Terraform Advisor Crew

Welcome to the Terraform Advisor Crew project, powered by crewAI. This project enables you to automatically analyze any Terraform GitHub repository, evaluate its infrastructure-as-code against AWS best practices (leveraging the AWS Well-Architected Framework), and generate a comprehensive technical report. The analysis and reporting process is driven by a team of specialized AI agents.

With Terraform Advisor Crew, you can:

• Analyze the architecture, security, and implementation patterns of any Terraform codebase
• Benchmark the repository against AWS Well-Architected Framework pillars and best practices
• Receive actionable recommendations, risk assessments, and improvement roadmaps in a structured report

Installation

Prerequisites

Ensure you have the following installed on your system:

• Python >=3.10 <3.13
• UV for dependency management and package handling

Setup

Clone this repository:

git clone https://github.com/56kcloud/terraform_advisor_by_56k.git

Navigate to your project directory and create a virtual environment and activate it:

cd terraform_advisor_by_56k
uv venv
source .venv/bin/activate

Install crewai inside the virtual environment:

uv tool install crewai

Install the project dependencies:

crewai install

Environment Configuration

Create your .env file by copying the example:

cp .env.example .env

You'll need to configure the following in your .env file:

• OPENAI_API_KEY: Your OpenAI API key for agent interactions
• GITHUB_TOKEN: A GitHub Personal Access Token for repository analysis

The .env file also allows you to customize:

• Target GitHub repositories for analysis
• LLM models

Running the Project

To analyze a Terraform GitHub repository and generate a best-practices report, run the following command from the root folder of your project:

crewai run

This command will:

• Assemble the AI agents as defined in your configuration
• Analyze the target repository and AWS documentation
• Produce a detailed report

The generated report and all outputs will be saved in the output folder in your project root.

Note:
If you want to analyze a different GitHub repository after having already run the crew, it is recommended to delete the db folder in your project root. This folder contains cached data and content from the previously analyzed repository. Removing it ensures a clean analysis for the new repository.

Customizing

• Modify src/terraform_advisor_by_56k/config/agents.yaml to define your agents
• Modify src/terraform_advisor_by_56k/config/tasks.yaml to define your tasks
• Modify src/terraform_advisor_by_56k/crew.py to add your own logic, tools and specific args
• Modify src/terraform_advisor_by_56k/main.py to add custom inputs for your agents and tasks

AWS Well-Architected Documentation

The AWS Well-Architected Framework documentation is already included in this project and available to the agent at knowledge/aws/waf.json. No additional setup is required.

Automated Review Questions

As part of the analysis, the agents will automatically iterate over a set of review questions defined in knowledge/questions.txt. For each question, the agents will analyze the target Terraform repository and AWS documentation to generate detailed, context-aware answers. This ensures a comprehensive evaluation of the infrastructure across multiple best-practice dimensions.

How to Add Your Questions

Create or edit the knowledge/questions.txt file in your project root and add your questions, one per line.

Example:

What security best practices are implemented in this infrastructure?
How well does this setup follow the AWS Well-Architected Framework?
Are there any potential cost optimization opportunities?
What disaster recovery mechanisms are in place?

Each line in the file will be treated as a separate question that the AI agents will analyze. Empty lines are ignored, so you can use them to organize your questions for better readability.

Understanding Your Crew

The terraform_advisor_by_56k Crew is composed of multiple AI agents, each with unique roles, goals, and tools. These agents collaborate on a series of tasks, defined in config/tasks.yaml, leveraging their collective skills to achieve complex objectives. The config/agents.yaml file outlines the capabilities and configurations of each agent in your crew.

Support

For support, questions, or feedback regarding crewAI, please visit the following resources:

• Visit crewAI documentation
• Join crewAI Discord
• Chat with crewAI docs

Credits

This project was developed by 56k.Cloud.