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Why Infrastructure as Code (IaC)?

Lesson 16/50 | Study Time: 35 Min

As your infrastructure grows on AWS — more servers, more databases, more networking — managing it manually through the AWS Console becomes slow, error-prone, and impossible to scale. Infrastructure as Code solves this by letting you define, provision, and manage your entire infrastructure using code. 

What is Infrastructure as Code?

Infrastructure as Code means writing code — in files stored in a repository — that describes the infrastructure you want.

Instead of logging into the AWS Console and clicking buttons to create a server, you write a file that says "create an EC2 instance with these specifications" and a tool reads that file and builds it for you.

Run one command and the instance is created exactly as defined. Change the file and run again — the infrastructure updates to match.

The Problem with Manual Infrastructure

Before understanding the benefits of IaC, consider what manual management looks like in practice:


1. A developer creates an EC2 instance by clicking through the Console. No record of what settings were chosen.

2. A second developer tries to recreate the same setup in a different environment. They get something slightly different because they remember the steps differently.

3. Three months later, nobody knows why a security group has a particular rule — or who added it.

4. A misconfiguration causes an outage. The team spends hours figuring out what changed.


This is called configuration drift, environments slowly diverge from each other and from what anyone intended. IaC eliminates it.

Core Benefits of IaC


1. Consistency: The same code creates the same infrastructure every time — in development, staging, and production. No more "it works on my environment" problems caused by infrastructure differences.


2. Version Control: Because infrastructure is code, it lives in Git. Every change is tracked, every change has an author, and you can roll back to any previous state just like application code.


bash

# See who changed the VPC configuration and when

git log --oneline infrastructure/vpc.tf


# Roll back to a previous version

git revert abc1234

```


3. Repeatability: Need ten identical environments for testing? Run the code ten times. Need to rebuild production after a disaster? Run the code once. What used to take days of manual work takes minutes.


4. Automation: IaC integrates directly into your CI/CD pipeline. When infrastructure code changes are pushed and reviewed, the pipeline can automatically apply them — just like deploying application code.


5. Auditability: Every infrastructure change goes through a pull request, gets reviewed, and is recorded in Git history. This gives you a full audit trail — essential for security compliance and debugging.

IaC Tools on AWS

There are three main IaC tools you will use in this course:


IaC in a DevOps Workflow

IaC does not sit separately from your DevOps pipeline — it is part of it.


Developer writes IaC code

        │

        ▼

Pull request opened → Team reviews infrastructure changes

        │

        ▼

CI pipeline runs → Validates syntax, checks for security issues

        │

        ▼

Approved and merged → Pipeline applies the changes to AWS

        │

        ▼

Infrastructure updated automatically — no manual steps

Drew Collins

Drew Collins

Product Designer
Profile

Class Sessions

1- What is DevOps? Principles, Culture, and Practices 2- The DevOps Lifecycle 3- Introduction to Cloud Computing 4- AWS Global Infrastructure 5- Core AWS Services Overview 6- Git Fundamentals 7- Branching Strategies 8- Pull Requests and Code Review Best Practices 9- Integrating Git with AWS CodeCommit and GitHub 10- Managing Secrets and Sensitive Files in Repositories 11- What is CI/CD? 12- Building Pipelines with AWS CodePipeline and CodeBuild 13- Automated Testing in CI 14- Deployment Strategies 15- Using GitHub Actions and Jenkins on AWS 16- Why Infrastructure as Code (IaC)? 17- AWS CloudFormation 18- Terraform on AWS 19- AWS Cloud Development Kit (CDK) 20- IaC Best Practices 21- Docker Fundamentals 22- Amazon ECR 23- Deploying Containers with Amazon ECS 24- Kubernetes Basics and Amazon EKS 25- Integrating Containers into CI/CD Pipelines 26- Serverless Computing Concepts and Use Cases 27- Building and Deploying AWS Lambda Functions 28- Event-Driven Automation with Amazon EventBridge 29- Orchestrating Workflows with AWS Step Functions 30- API Gateway Integration for Serverless APIs 31- Introduction to MLOps 32- Training and Deploying Models with Amazon SageMaker 33- Automating ML Pipelines with SageMaker Pipelines 34- Using Amazon CodeWhisperer and AI Tools for Code Automation 35- AI-Powered Testing, Anomaly Detection, and Incident Prediction 36- Observability Fundamentals 37- Amazon CloudWatch 38- Distributed Tracing with AWS X-Ray 39- Centralised Logging with Amazon OpenSearch Service 40- Setting Up Automated Alerts and Incident Response Workflows 41- Shift-Left Security 42- IAM Roles, Policies, and Least-Privilege Access 43- Static Code Analysis and Vulnerability Scanning in CI/CD 44- AWS Security Hub, GuardDuty, and Config for Compliance 45- Secrets Management with AWS Secrets Manager and Parameter Store 46- AWS Well-Architected Framework 47- Auto Scaling and Elastic Load Balancing for Resilience 48- Cost Monitoring with AWS Cost Explorer and Budgets 49- Disaster Recovery Strategies 50- Preparing Your Project for Production