Metadata-Version: 2.4
Name: dockerclustermon
Version: 0.2.7
Summary: A CLI tool for a live view of your docker containers running on a remote server.
Project-URL: Homepage, https://github.com/mikeckennedy/dockerclustermon
Author-email: Michael Kennedy <michael@talkpython.fm>
License: MIT
License-File: LICENSE
Keywords: Docker,Docker Compose,Monitoring
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.10
Requires-Dist: rich>=13.9.4
Requires-Dist: setproctitle>=1.3.7
Requires-Dist: typer>=0.13.1
Description-Content-Type: text/markdown

# Docker Cluster Monitor

**Stop SSH-ing into servers just to check container status.**

Get a live, color-coded dashboard of all your Docker containers across remote servers-right from your terminal. See CPU, memory, and health at a glance, updated automatically every few seconds.

![Docker Cluster Monitor in action](https://blobs.talkpython.fm/docker-status.gif?cache_id=c4e79e)

## Why Docker Cluster Monitor?

**⚡ Save Time**: No more logging into servers to run `docker stats` or `docker ps`  
**👀 Instant Clarity**: Color-coded metrics show problems at a glance  
**🔄 Stay Informed**: Auto-refreshing dashboard keeps you updated  
**🚀 Zero Configuration**: Just point it at your server and go

## See Everything at a Glance

**Smart color coding** helps you spot issues instantly:
- 🟢 **Green**: Healthy, low resource usage
- 🔵 **Cyan**: Moderate load-everything's fine
- 🔴 **Red**: High CPU or memory usage-time to investigate

Memory percentages reflect your Docker Compose deployment limits, so you know exactly how close each container is to its configured threshold-not just the physical machine limits.

## Quick Start

### Install

**Using uv** (recommended):
```bash
uv tool install dockerclustermon
```

> **Note**: Make sure you have [uv](https://docs.astral.sh/uv/getting-started/installation/) installed first.

### Monitor Your Containers

Run `dockerstatus` (or the shorter `ds` alias) with your server hostname:

```bash
dockerstatus my-docker-host
```

That's it! You now have a live dashboard of your containers, refreshing automatically.

## How to Use

### Basic Usage

Monitor containers on a remote server:
```bash
dockerstatus server.example.com
```

Specify a different SSH user (defaults to `root`):
```bash
dockerstatus server.example.com myuser
```

Use with SSH config entries:
```bash
dockerstatus my-server --ssh-config
```

Run with sudo privileges:
```bash
dockerstatus server.example.com --sudo
```

### Complete Command Reference

![](https://blobs.talkpython.fm/dockerclustermon-help.png?cache_id=029533)


## System Requirements

Docker Cluster Monitor works on any system that supports SSH and has Docker CLI tools installed on the remote server.

**Tested on**: Ubuntu Linux  
**Should work on**: Most Linux distributions and Unix-like systems  
**Current limitation**: Does not work on the local machine (remote servers only)

> **Want local support?** Contributions welcome! PRs accepted.

## About

Docker Cluster Monitor is available on [PyPI](https://pypi.org/project/dockerclustermon/) as `dockerclustermon`. While it's published as a Python package, it's designed as a standalone CLI tool rather than a library to import into your programs.
