Well Architected Iac Analyzer

Sample Generative AI tool for evaluating Infrastructure as Code and architecture diagrams against AWS Well-Architected best practices.

Blockchain & Cloud ComputingTypeScriptMIT-0

Abstract

Well Architected Iac Analyzer is an open-source Blockchain & Cloud Computing project. Sample Generative AI tool for evaluating Infrastructure as Code and architecture diagrams against AWS Well-Architected best practices. Well-Architected Infrastructure as Code (IaC) Analyzer is a sample project that demonstrates how generative AI can be used to evaluate infrastructure code for alignment with best practices. It is built using TypeScript, AWS. Key capabilities include: NEW Prioritization Framework with Eisenhower Matrix:; Each Not Applied best practice is scored with Criticality (from Knowledge Base Risk Level), Complexity (remediation effort), and Priority (Immediate | Short-term | Long-term) derived via the Eisenhower Matrix; Click any point on the matrix to open a details panel with the best practice's status reason, recommendation, and Criticality/Complexity/Priority reasons, or ask the Analyzer Assistant about it in one click. The complete source code is publicly available on GitHub under the MIT No Attribution, making it a useful reference for students building a Blockchain & Cloud Computing mini project or final-year project.

1. Introduction

Well-Architected Infrastructure as Code (IaC) Analyzer is a sample project that demonstrates how generative AI can be used to evaluate infrastructure code for alignment with best practices.

It features a modern web application built with React and AWS Cloudscape Design System, allowing users to upload IaC documents (e.g., AWS CloudFormation, Terraform, or AWS CDK templates), complete IaC projects (multiple files or zip archives), or architecture diagrams for assessment. The application leverages Amazon Bedrock to analyze the infrastructure against AWS Well-Architected best practices. These best practices are sourced from AWS Well-Architected whitepapers and synchronized with the Amazon Bedrock knowledge base.

Additionally, an interactive Analyzer Assistant chatbot enables users to ask questions, seek clarification, and receive personalized guidance about analysis results and Well-Architected best practices.

2. Objective

Sample Generative AI tool for evaluating Infrastructure as Code and architecture diagrams against AWS Well-Architected best practices.

This project demonstrates how TypeScript, AWS can be applied to a real-world Blockchain & Cloud Computing problem.

3. Key Features / Modules

  • NEW Prioritization Framework with Eisenhower Matrix:
  • Each Not Applied best practice is scored with Criticality (from Knowledge Base Risk Level), Complexity (remediation effort), and Priority (Immediate | Short-term | Long-term) derived via the Eisenhower Matrix
  • Click any point on the matrix to open a details panel with the best practice's status reason, recommendation, and Criticality/Complexity/Priority reasons, or ask the Analyzer Assistant about it in one click
  • Filter the analysis by Criticality, Complexity, or Priority to focus remediation planning, and export all fields to CSV
  • NEW Enhanced AI Capabilities with Latest Anthropic Models:
  • Full support for Claude Fable 5.1, Claude Opus 5, Claude Sonnet 5 (default), Claude Fable 5 and Claude Opus 4.8
  • Supported Claude models leverage Adaptive Thinking for complex reasoning and analysis
  • Switch models at deployment time via the ModelId CloudFormation parameter or config.ini (e.g. global.anthropic.claude-fable-5-1, global.anthropic.claude-opus-5)
  • Accelerated Analysis with Parallel Processing:
  • Configurable batch size controls how many Well-Architected (or selected Lens) questions are processed in parallel

4. Technology Stack

TypeScriptAWS

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

  • Node.js (LTS) and npm / yarn / pnpm
  • VS Code or any code editor
  • Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/aws-samples/well-architected-iac-analyzer.git
cd well-architected-iac-analyzer
  1. Option 1: Using a CloudFormation Deployment Stack (Recommended)
  2. Option 2: Using a Deployment Script
  3. Option 3: Manual Deployment
  4. Download the CloudFormation template: iac-analyzer-deployment-stack.yaml
  5. Open the AWS CloudFormation console:
  6. Make sure you are in the same AWS region where you enabled access to the LLM models
  7. On the "Create stack" page:
  8. Select "Upload a template file" and upload the iac-analyzer-deployment-stack.yaml template

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

  • Add a CI/CD pipeline with GitHub Actions
  • Deploy to a public test network or cloud free tier
  • Add monitoring and cost alerts

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

  1. Why does this problem need a blockchain or cloud-native design?
  2. Explain the smart contract / infrastructure components and how they interact.
  3. How are gas costs or cloud costs kept under control?
  4. How is the system secured (keys, IAM, access control)?
  5. How would the solution scale to many more users?

9. Source Code & License

This project is developed by aws-samples and published on GitHub under the MIT No Attribution. Please follow the license terms and credit the original author when you use or modify this code.

View Source on GitHubDownload ZIP

Want to build this as your internship project?

Work on a Blockchain & Cloud Computing project like this with mentor guidance, weekly reviews and an internship certificate from Training Trains, Erode — online or offline.

Apply for Blockchain & Cloud Computing Internship