docker-monitor-manager 1.0.1

A powerful desktop tool for monitoring and managing Docker containers

DocMan 🐳📊

A powerful desktop tool for monitoring and managing Docker containers, built with Python and Tkinter.

This application provides a native graphical interface for live monitoring and management of your Docker containers, including:

• Real-time resource tracking (CPU & RAM).
• Auto-scaling of services when resource limits are exceeded.
• An integrated terminal for running Docker commands directly.

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Features ✨

• 📈 Live container stats (CPU%, RAM%)
• ⚡ Auto-scale containers when resource limits are exceeded
• ⏯️ Manage containers: Stop, Pause, Unpause, Restart, and Remove containers directly from the UI.
• 🎛️ Global controls: Apply actions to all containers at once.
• 🖥️ Embedded Terminal: A secure terminal for running docker commands.
• 📝 Live Application Logs: See what the monitor is doing in real-time.
• ⚙️ Dynamic Configuration: Adjust CPU/RAM limits and other settings without restarting the app.

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Installation 🚀

Option 1: Install from PyPI (Recommended)

pip install docker-monitor-manager

Option 2: Install from Source

git clone https://github.com/amir-khoshdel-louyeh/docker-monitor.git
cd docker-monitor
pip install .

Prerequisites

• Python 3.8+
• Docker Engine (must be installed and running)

Usage

After installation, you can run Docker Manager from anywhere:

docker-manager

Development Setup

If you want to contribute or modify the source code:

1. Clone the Repository

git clone https://github.com/amir-khoshdel-louyeh/docker-monitor.git
cd docker-monitor

2. Create and Activate a Virtual Environment

On macOS / Linux:

python3 -m venv venv
source venv/bin/activate

On Windows:

python -m venv venv
venv\Scripts\activate

3. Install in Development Mode

pip install -e .

Configuration ⚙️

On Windows:

python -m venv venv
.\venv\Scripts\activate

You can adjust the monitoring behavior in the script:

3. Install Dependencies

Install the required Python packages from requirements.txt.

pip install -r requirements.txt

• CPU Limit: CPU_LIMIT = 70.0
• RAM Limit: RAM_LIMIT = 70.0
• Max Clones: CLONE_NUM = 2
• Check Interval: SLEEP_TIME = 1 (seconds)

4. Run the Application

Launch the Tkinter application.

python3 app_tkinter.py

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API Endpoints 📡

Configuration ⚙️

• / → Web dashboard
• /logs → Returns latest logs in JSON
• /container_stats → Stats for all containers (JSON)
• /control → Control a specific container (pause, unpause, restart, remove)
• /control_all → Apply action to all containers
• /stream → Live event stream (Server-Sent Events)
• /kill_remove → Run kill & remove script
• /test_environment → Run test setup script
  You can adjust the monitoring behavior by clicking the "Config" button within the application. This allows you to dynamically change:

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• CPU Limit (%)
• RAM Limit (%)
• Max Clones
• Check Interval (s)

Example Dashboard Screenshot 🖼️

(Add your screenshot here!)

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Notes 📝

• Requires Docker daemon access (if running without root, make sure your user is added to the docker group).
• Custom scripts used: