Embarking on the Cloud Resume Challenge was a defining moment in my cloud journey. It gave me the opportunity to dive into Infrastructure as Code (IaC) while building a tangible, functional project: a visitor counter for my resume. This blog post outlines the steps I took to set up the infrastructure and the lessons I learned along the way.
Overview
At the heart of this project is a visitor counter, showcasing how serverless architecture can deliver scalable and efficient solutions. The counter not only tracks page visits but also highlights my skills in cloud development.
Key Components
DynamoDB Table
- Acts as the database for storing visitor counts persistently. Its managed nature ensures scalability and minimal maintenance.
AWS Lambda Function
- A serverless function that processes requests to increment and retrieve the visitor count. Lambda ensures low latency and high efficiency.
API Gateway
- A bridge between the frontend and backend, exposing the Lambda function as a secure HTTP API endpoint.
Deployment Instructions
Deploying this infrastructure required leveraging the AWS Serverless Application Model (SAM). Here’s how I went about it:
Install AWS SAM CLI
- The AWS SAM CLI is the backbone of the deployment process. Installation instructions can be found here.
Build the Application
- Running
sam buildcompiles the Lambda function and prepares the resources for deployment.
- Running
Deploy the Application
- Using the guided deployment commands. I configured my stack name, region, and IAM roles. This step created and linked the necessary AWS resources.
Post-Deployment Configuration
After the deployment process:
I retrieved the API Gateway URL from the output. This endpoint was integrated with my frontend to make API requests.
I carefully reviewed and updated permissions, adhering to the principle of least privilege to secure my infrastructure.
Future Improvements
While this project is functional, there’s always room for enhancements:
Monitoring and Alerts: Integrating AWS CloudWatch to monitor performance and set up failure alerts.
Automated Testing: Adding unit tests for the Lambda function and integration tests for the API Gateway.
Scalability: Configuring DynamoDB auto-scaling for high-traffic scenarios.
Reflections and Next Steps
This challenge was more than a technical exercise—it was a chance to combine my learning with real-world implementation. From crafting serverless workflows to deploying resources with IaC, I gained hands-on experience in core AWS services.
Next, I plan to start implementing Terraform infrastructure in different projects and continue exploring advanced AWS certifications.
Are you ready to take on your own Cloud Resume Challenge? Dive in, learn, and build something amazing. If you’ve tried this or are considering it, I’d love to hear about your journey. Let’s connect and share ideas! 🚀