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Q-bits: CloudFront Deployment with Amazon Q and Terraform

This post showcases how Amazon Q Developer streamlines AWS infrastructure deployment with Terraform, demonstrating practical examples of CloudFront, S3, and security configurations. It highlights how Amazon Q's AI capabilities help developers create and maintain AWS infrastructure while following best practices.

q-bitsamazon-q-developerterraformcloudfrontroute53
Urvi Sharma
Amazon Employee
Published Feb 25, 2025
Welcome to another installment of Q-Bits, our regular series showcasing cool ways Amazon employees are leveraging Amazon Q Developer. In this article, we'll explore how Amazon Q enhances developer productivity, provides recommendations, and helps maintain AWS best practices when deploying an AWS Infrastructure using Terraform. Amazon Q Developer aids in creating CloudFront distribution, explaining code assets, demonstrating integration with custom SSL certificate, and providing examples of Lambda@Edge use-cases.

Introduction

Terraform is a powerful Infrastructure as Code (IaC) tool that transforms how organizations manage their AWS infrastructure. Instead of manually clicking through the AWS Console, Terraform allows you to define your infrastructure in code using a declarative language. This means you can version control your infrastructure, automate deployments, and ensure consistent environments across development, staging, and production.
Prerequisites
To get started you will need the following:
  • An AWS Account
  • AWS CLI configured with your credentials
  • An IDE for your programming language, in this case I am using Visual Studio Code
  • Amazon Q Developer plugin

Leveraging Amazon Q for CloudFront Infrastructure Design

I started with a seemingly complex request with the following prompt - "Create a Terraform template for a simple S3 website with CloudFront in front of it and add basic WAS rules. Explain the CloudFront distribution, behaviour and origin configurations. Demonstrate a simple Lambda@Edge integration and custom SSL certificate."
Amazon Q not only understood the request but generated a complete Terraform template, breaking down complex configurations into manageable components.
The infrastructure generated by Amazon Q prioritizes security and performance, with CloudFront distribution including Origin Access Control for secure Amazon S3 access and optimized caching policies. The integration of AWS WAF provided essential protection against common web vulnerabilities. Amazon Q configured multiple security layers through WAF rules, custom SSL certificates, and Lambda@Edge integration for security headers.
Amazon Q shared the following explanations about the code that it generated:
  1. CloudFront Distribution Configuration:
    • Origin Configuration: Uses Origin Access Control (OAC) for secure S3 access
    • Default Cache Behavior:
      • Allows GET, HEAD, OPTIONS methods
      • Redirects HTTP to HTTPS
      • Uses optimized caching policy
      • Integrates Lambda@Edge for security headers
    • Custom error handling for SPA support
    • SSL/TLS configuration with custom certificate
    • WAF integration for security
  2. Cache Behavior:
    • Uses managed cache policy for optimal caching
    • Implements compression for faster delivery
    • Configures CORS handling through origin request policy
    • Lambda@Edge adds security headers to all responses
  3. Security Features:
    • WAF basic rules using AWS managed rule sets
    • Custom SSL certificate for HTTPS
    • Security headers via Lambda@Edge
    • S3 bucket policy restricting access to CloudFront
    • Origin Access Control for secure S3 access
  4. Lambda@Edge Integration:
    • Adds security headers to all responses
    • Runs in the viewer-response phase
    • Implements common security headers (HSTS, XSS protection, etc.)
This setup provides:
  1. Secure static website hosting
  2. Global content delivery
  3. Basic security protections
  4. Custom domain support
  5. SPA support through custom error responses
  6. Performance optimization through caching
  7. Security headers through Lambda@Edge
Remember to:
  1. Initialize Terraform
  2. Set up your AWS credentials
  3. Replace variable values as needed
  4. Handle DNS records separately (Route 53 or your DNS provider)
  5. Upload your website content to the S3 bucket

Terraform Deployment

When implementing Terraform in production environments Amazon Q's step-by-step guidance through the deployment process. The platform provided clear instructions for organizing project files, setting up environment variables, and executing deployment commands. The implementation included best practices for different environments, ensuring a robust deployment strategy.

Optimizing CloudFront Content Delivery and Cache Management

Amazon Q helped create a basic website structure and provided clear instructions for content deployment. The integration between S3 and CloudFront was seamless, with proper cache invalidation steps detailed for optimal performance. The solution included a basic website structure with the following deployment commands:

Route 53 Integration and SSL/TLS Implementation

Once prompted to Q on how to create Route53 DNS records while making the updates consistent with the rest of the files, it was able to tell me how to add Route53 configuration files.
The configuration included:
  1. Reference to my existing Route 53 hosted zone
  2. Create an A record pointing to my CloudFront distribution
  3. Create validation records for my ACM certificate
  4. Validate the certificate automatically
Amazon Q also recommended additional changes to maintain code consistency across all files. A key suggestion was updating the CloudFront distribution configuration to wait for certificate validation completion before proceeding. This change ensures proper SSL implementation and prevents deployment issues that could arise from timing mismatches between certificate validation and distribution creation.
Amazon Q provided specific commands to implement and apply these changes:
This is what it suggested further:
  1. Ensure your domain is registered
  2. Have a Route53 hosted zone for your domain
  3. Make sure your AWS account has the necessary permissions for Route53
When I encountered certificate validation issues, the workspace analysis feature proved invaluable, analyzing configurations and providing targeted solutions.
After analyzing my workspace, Amazon Q identified that the error stemmed from referencing an undefined resource in the CloudFront configuration and provided solutions to resolve this issue.
This worked! In just a few hours, I could create a Terraform template and deploy proper AWS infrastructure.

Best Practices and Enhancements

Amazon Q emphasized the importance of using Remote State Storage, implementing workspace environments, and managing environment-specific variables. The platform recommended regular security audits and performance monitoring practices. The tool went beyond basic setup, recommending additional website features, performance optimizations, and security enhancements.

Amazon Q's Role in IaC Development

Implementation with Amazon Q demonstrates how AI can accelerate infrastructure development while reducing configuration errors. The solution automatically implemented best practices and provided contextual learning opportunities, making complex infrastructure setup more accessible to developers at all skill levels.

Implementation Guidelines with Amazon Q

Here are some practical tips I learned while working with Amazon Q:
  1. Leverage @workspace: Command Always use @workspace in your prompts when asking about existing code. This helps Amazon Q understand your entire project context and aligns with AWS's emphasis on comprehensive environment understanding.
  2. Break Down Complex Requests: Start with core infrastructure, then add security layers, and finally specific customization. This incremental approach aligns with AWS's well-architected framework.
  3. Prioritize Security: Ask Amazon Q to review security configurations, verify IAM permissions, and validate SSL/TLS setups. Always cross-check with AWS security best practices.
  4. Seek Explanations: When Amazon Q generates code, ask for explanations. This helps you understand each component and its purpose within your AWS infrastructure.
  5. Effective Error Resolution: When encountering errors, you can provide the full error message and use @workspace for context. Amazon Q can then analyze your code and offer targeted solutions.
  6. Documentation and Review: When implementing Amazon Q's suggestions, always review against official AWS documentation. Check resource configurations, compliance requirements, and potential cost implications.
Remember: Amazon Q is a powerful assistant, but always review and understand the code it generates before implementing it in production.

Conclusion

This Terraform implementation with Amazon Q showcases the future of infrastructure development. AI-powered tools like Amazon Q can significantly enhance infrastructure development while maintaining high standards for security and best practices. The combination of automated configuration generation, intelligent error resolution, and best practice implementation makes it an invaluable tool for modern cloud infrastructure development.
While it's an incredibly powerful tool, it's important to remember that it's an aid, not a replacement for understanding your infrastructure. Best practices include reviewing generated configurations thoroughly, test in non-production environments, and maintain security best practices while using AI as a guide.
 

Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.

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