🇺🇸 English | 🇷🇺 Russian Version

🚀 Monitron

Personal Monitoring Stack for developers and DevOps engineers.

Monitron is a ready-to-use monitoring stack that helps you collect, analyze, and visualize metrics from your applications and infrastructure.
Perfect for pet projects, home labs, and DevOps practice environments.

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✨ Features

• 📊 Metrics collection — Prometheus for time-series data storage
• 📈 Visualization — Grafana dashboards ready to use
• 🚨 Alerting — Alertmanager with Telegram integration
• 🖥 System monitoring — Node Exporter for host metrics
• 🌐 Web monitoring — Nginx + Exporter for web server stats
• 🔄 CI/CD — automatic configuration validation and build tests

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🛠 Stack Components

Component	Version	Description
Prometheus	2.48	Metrics collection & storage
Grafana	10.2	Visualization & dashboards
Alertmanager	—	Alert routing & notifications
Node Exporter	—	Host-level metrics
Docker Compose	2.15	Container orchestration
GitHub Actions	—	CI/CD automation

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🚀 Quick Start

# 1. Clone the repository
git clone https://github.com/DanLinX2004X/monitron.git
cd monitron

# 2. Create an .env file from the template
cp .env.example .env

# 3. Launch the monitoring stack
docker compose up -d --build

# 4. Check running services
docker compose ps

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🔗 Service Access

Service URL Login

Grafana http://localhost:3000 admin / admin

Prometheus http://localhost:9090

Alertmanager http://localhost:9093

Nginx http://localhost:8080

P.S. Login and password are required to log in to Grafana. When you open it for the first time, it will be admin/ admin (login and password match), after that Grafana will ask you to change the password.

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📦 Stop Services

docker compose down

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⚙️ Alertmanager & Telegram Integration

The .env.example file contains variables for Telegram notification setup:

TELEGRAM_BOT_TOKEN=123456789:ABCDEF123456789
TELEGRAM_CHAT_ID=123456789

Once filled in, Alertmanager will automatically send alerts to your Telegram chat.

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📊 Grafana Dashboards

System Overview — CPU, memory, disk, network

Nginx Analytics — requests, connections, errors

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🏗 Project Structure

monitron/
├── 📁 prometheus/
│   ├── config/
│   │   ├── prometheus.yml       # Main configuration
│   │   └── alert.rules.yml      # Alert rules
│   └── data/                    # Time series data
├── 📁 grafana/
│   └── provisioning/            # Auto setup files
├── 📁 nginx/
│   ├── html/
│   │   └── index.html           # Demo page
│   └── nginx.conf               # Web server config
├── 📁 screenshots/              # Screenshots for documentation
│   ├── system_dashboard.png
│   └── nginx_monitoring.png
├── 🐳 docker-compose.yml        # Main Docker Compose file
├── 📜 .env.example              # Environment variables
├── 📘 README.md                 # Documentation (RU)
└── 📘 README.en.md              # Documentation (EN)

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🔄 CI/CD Pipeline

Automated workflow using GitHub Actions:

✅ Docker Compose syntax validation

✅ Prometheus config validation (promtool check config)

✅ Health check of running containers

✅ Build and deploy verification

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⚠️ Local Testing with act

You can run the pipeline locally using:

act -j validate

⚠️ Note: act has known limitations (network isolation, health-checks, volume mapping). For reliable testing — use real GitHub Actions runners.

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📸 Screenshots

System Dashboard

Nginx Monitoring

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🤝 Contributing

1. Fork the repository

2. Create a feature branch: git checkout -b feature/amazing-feature

3. Commit changes: git commit -m 'Add amazing feature'

4. Push the branch: git push origin feature/amazing-feature

5. Open a Pull Request

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📄 License

Distributed under the MIT License.

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👤 Author

DanLinX2004X