Real-World AWS Projects

# CHAPTER 29

Real-World AWS Projects #

1. Introduction #

Reading about cloud computing is not enough to get hired. Employers do not hire candidates who have merely passed multiple-choice exams; they hire candidates who can prove they have navigated the AWS Console, debugged IAM permission errors, and wired services together successfully. In this chapter, we transition from theory to practice. We outline five production-grade portfolio projects, escalating in difficulty, designed to demonstrate your competency as a Cloud Engineer.

2. Learning Objectives #

By the end of this chapter, you will be able to:

• Synthesize multiple AWS services into cohesive architectures.

• Build a cloud-native portfolio to showcase to employers.

• Understand the architectural diagrams of common enterprise workloads.

• Translate business requirements into AWS technical implementations.

3. Project 1: The Serverless Cloud Resume (Beginner) #

The Goal: Stop sending PDF resumes. Host your resume as a live, highly scalable, serverless website with a dynamic visitor counter. The Architecture:

1. 1. Frontend: Write a simple HTML/CSS resume. Upload it to an Amazon S3 bucket configured for Static Website Hosting.

1. 2. CDN: Place an Amazon CloudFront distribution in front of the S3 bucket to provide HTTPS encryption and global caching.

1. 3. DNS: Purchase a domain (e.g., yourname.com) and use Amazon Route 53 to route traffic to CloudFront using an Alias Record.

1. 4. Database: Create an Amazon DynamoDB table with a single item: {"id": "visitors", "count": 0}.

1. 5. Backend Logic: Write a Python AWS Lambda function that reads the DynamoDB count, adds +1, saves it back, and returns the new count.

1. 6. API: Create an Amazon API Gateway HTTP API that triggers the Lambda function. Have your frontend JavaScript call this API when the page loads to display the visitor count!

4. Project 2: The WordPress Multi-Tier Migration (Intermediate) #

The Goal: Architect a traditional, highly available 2-tier web application using standard EC2 and RDS. The Architecture:

1. 1. Networking: Create a custom VPC with 2 Public Subnets and 2 Private Subnets spanning two Availability Zones.

1. 2. Database Tier: Launch an Amazon RDS (MySQL) database into the Private Subnets. Enable Multi-AZ for disaster recovery. Ensure its Security Group ONLY allows Port 3306 from the Web Server Security Group.

1. 3. Web Tier: Launch an EC2 Instance in a Public Subnet. SSH into it, install PHP/Apache, and install WordPress. Connect WordPress to the RDS endpoint.

1. 4. Storage: Install a WordPress plugin that forces all image uploads to save directly to an Amazon S3 bucket rather than the EC2 hard drive, ensuring the EC2 instance remains stateless.

1. 5. Load Balancing: Place an Application Load Balancer (ALB) in front of the EC2 instance, distributing public traffic across the public subnets.

5. Project 3: The Elastic API Auto Scaler (Intermediate) #

The Goal: Prove you understand elasticity by forcing an application to scale out under simulated heavy load. The Architecture:

1. 1. The AMI: Launch an EC2 instance. Install Node.js and write a simple Express API that intentionally contains a computationally heavy math loop to spike the CPU. Create an Amazon Machine Image (AMI) of this server.

1. 2. The Template: Create a Launch Template using your custom AMI.

1. 3. The ASG: Create an Auto Scaling Group (ASG) spanning two AZs. Set Min: 2, Max: 6. Create a Target Tracking Scaling Policy targeting 50% CPU utilization.

1. 4. The Test: Attach an Application Load Balancer. Use a free load-testing tool (like Apache JMeter or artillery.io) on your laptop to bombard the ALB DNS URL with 5,000 requests.

1. 5. The Result: Watch CloudWatch. As the CPU spikes to 100%, take screenshots of the ASG automatically spinning up instances 3, 4, 5, and 6. As you turn off the load tester, screenshot the ASG terminating the excess instances to save money.

6. Project 4: The Dockerized Microservice (Advanced) #

The Goal: Demonstrate modern container orchestration by deploying a Dockerized application without managing any servers. The Architecture:

1. 1. Containerize: Write a simple Python/Flask application. Write a Dockerfile. Build the image on your local machine.

1. 2. Registry: Create a private repository in Amazon ECR. Authenticate your Docker CLI with AWS, and push the image to ECR.

1. 3. Orchestration: Create an Amazon ECS Cluster using the AWS Fargate template.

1. 4. Task Definition: Create a Task Definition pointing to your ECR image URL, requesting 1GB RAM and 0.5 vCPU.

1. 5. Deployment: Create an ECS Service running 2 desired tasks, placed behind an Application Load Balancer. Verify the containers are running on serverless Fargate infrastructure.

7. Project 5: The Infrastructure-as-Code Automation (Advanced) #

The Goal: Prove you can automate everything. Never use the AWS Console. The Architecture:

1. 1. The Blueprint: Write an AWS CloudFormation YAML template (or a Terraform configuration).

1. 2. The Code: The template must programmatically define a VPC, an Internet Gateway, a Public Subnet, a Security Group allowing Port 80, and an EC2 instance running a simple web server via UserData script.

1. 3. The Deployment: Open your local terminal. Use the AWS CLI command: aws cloudformation create-stack --stack-name PortfolioStack --template-body file://my-infra.yaml.

1. 4. The Cleanup: Prove you understand financial safety by running aws cloudformation delete-stack --stack-name PortfolioStack to instantly wipe the entire architecture from existence.

8. How to Present Your Projects #

Do not just build them; document them.

• GitHub: Create a GitHub repository for each project.

• Architecture Diagrams: Use a free tool like Draw.io to draw the AWS architecture diagram (VPC boundaries, icons for EC2, RDS, ALB, etc.) and put it in the README.md.

• The Narrative: In the README, explain *why* you chose specific services. "I chose DynamoDB instead of RDS for the visitor counter because it offers single-digit millisecond latency and serverless pricing for simple key-value lookups." This proves you think like an architect.

9. Summary #

In Chapter 29, we transitioned from academic learning to practical engineering. We mapped out five ascending portfolio projects designed to exercise the entirety of the AWS curriculum. From establishing a serverless static resume using S3 and Lambda, to architecting highly available WordPress multi-tier networks, and finally deploying containerized microservices via ECS Fargate and CloudFormation automation. Completing these projects proves to employers that you possess the hands-on capability to build, scale, and secure production cloud environments.

10. Next Chapter Recommendation #

Your portfolio is built. It is time to prepare for the technical interview and plan your career path. Proceed to Chapter 30: AWS Interview Questions and Career Roadmap.