initial commit

[mvsnogueira-dnx]

Describe the big picture of your changes here to communicate to the maintainers why we should accept this pull request. If it fixes a bug or resolves a feature request, be sure to link to that issue.

Types of changes

What types of changes does your code introduce to <repo_name>?
Put an x in the boxes that apply

• Bugfix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Documentation Update (if none of the other choices apply)

Checklist

Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your code.

• I have read the CONTRIBUTING.md doc.
• I have added necessary documentation (if appropriate).
• Any dependent changes have been merged and published in downstream modules.

Further comments

If this is a relatively large or complex change, kick off the discussion by explaining why you chose the solution you did and what alternatives you considered, etc...

[amazon-q-developer]

⏳ Code review in progress. Analyzing for code quality issues and best practices. You can monitor the review status in the checks section at the bottom of this pull request. Detailed findings will be posted upon completion.

Using Amazon Q Developer for GitHub

Amazon Q Developer¹ is an AI-powered assistant that integrates directly into your GitHub workflow, enhancing your development process with intelligent features for code development, review, and transformation.

Slash Commands

Command	Description
/q <message>	Chat with the agent to ask questions or request revisions
/q review	Requests an Amazon Q powered code review
/q help	Displays usage information

Features

Agentic Chat
Enables interactive conversation with Amazon Q to ask questions about the pull request or request specific revisions. Use /q <message> in comment threads or the review body to engage with the agent directly.

Code Review
Analyzes pull requests for code quality, potential issues, and security concerns. Provides feedback and suggested fixes. Automatically triggered on new or reopened PRs (can be disabled for AWS registered installations), or manually with /q review slash command in a comment.

Customization

You can create project-specific rules for Amazon Q Developer to follow:

1. Create a .amazonq/rules folder in your project root.
2. Add Markdown files in this folder to define rules (e.g., cdk-rules.md).
3. Write detailed prompts in these files, such as coding standards or best practices.
4. Amazon Q Developer will automatically use these rules when generating code or providing assistance.

Example rule:

All Amazon S3 buckets must have encryption enabled, enforce SSL, and block public access.
All Amazon DynamoDB Streams tables must have encryption enabled.
All Amazon SNS topics must have encryption enabled and enforce SSL.
All Amazon SNS queues must enforce SSL.

Feedback

To provide feedback on Amazon Q Developer, create an issue in the Amazon Q Developer public repository.

For more detailed information, visit the Amazon Q for GitHub documentation.

Footnotes

1. Amazon Q Developer uses generative AI. You may need to verify generated code before using it in your environment. See the AWS Responsible AI Policy. ↩

[amazon-q-developer]

Review Summary

This PR introduces a comprehensive Terraform module for AWS Serverless Image Handler, converting from CloudFormation to Terraform. While the overall architecture is sound, there are several critical issues that must be addressed before merge:

Critical Issues Found:

1. Missing Lambda Function URL: CloudFront references a Lambda Function URL that is never created, causing deployment failure
2. Security Vulnerability: Overly permissive S3 access policy grants s3:* permissions instead of following least privilege
3. Lambda Naming Issue: Function name can exceed AWS 64-character limit
4. IAM Policy Logic Error: Secrets Manager ARN construction fails when variable is empty
5. Documentation Error: README references non-existent placeholder files

Recommendations:

• Add the missing aws_lambda_function_url resource for the non-S3-Object-Lambda path
• Implement proper input validation for Lambda memory and timeout variables
• Fix security issues by restricting IAM permissions to minimum required
• Update documentation to reflect actual implementation

The module shows good practices with conditional resource creation, proper tagging, and comprehensive feature coverage. Once the critical issues are resolved, this will be a solid Terraform module for serverless image processing.

---

You can now have the agent implement changes and create commits directly on your pull request's source branch. Simply comment with /q followed by your request in natural language to ask the agent to make changes.

[amazon-q-developer]

🛑 Logic Error: Lambda Function URL is referenced but never created. The CloudFront distribution will fail to deploy because the Lambda Function URL resource is missing.

[jsalszbrun]

Looks good to me!

[github-actions]

I'm going to lock this pull request because it has been closed for 30 days ⏳. This helps our maintainers find and focus on the active issues. If you have found a problem that seems related to this change, please open a new issue and complete the issue template so we can capture all the details necessary to investigate further.