xFarm – CSV Processing Pipeline with Terraform

📌 Architecture Overview

This project provisions a simple and secure AWS-based pipeline using Terraform. The architecture responds to a common data ingestion use case:

• 📤 A CSV file is uploaded to an S3 Bucket
• ⚡ That triggers an AWS Lambda function
• 🔍 The Lambda processes the file contents (e.g., reads or parses it)

🛠️ Technologies

• Terraform (local backend)
• AWS Lambda (Python 3.12)
• S3 with event triggers
• IAM Roles (least privilege)

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🚀 Deployment Instructions

1. Clone the repo

git clone --branch stable https://github.com/zunderStake/xFarm.git
cd xFarm

2. Package the Lambda function

cd lambda
zip ../lambda_function_payload.zip handler.py
cd ..

3. Initialize and deploy

terraform init
terraform plan
terraform apply

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⚙️Environment Configuration

All variables are defined in terraform.tfvars, like:

• bucket_name = "xfarm-csv-processing-bucket"
• lambda_name = "xfarmCsvProcessor"
• lambda_zip_path = "lambda_function_payload.zip"

🔐 Security Best Practices Applied

• Least privilege IAM role for Lambda
• S3 versioning and server-side encryption (AES-256)
• Modularized Terraform code (clean structure)
• Environment variables supported via Terraform

📦 Project Structure

├── lambda/ → Python function
├── modules/
│ ├── iam/ → IAM role & policies
│ ├── lambda/ → Lambda + permissions
│ └── s3/ → S3 bucket + event trigger
├── main.tf
├── variables.tf
├── outputs.tf
├── terraform.tfvars
└── README.md