🪣 S3 Lifecycle Buddy

Automate Amazon S3 lifecycle policies using Python and AWS CLI — from bucket creation to cleanup.

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📌 Project Overview

S3 Lifecycle Buddy is a fully automated Python tool that manages the entire lifecycle of an S3 bucket using code — no Console clicks required.

This project handles:

• ✅ Region-aware S3 bucket creation
• ✅ Lifecycle policy application via inline JSON
• ✅ Upload of a test object
• ✅ Optional cleanup that deletes both the object and the bucket

It’s a real-world cloud automation use case for cost optimization, policy enforcement, and DevOps-style AWS control.

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🎯 Why This Project Matters

AWS storage can quietly rack up costs without proper management. This script demonstrates how to:

• Enforce data retention using lifecycle rules
• Reduce cloud waste from forgotten dev/test buckets
• Automate cleanup workflows to avoid manual intervention

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🛠️ Technologies Used

• Python 3
• AWS CLI – for command-line resource management
• boto3 – AWS SDK for Python
• subprocess – to bridge Python with CLI commands

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📁 Project Structure

s3-lifecycle-buddy/
├── s3_lifecycle.py       # Main Python script
├── README.md              # Project documentation
├── test_upload.txt        # Auto-generated test file
├── .gitignore             # Git cleanup rules
└── venv/       

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🚀 How It Works

1. Bucket Creation
   Creates an S3 bucket using AWS CLI logic that adjusts automatically for us-east-1 region behavior.

2. Lifecycle Policy
   Applies a lifecycle policy via inline JSON to automatically delete objects after 1 day.

3. Test Upload
   Generates and uploads a sample file to validate the lifecycle configuration.

4. Cleanup (Optional)
   Deletes all objects and the bucket using:

   aws s3 rb s3://bucket-name --force

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▶️ How to Run

🧱 Prerequisites

• Python 3 installed
• AWS CLI installed and configured (run: aws configure)
• Virtual environment (optional but recommended)
• Boto3 installed in your environment

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📦 Setup Steps

# 1. Create a virtual environment (optional but recommended)
python -m venv venv

# 2. Activate the virtual environment
# On Windows:
venv\Scripts\activate

# On macOS/Linux:
source venv/bin/activate

# 3. Install boto3 if not already installed
pip install boto3

# 4. Run the script
python s3_lifecycle.py

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📎 License MIT License — Free to use, modify, and distribute.