System Monitor

A lightweight, Python-based system monitoring tool built to track server health in real-time. The System Monitor continuously checks CPU, RAM, and Disk usage, logging performance data and automatically dispatching email alerts when critical thresholds are exceeded.

Designed for simplicity, reliability, and automated oversight (SysAdmin automation, remote server monitoring, resource tracking).

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Table of Contents

• Key Features
• Project Architecture
• Installation
• Environment Setup
• Usage
• Configuration
• Logs & Outputs
• Contributing
• License

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Key Features

• Real-Time Resource Tracking: Utilizes psutil to monitor CPU load, RAM usage, and Disk partition storage every few seconds.
• Automated Alerting System: Instantly detects when resources breach safety limits and sends email notifications via SMTP (Gmail).
• Persistent Logging: Maintains a historical record of system performance in system.log for audit and analysis purposes.
• Configurable Thresholds: Easily adjustable sensitivity settings for CPU, RAM, and Disk usage via a central configuration file.
• Multi-Partition Support: Dynamically discovers and monitors usage across all mounted disk partitions (e.g., C:\, D:\).

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Project Architecture

Based on the modular structure, the project is organized as follows:

System_Monitor/
│
├── main.py                  # Application entry point & main loop
├── config.py                # User-defined thresholds & intervals
├── system.log               # Output log file (auto-generated)
├── README.md
│
└── monitor/                 # Core monitoring logic
    ├── __init__.py
    ├── cpu.py               # CPU usage extraction
    ├── memory.py            # RAM usage extraction
    ├── disk.py              # Disk partition scanning
    ├── alerts.py            # Threshold logic & message generation
    ├── email_alert.py       # SMTP email dispatcher
    └── logger.py            # Logging configuration

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Installation

1. Clone the repository:

   git clone [https://github.com/YourUsername/System_Monitor](https://github.com/YourUsername/System_Monitor)
   cd System_Monitor

2. Prerequisites: This project requires Python 3.x+ and the psutil library for hardware monitoring.

   pip install psutil

3. Prepare Directories: Ensure the directory structure matches the architecture above so main.py can correctly import modules.

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Environment Setup

To enable email alerts, you must configure environment variables for your email credentials. The application looks for the specific keys defined in email_alert.py:

Linux/Mac:

export Sender_mail@example.com="your_email@gmail.com"
export Recievers_mail@example.com="admin_email@example.com"
export EMAIL_APP_PASSWORD="your_app_password"

Windows (Command Prompt):

set Sender_mail@example.com="your_email@gmail.com"
set Recievers_mail@example.com="admin_email@example.com"
set EMAIL_APP_PASSWORD="your_app_password"

Note: If using Gmail, you must generate an "App Password" in your Google Account security settings.

Usage

1. Run the monitor: Execute the main script to start the monitoring loop.

   python main.py

2. Console Output: The system will print real-time stats and alerts to the console:

   CPU=4.9% | RAM=81.5% | DISKS={'C:\\': 55.7, 'D:\\': 0.3}
   CPU=12.1% | RAM=82.0% | DISKS={'C:\\': 55.7, 'D:\\': 0.3}
   ⚠ CPU usage high: 95.2%
   ⚠ Disk usage high on C:\: 88.0%
   

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Configuration

You can tune the sensitivity of the monitor by modifying config.py.

File: config.py

# Resource Thresholds (Percentage)
CPU_THRESHOLD = 80
DISK_THRESHOLD = 75
RAM_THRESHOLD = 85

# Loop Interval
CHECK_INTERVAL = 5   # Seconds between checks

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Logs & Outputs

The tool automatically generates a log file in the root directory.

System Log (system.log)

• Format: Text / Log structure
• Content:
  • Timestamps for every check.
  • Detailed breakdown of CPU, RAM, and individual Disk partition usage.
  • Information on sent alerts.

Example Entry:

2026-01-21 14:09:54,052 - INFO - CPU=4.9% | RAM=81.5% | DISKS={'C:\\': 55.7, 'D:\\': 0.3}
2026-01-21 14:10:06,059 - INFO - CPU=7.2% | RAM=81.3% | DISKS={'C:\\': 55.7, 'D:\\': 0.3}

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Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/NewMonitor
3. Commit your changes
4. Open a Pull Request

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Roadmap & Future Improvements

Here are some features planned for future releases to make the System Monitor more robust and user-friendly:

• Web Dashboard: Implement a lightweight web interface (using Flask or Streamlit) to visualize CPU and Memory trends with real-time graphs.
• Multi-Channel Alerts: Expand alerting beyond Email to include integrations for Slack, Discord, or SMS (via Twilio).
• Database Integration: Transition from text-based logging (system.log) to a local database (SQLite) to enable historical data queries and long-term analysis.
• Background Service: Create a setup script to run the monitor as a systemd service (Linux) or Windows Service, ensuring it runs automatically on boot.
• Daily Health Reports: specific module to generate and email a daily summary PDF of system performance statistics.

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License

Distributed under the MIT License.

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