CloudOps Automation Toolkit

A comprehensive DevOps toolkit for AWS cloud environments, providing automated system monitoring, log analysis, backup management, and security compliance verification capabilities. Built with Python, this project demonstrates modern DevOps practices and cloud automation skills.

Current Status & Progress

Completed Features

• ✅ System Health Monitoring

  • Created SystemMonitor class with Prometheus integration
  • Real-time CPU, memory, and disk metrics
  • Complete test coverage with integration tests

• ✅ Log Analysis System

  • Implemented log collection and analysis
  • Pattern recognition with custom patterns
  • Alert generation system
  • Log rotation with retention policies

• ✅ S3 Backup Management

  • AWS S3 integration for backups
  • Backup verification system
  • Restoration capabilities
  • Metadata tracking

In Progress

• 🚧 Backup Scheduling System
• 🚧 Security Compliance Features
• 🚧 CI/CD Pipeline Setup
• 🚧 Docker Containerization
• 🚧 Kubernetes Deployment Configuration

Features

• 🔍 System Health Monitoring

  • Real-time CPU, memory, and disk metrics
  • Process monitoring and analysis
  • Prometheus metrics integration

• 📊 Log Analysis

  • Automated log collection and rotation
  • Pattern recognition and alerts
  • Retention management

• 💾 Backup Automation

  • AWS S3 integration
  • Backup verification
  • Restoration testing

• 🔒 Security Compliance

  • Security status monitoring
  • Compliance verification
  • Configuration auditing

Technology Stack

• Python 3.11+
• AWS SDK (boto3)
• Prometheus Client
• Docker
• pytest for testing
• Black for formatting
• pylint for code quality

Installation & Setup

Prerequisites

• Python 3.11 or higher
• Git
• AWS account (for cloud features)

Initial Setup

1. Clone the repository

git clone https://github.com/paulcyi/cloudops-automation-toolkit.git
cd cloudops-automation-toolkit

2. Create and activate virtual environment

python3 -m venv venv
source venv/bin/activate  # On Unix/MacOS
# or
.\venv\Scripts\activate  # On Windows

3. Install required packages

python3 -m pip install pytest psutil
# or for all dependencies:
python3 -m pip install -r requirements.txt

Development

Development Environment

Daily Workflow

1. Activate the virtual environment:

source venv/bin/activate  # On Unix/MacOS
# or
.\venv\Scripts\activate  # On Windows

2. Work on your feature branch:

git checkout -b feature/your-feature-name

3. Run tests:

pytest tests/ -v

4. Before committing:

   • Run all tests
   • Update documentation if needed
   • Follow commit message convention: type(scope): description

5. When finished, deactivate the virtual environment:

deactivate

Development Standards

Git Workflow

• Main branch: Production-ready code
• Develop branch: Integration branch
• Feature branches: Format feature/component-name
• Commits: Use conventional commits format

Example commit:

feat(monitoring): implement system metrics collection

- Add CPU, memory, and disk metrics
- Configure Prometheus integration
- Add unit tests

Testing

• Write tests for all new features
• Maintain >80% test coverage
• Run full test suite before commits

Code Style

• Follow PEP 8 guidelines
• Use type hints
• Document all functions and classes
• Use Black for formatting
• Use pylint for code quality

Code Quality

# Format code
black .

# Check code quality
pylint src/

Project Structure

cloudops-automation-toolkit/
├── src/
│   ├── monitors/
│   │   └── system_monitor.py
│   ├── logs/
│   │   ├── log_analyzer.py
│   │   ├── log_reader.py
│   │   └── log_rotator.py
│   └── backup/
│       └── s3_backup.py
├── tests/
│   ├── monitors/
│   │   └── test_system_monitor.py
│   ├── logs/
│   │   ├── test_log_reader.py
│   │   └── test_log_rotator.py
│   └── backup/
│       └── test_s3_backup.py
├── docs/
├── pytest.ini
├── requirements.txt
└── README.md

Next Steps

1. Implement backup scheduling system
2. Add security compliance features
3. Set up GitHub Actions for CI/CD
4. Add Docker containerization
5. Create Kubernetes deployment manifests

Contributing

[Coming Soon]

License

[Coming Soon]

Author

Paul Yi

• GitHub: @paulcyi
• LinkedIn: Paul Yi

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This project is part of my DevOps learning journey and portfolio development.