☁️ Python AWS Automation Toolkit

Production-grade AWS automation scripts built with Python, boto3, and argparse — designed for real-world cloud operations, FinOps, and infrastructure management.

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📋 Overview

A collection of three CLI-driven AWS automation tools that handle everyday cloud operations:

Script	Purpose	Key Feature
EC2 Manager	Instance lifecycle management	Tag-based filtering for start/stop
S3 Cleanup	Storage cost optimization	Dry-run safety with age-based deletion
Cost Report	FinOps cost visibility	30-day spend breakdown by service

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🚀 Features

1. EC2 Manager (ec2_manager.py)

• List all EC2 instances with ID, state, type, and tags
• Start/Stop instances filtered by tag key-value pairs
• Clean CLI interface with argument validation

# List all instances
python scripts/ec2_manager.py --list

# Stop instances tagged Environment=dev
python scripts/ec2_manager.py --stop --tag-key Environment --tag-value dev

# Start instances tagged Environment=dev
python scripts/ec2_manager.py --start --tag-key Environment --tag-value dev

2. S3 Cleanup (s3_cleanup.py)

• List all S3 buckets with total size in MB
• Identify objects older than a configurable number of days
• Dry-run by default — safe exploration before any deletion
• --execute flag required for actual deletion (safety-first design)

# List all buckets and sizes
python scripts/s3_cleanup.py --list

# Preview old objects (dry run)
python scripts/s3_cleanup.py --bucket my-bucket --days 90

# Actually delete objects older than 90 days
python scripts/s3_cleanup.py --bucket my-bucket --days 90 --execute

3. AWS Cost Report (cost_report.py)

• Pulls the last 30 days of AWS spend via the Cost Explorer API
• Groups costs by service for clear visibility
• Outputs a clean, formatted table using tabulate

python scripts/cost_report.py

Sample Output:

Service              Cost (30 days)
-------------------  ----------------
Amazon EC2           $142.53
Amazon S3            $23.17
AWS Lambda           $8.42
Amazon RDS           $67.89

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📦 Requirements

• Python 3.8+
• AWS Credentials configured via aws configure or environment variables
• IAM Permissions for the services you intend to manage

Install Dependencies

pip install -r requirements.txt

IAM Permissions

Script	Required IAM Actions
EC2 Manager	ec2:DescribeInstances, ec2:StartInstances, ec2:StopInstances
S3 Cleanup	s3:ListBucket, s3:ListObjectsV2, s3:DeleteObject, s3:ListAllMyBuckets
Cost Report	ce:GetCostAndUsage

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🏗️ Project Structure

python-aws-automation/
├── README.md
├── requirements.txt
└── scripts/
    ├── cost_report.py      # FinOps cost reporting
    ├── ec2_manager.py      # EC2 lifecycle management
    └── s3_cleanup.py       # S3 storage optimization

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🛡️ Safety Features

• Dry-run default on destructive operations (S3 cleanup)
• Tag-based filtering prevents accidental instance management
• Explicit confirmation required via --execute flag
• No hardcoded credentials — uses AWS SDK default credential chain

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📸 Screenshots

To be updated

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🔮 Future Enhancements

• Add Lambda support for serverless function management
• Implement CloudWatch log cleanup for older log groups
• Add RDS instance start/stop scheduling
• Support multi-account via AWS Organizations / STS assume-role
• Add JSON/YAML output format options for CI/CD integration
• Include unit tests with moto for AWS mocking
• Add pre-commit hooks and linting (flake8, black, mypy)
• Package as a CLI tool with setup.py / pyproject.toml
• Add Slack/Teams notifications for cost alerts and cleanup summaries
• Support Terraform state integration for drift detection

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📝 License

MIT License — see LICENSE for details.

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🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to open a PR or issue.

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Built with ☕ and ☁️ by Deepak