A comprehensive health monitoring system for robotic applications that tracks system resources, sensor status, and provides automated maintenance capabilities.

• CPU Monitoring: Tracks CPU usage with configurable thresholds and alerts
• Memory Monitoring: Monitors RAM usage and detects memory pressure
• Disk Monitoring: Monitors disk space and I/O operations
• Network Monitoring: Tracks network interface statistics and connectivity

• Camera Simulator: Simulates camera sensor operations and health checks
• GPS Simulator: Simulates GPS positioning and signal quality monitoring

• Log Cleanup: Automated log rotation and cleanup utilities
• Service Restart: Automated service restart capabilities for fault recovery

• Centralized logging configuration with rotating file handlers
• Structured logging with different log levels and categories
• Configurable monitoring thresholds and intervals

health-monitor/
├── main.py                 # Main application entry point
├── logger_config.py        # Logging configuration
├── requirements.txt        # Python dependencies
├── Dockerfile             # Docker container configuration
├── docker-compose.yml     # Docker Compose deployment
├── monitor/               # System monitoring modules
│   ├── cpu_monitor.py
│   ├── memory_monitor.py
│   ├── disk_monitor.py
│   └── network_monitor.py
├── sensors/               # Sensor simulation modules
│   ├── camera_simulator.py
│   └── gps_simulator.py
├── auto_fix/              # Automated maintenance scripts
│   ├── cleanup_log.py
│   ├── cleanup_logs
│   └── restart_service.py
└── logs/                  # Application logs directory

• Python 3.8 or higher
• Docker and Docker Compose (for containerized deployment)

1. Clone the repository:

git clone https://github.com/DipendraChandel/Application-Health-Monitoring.git
cd Application-Health-Monitoring

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

Start the health monitoring system:

python main.py

The application will start monitoring system resources and log to the logs/ directory.

1. Build the Docker image:

docker-compose build

2. Start the service:

docker-compose up -d

3. View logs:

docker-compose logs -f

4. Stop the service:

docker-compose down

Modify the threshold values in the respective monitor files:

• CPU_THRESHOLD in monitor/cpu_monitor.py
• MEMORY_THRESHOLD in monitor/memory_monitor.py
• DISK_THRESHOLD in monitor/disk_monitor.py

Adjust logging settings in logger_config.py:

• Log levels
• File rotation policies
• Log format

Run the log cleanup script:

python auto_fix/cleanup_log.py

Execute the service restart utility:

python auto_fix/restart_service.py

1. Create a new monitor file in the monitor/ directory
2. Implement the monitoring function following the pattern:

def monitor_[resource](stop_event):
    while not stop_event.is_set():
        # Monitoring logic
        # Logging
        time.sleep(interval)

3. Import and add the monitor thread in main.py

1. Create sensor simulator in the sensors/ directory
2. Implement sensor health checks and data simulation
3. Integrate with the main monitoring loop if needed

• psutil==7.1.3: System and process utilities for monitoring

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

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

For issues and questions, please open an issue on the GitHub repository.