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🔧 Patch Management Automation

License: MIT Python Version Code style: black PRs Welcome Maintenance

Streamline your system patching workflow with intelligent automation

Features • Getting Started • Documentation • Contributing

📋 Overview

Patch Management Automation is a comprehensive solution designed to automate and streamline the process of managing system patches across your infrastructure. It provides intelligent scheduling, compliance tracking, and automated deployment capabilities to keep your systems secure and up-to-date.

🎯 Why Use This?

  • ⚡ Automation First: Reduce manual intervention and human error
  • 🔒 Security Focused: Ensure timely security patch deployment
  • 📊 Comprehensive Reporting: Track patch status and compliance metrics
  • 🔄 Flexible Scheduling: Customize deployment windows for your environment
  • 🛡️ Zero-Downtime Deployment: Minimize impact on production systems

✨ Features

Core Capabilities

  • 🚀 Automated Patch Detection - Continuously monitor for available patches
  • 📅 Intelligent Scheduling - Deploy patches during maintenance windows
  • 📈 Progress Tracking - Real-time monitoring of patch deployment status
  • 📊 Compliance Reports - Generate detailed compliance and audit reports
  • 🔔 Smart Notifications - Alert stakeholders on deployment status
  • 🔍 Pre-deployment Validation - Automated testing before production rollout
  • 🗂️ Multi-System Support - Manage patches across diverse infrastructure
  • 🔐 Role-Based Access Control - Secure access management

🚀 Getting Started

Prerequisites

  • Python 3.8 or higher
  • pip package manager
  • System administrator access
  • Network connectivity to target systems

Installation

  1. Clone the Repository
git clone https://github.com/ng-sudo/Patch-Management-Automation.git
cd Patch-Management-Automation
  1. Create Virtual Environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install Dependencies
pip install -r requirements.txt
  1. Configure Environment
cp .env.example .env
# Edit .env with your configuration

Quick Start

# Initialize the application
python main.py --init

# Start automated patching
python main.py --start

# Check patch status
python main.py --status

📚 Documentation

Configuration

Detailed configuration options are available in docs/CONFIG.md

API Reference

Complete API documentation can be found in docs/API.md

CLI Commands

For command-line interface documentation, see docs/CLI.md

Examples

Explore practical examples in the examples/ directory

🔧 Usage Examples

Schedule Automatic Patching

from patch_automation import PatchScheduler

scheduler = PatchScheduler()
scheduler.add_schedule({
    'systems': ['server1', 'server2'],
    'day': 'Sunday',
    'time': '02:00',
    'timeout': 3600
})
scheduler.start()

Generate Compliance Report

from patch_automation import ReportGenerator

reporter = ReportGenerator()
report = reporter.generate_compliance_report(
    start_date='2025-01-01',
    end_date='2025-12-31'
)
report.save('compliance_report.pdf')

Check Patch Status

from patch_automation import PatchManager

manager = PatchManager()
status = manager.get_system_status('production-server-01')
print(status)

📁 Project Structure

Patch-Management-Automation/
├── src/
│   ├── core/              # Core patching logic
│   ├── schedulers/        # Scheduling modules
│   ├── reporters/         # Report generation
│   └── utils/             # Utility functions
├── tests/                 # Unit and integration tests
├── docs/                  # Documentation
├── examples/              # Usage examples
├── config/                # Configuration templates
├── requirements.txt       # Python dependencies
└── README.md             # This file

🧪 Testing

Run the test suite with:

# Run all tests
pytest

# Run with coverage report
pytest --cov=src

# Run specific test module
pytest tests/test_scheduler.py

🤝 Contributing

We welcome contributions! Please follow these guidelines:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

For detailed contribution guidelines, see CONTRIBUTING.md

Development Setup

# Install development dependencies
pip install -r requirements-dev.txt

# Install pre-commit hooks
pre-commit install

# Run linting
flake8 src/ tests/

# Format code
black src/ tests/

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support & Troubleshooting

Common Issues

Issue: Connection timeout to target systems

  • Solution: Check network connectivity and firewall rules

Issue: Permission denied errors

  • Solution: Ensure your user has sufficient administrator privileges

For more help, please:

🗺️ Roadmap

  • Web-based dashboard UI
  • Kubernetes patch automation
  • Advanced ML-based scheduling
  • Multi-cloud support
  • Enhanced security features
  • Performance optimizations

👥 Authors & Acknowledgments

  • ng-sudo - Project Creator & Maintainer

Special thanks to all our contributors who have helped make this project better!

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