📡 Advanced Automated Network & System Monitor

An advanced, offline-first Network and System resource monitoring application built with Streamlit, SQLite, and psutil. It logs historical CPU, RAM, and Disk metrics along with host connection (ping) logs to a local database, and dispatches automated alerts to Discord or Telegram when thresholds are breached or hosts go offline.

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🎨 User Interface Preview

Dark Mode (Giao diện Tối)

The dark theme uses a modern gradient background with glassmorphism cards and bright badges:

Light Mode (Giao diện Sáng)

The light theme uses a clean, high-contrast slate gradient for optimal daylight monitoring:

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🌟 Key Features

• System Metric Logging: Automatically logs CPU, RAM, and Disk usage using Python's psutil library.
• Target Host Pinger: Periodically pings list of target IPs/domains and logs their ONLINE/OFFLINE status.
• Interactive Web Dashboard: Modern Web UI displaying real-time gauges, historical line charts, and device grids.
• Web Form Configuration Editor: Add/remove targets and change alert thresholds directly from the browser.
• Multi-Channel Alerts: Dispatches instant warnings to Discord via Webhooks or Telegram channel bots.
• Simulation Mode: Built-in simulation tool to trigger spike warnings and test Webhook notification relays.

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📘 Detailed End-User Guide & Explanation

To make it easy for non-technical users to understand and operate the system, here is a detailed breakdown of the dashboard metrics and controls:

1. Understanding System Resources

• CPU Usage: Think of this as the "brain" of the computer. It handles all running calculations and tasks.
  • Normal Level: Typically fluctuates between 5% and 60% depending on what programs are open.
  • When to Worry: If it consistently stays above 90% (digits will turn red), the computer may slow down, freeze, or overheat (fans spinning fast).
• RAM Usage: Think of this as the "desk space" in an office. RAM stores temporary data of active applications for quick retrieval by the CPU.
  • Normal Level: Typically stays between 30% and 80%.
  • When to Worry: If it exceeds 90%, the computer runs out of memory, causing software to crash or freeze.
• Disk Usage: Think of this as the "filing cabinet" for long-term storage (operating system files, personal documents, and apps).
  • Normal Level: Depends on how much data you have saved.
  • When to Worry: If it reaches 95% or more, you will not be able to save new files, download updates, or start the system correctly.

2. How the Target Host Pinger Works

• "Ping" is a command that sends a quick "Are you there?" message to a computer or website over the network.
  • 🟢 ONLINE: The target responded successfully. The network connection is stable.
  • 🔴 OFFLINE: The target did not respond. This could mean the device is powered off, disconnected from the network, or configured incorrectly. The system will dispatch an alert instantly.

3. How to Use the Sidebar Controls

The sidebar forms are cleanly tucked inside expanders to keep the view neat:

• Alert Thresholds & Webhooks:
  • Set the danger threshold percentage for CPU, RAM, and Disk.
  • Paste your Discord Webhook URL or Telegram Bot Token/Chat ID to receive automatic alert notifications directly to your phone/PC.
• Add Target Host:
  • If you have a network printer, IP camera, or local server, type its friendly name (e.g., Office Printer) and IP Address (e.g., 192.168.1.50). The system will scan it every 10 seconds.
• Remove Target Host:
  • Select any host from the dropdown list and click the button to stop monitoring it.
• Alert System Simulation:
  • Click the simulation button to trigger a safe, artificial alert (e.g., spiking CPU or offline target) to verify that your Discord or Telegram alerts are coming through correctly without affecting real hardware.

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🏗️ System Architecture

graph TD
    Monitor[Background monitor.py] -->|Log Metrics & Status| DB[(SQLite DB)]
    Monitor -->|Alerts| Webhook[Discord/Telegram]
    WebUI[Streamlit app.py] -->|Read Logs & Status| DB
    WebUI -->|Edit Configurations| Config[config.json]
    Config -->|Reload Automatically| Monitor

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💻 Local Setup & Execution Guide

Step 1: Install Dependencies

Open your terminal in this directory and install requirements:

pip install -r requirements.txt

Step 2: Initialize background logger

Start the background pinger and performance collector:

python monitor.py

(This script will create config.json and initialize the local database monitor_logs.db automatically).

Step 3: Run the Web Dashboard

Launch the interactive web page:

streamlit run app.py

Open your browser at http://localhost:8501 to view your system metrics!

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🧪 Running Unit Tests

To verify database structure, logging, and ping functionalities, run:

python -m unittest tests/test_monitor.py

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📄 License

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