manage Infrastructure as Code (IaC)
Provision cloud infrastructure using Terraform, Pulumi, CloudFormation, and Ansible
Leverage AI developer tools like GitHub Copilot, Cursor, and Kiro IDE in vibe and spec modes
Use agentic workflows and MCP Servers to enhance IaC security, compliance, and best practices
Create GitOps-style pipelines with AI-powered PR reviews and automated IaC delivery
Secure and validate IaC with tools like Checkov, tfsec, and OPA/Conftest
Complete a capstone project to provision secure, production-grade cloud environments with AI assistance

Course content

3 sections • 35 lectures • 5h 37m total length

Module Intro2:19
What is AI Driven IaC as why should you care ?9:15
Explore the evolution from manual server config to AI-driven infrastructure as code, using natural language prompts to generate, test, and secure IaC with tools like Terraform and CloudFormation.
What is Vibe Coding Afterall - Getting started with the Concepts11:27
Explore vibe coding, an AI-assisted approach that prioritizes intent over implementation, generates architecture and code, and refines results through conversation toward spec workflows.
Emergence of AI-Augmented Bionic Devops Engineer10:37
Discover AI-augmented DevOps engineering, a bionic blend of human intuition and AI that shifts responsibilities toward intent over syntax and strategic outcomes.
Setting up VSCode, Terraform, AWS, GitHub Copilot8:57
Set up VS Code with GitHub Copilot to generate a Terraform EC2 deployment on AWS using natural language prompts, including a security group and SSH key, within the free tier.
Project Spec and Tools Overview13:37
Set up prerequisites for AI-driven IaC and cloud automation, including Terraform, AWS CLI, Git, VS Code, and GitHub Copilot; configure AWS credentials and explore VS Code extensions.
Vibe Code Principle 1 - Starting with the Intent10:20
Start with the intent to generate terraform code for a free-tier EC2 in Oregon, using AWS provider and latest Amazon Linux AMI, with security rules and human-in-the-loop review.
Vibe Code Step 2 - Iterative Refinement9:06
In this vibe code session, explore ai-driven infrastructure as code by iteratively refining terraform code across models, adding key pairs, security groups, and tags.
Project wrap up, Key takeaways and Cleaning up9:06
Learn to safely clean up Terraform infrastructure with terraform destroy and guardrails, and explore AI-driven documentation prompts to produce a ready readme and best practices.

Module Intro1:55
Master ai-driven infrastructure as code for cloud automation by building a production-grade, three-tier web app deployed with Terraform, guided by prompt engineering and MCP servers to access docs.
Vibe Coding Recap and using Copilot Agentic Capabilities10:05
Build a production-ready three-tier PHP app using AI-driven Terraform workflows and GitHub Copilot’s agentic capabilities in VS Code.
Project Spec Deep Dive - 3 Tier Infra Provisioning with Terraform11:22
Design a highly available, three-tier infra with Terraform for a PHP web app connected to a MySQL database, using VPC, subnets, security groups, app load balancer, and auto scaling.
Quick Overview of Terraform Concepts9:22
Explore Terraform as code for cloud provisioning with providers, modules, and data sources. Learn plan, apply, destroy workflows, state locking, and reusable registries.
Why do you need MCP Server for Terraform ?7:41
Build a base VPC with a 10.42.0.0/16 CIDR, four subnets in two availability zones, and public and private route tables with an internet gateway. Integrate Terraform MCP server via Docker.
Connecting Copilot with Terraform Documentation using MCP12:51
Connect Copilot to Terraform documentation via Docker MCP gateway in VS Code to explore AWS VPC modules and deploy a 3-tier infrastructure using VPC, EC2, ELB, Auto Scaling, and RDS.
Generating Terraform code for VPC with AI10:30
Explore generating an aws vpc with two public and two private subnets across two availability zones using terraform, with proper routing, internet gateway, and security groups for web and database.
Setting up MySQL RDS with Prompts17:25
Use prompts to configure a MySQL RDS on AWS DS, prioritizing the free tier, private subnets, subnet groups, and a referenced security group, with Terraform state and outputs.
Provisioning EC2 Instance with User Data using Copilot11:47
Provision an EC2 web server with a user data script using Copilot, selecting the latest Ubuntu AMI on a free-tier t2 micro in a public subnet, and open port 80.
Adding Database Configurations with AI10:08
Learn how AI assists configuring databases in Terraform deployments, generating config.ini with hostname, username, password, and applying the SQL schema via provisioners and remote execution on the web server.
Summary2:11
Delve into prompt engineering and vibe coding, share prompts as specs within a project using the Cairo IDE for spec-driven development, and build an MVP.

Module Intro1:27
Discover spec driven AI development and AI code generation, guided by Gaurav, and learn why to use Amazon Cairo and how to apply these concepts across IDEs.
Understanding Concepts related to Spec Based AI Coding9:38
Explore spec driven ai coding for infrastructure as code, from wip prompts to declarative specs. Learn specs, agent steering, and MCP integration, and how a spec native ide enables consistency.
Introduction to Kiro - Spec Native AI Idea by Amazon5:09
Explore Cairo dev, the official Cairo IDE, and its spec-driven workflow from requirements and design to tasks, with AI agentic hooks that auto-update documentation using markdown specs and steering files.
Overview of the Project you will build in this Module6:01
Elevate the MVP into a high-availability, scalable infra with a load balancer, a target group, and auto scaling, using Cairo IDE for AI-driven code generation.
Exploring Kiro IDE Intrface and Components10:11
Set up hero IDE and configure terraform extensions to manage VPC, RDS, and EC2. Adopt RSpec approach to add auto scaling with an application load balancer and explore Cairo specs.
Step 1 - Analysing User Stories and Requirements9:29
Explore defining high-availability and scalable web applications with auto scaling and load balancing, guided by user stories, acceptance criteria, and a design-to-implementation workflow in AI-assisted IaC.
Step 2 - Analying Design Spec created by Kiro12:27
Analyze the design spec created by Kiro to translate requirements into a high-availability, scalable, and secure architecture, detailing alb, target groups, autoscaling, cloudwatch alarms, subnets, and RDS.
Step 3 - Reviewing Implementation Plan and Tasks List5:22
Explore how AI-driven infrastructure as code accelerates cloud automation, detailing a spec-driven workflow that uses Cairo to generate and review a launch template, ALB setup, auto scaling, and Terraform validation.
Configuring Agent Steeing and Agent Hooks11:03
Define agent steering and hooks to enforce guardrails, generate documentation, and drive automated task execution for an AI-driven IaC and cloud automation workflow.
Analysing the first Task Execution7:47
Explore ai-driven infrastructure as code (IaC) and cloud automation by generating launch templates, reviewing plans, validating documentation, and aligning tasks with a human-in-the-loop workflow.
Generating Terraform Validation Code with Tasks16:48
Demonstrates end-to-end terraform validation code generation from spec to execution, including agent steering, task execution, hooks, documentation updates, and automated testing of a load balancer, target groups, and autoscaling.
Applying Terraform Code and Troubleshooting Issues with AI Agent18:53
Apply terraform with auto approve to deploy VPC, RDS, EC2, and auto scaling with a load balancer, while diagnosing and correcting health check issues in a Terraform-based IaC workflow.
Refining and Iterating with Code Agent to fix AMI and Health Checks17:57
Leverage ai-generated Terraform to build a custom AMI and refine health checks by adjusting path and interval, while iterating via design documents, revision control, and planned implementation steps.
Running Validation and Final Verdict with Spec driven AI Coding12:33
Validate infrastructure as code with a spec-driven AI coding workflow that checks Terraform state against AWS resources, including VPC, subnets, and auto scaling.
Summary2:47
Explore how AI-driven infrastructure as code enables spec-driven code generation and automated workflows, from user stories to design, implementation, and guardrails.

Requirements

A basic understanding of cloud computing and DevOps concepts
Prior experience with any scripting or programming language
Familiarity with version control (e.g., Git and GitHub)
Access to an AWS Free Tier account (optional: GCP)
A modern code editor (VSCode recommended)
Installed Terraform CLI, Python, and Checkov for local labs
Willingness to explore AI tools (Copilot, Cursor, Kiro IDE)

Description

Unlock the next generation of Infrastructure as Code (IaC) with the power of AI.

In this hands-on, project-driven course, you'll learn how to combine popular IaC tools like Terraform, Pulumi, and Ansible with cutting-edge AI assistants such as GitHub Copilot, Cursor, and Kiro IDE. You'll not only automate cloud provisioning but also secure, validate, and optimize your code using MCP servers, Checkov, and GitHub Actions.

You’ll start with vibe mode AI coding in VSCode and gradually transition to spec mode with Kiro IDE. You’ll build multi-cloud, multi-tool workflows and integrate security-first practices using tfsec and Checkov — all driven by AI.

Whether you’re provisioning an EC2 instance, deploying a multi-tier app, or securing GitOps pipelines, you’ll do it with intelligent, AI-enhanced speed.

This course includes:

Realistic labs and guided projects using AWS Free Tier
End-to-end IaC automation pipelines with AI tools
Deep integration with the AWS Terraform MCP server for best practices and compliance
A capstone project that delivers a production-grade cloud environment using Terraform, Ansible, GitHub Actions, and AI remediation
Bonus content on Prompt Engineering for IaC, DevOps portfolio building, and interview preparation

Perfect for DevOps engineers, SREs, and cloud professionals ready to level up their automation game.

Enroll now to become fluent in the future of IaC and Cloud Automation — powered by AI.

Who this course is for:

DevOps Engineers looking to modernize their IaC workflows
Platform Engineers interested in automating infrastructure provisioning
Site Reliability Engineers (SREs) seeking secure and scalable infra delivery pipelines
Cloud Engineers aiming to use AI-powered tools for faster, safer deployments
Professionals preparing for AI-integrated DevOps and IaC interviews
Anyone building a GitHub portfolio of AI-enhanced infrastructure projects

AI-Driven Infrastructure as Code (IaC) and Cloud Automation

What you'll learn

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Course content

Iac Code Generation with AI - From Zero to Vibe Coding9 lectures • 1hr 25min

Build a Terraform Module using Code Agents11 lectures • 1hr 45min

AI Agent Augmented, Spec Driven Coding with Kiro IDE15 lectures • 2hr 28min

Requirements

Description

Who this course is for: