🐕 WatchDog

Distributed Uptime Monitoring & Cold-Start Prevention System

A production-grade, containerized microservice architecture for preventing cold starts on free-tier hosting platforms

Features • Architecture • Tech Stack • Quick Start • API

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📋 Table of Contents

• Overview
• Problem Statement
• System Architecture
• Core Features
• Technology Stack
• Installation & Setup
• Configuration
• Usage
• API Reference
• Performance Metrics
• Security
• Future Enhancements

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🎯 Overview

WatchDog is a sophisticated, distributed uptime monitoring system engineered to solve the cold-start problem inherent in free-tier PaaS platforms (Render, Railway, Fly.io). Built on a microservices architecture, it leverages asynchronous task queues, scheduled workers, and real-time UI updates to ensure your services remain warm and responsive 24/7.

Key Highlights

• Distributed Task Processing: Celery workers with Redis message broker
• Intelligent Scheduling: Cron-based task scheduling with configurable intervals
• Real-time Dashboard: HTMX-powered reactive UI with zero JavaScript frameworks
• Containerized Deployment: Multi-container Docker Compose orchestration
• Production Database: PostgreSQL with SQLAlchemy ORM
• HTTP/2 Support: curl-cffi for browser impersonation and TLS fingerprinting
• Graceful Failure Handling: Exponential backoff retry mechanism

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🔍 Problem Statement

Free-tier hosting platforms (Render, Railway, Heroku) spin down inactive services after 15 minutes of inactivity, causing:

• Cold Start Latency: 30-60 second response delays on first request
• Poor UX: Users experience timeouts and failed requests
• Lost Opportunities: Recruiters/clients abandon slow-loading portfolio sites

WatchDog solves this by periodically pinging your services at configurable intervals, keeping them perpetually warm and responsive.

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🏗️ System Architecture

┌─────────────────────────────────────────────────────────────────┐
│                         WatchDog System                         │
└─────────────────────────────────────────────────────────────────┘

┌──────────────┐         ┌──────────────┐         ┌──────────────┐
│              │         │              │         │              │
│   Flask Web  │◄────────┤    Redis     │────────►│Celery Worker │
│   Server     │         │   Message    │         │    Pool      │
│   (Port 5000)│         │   Broker     │         │  (Async)     │
│              │         │  (Port 6379) │         │              │
└──────┬───────┘         └──────────────┘         └──────┬───────┘
       │                                                  │
       │                                                  │
       │                 ┌──────────────┐                │
       │                 │              │                │
       └────────────────►│  PostgreSQL  │◄───────────────┘
                         │   Database   │
                         │   (Neon)     │
                         │              │
                         └──────────────┘
                                ▲
                                │
                         ┌──────┴───────┐
                         │              │
                         │ Celery Beat  │
                         │  Scheduler   │
                         │ (Cron Jobs)  │
                         │              │
                         └──────────────┘

┌─────────────────────────────────────────────────────────────────┐
│                      Request Flow Diagram                       │
└─────────────────────────────────────────────────────────────────┘

User Browser ──► Flask (HTMX) ──► PostgreSQL (Read/Write)
                    │
                    └──► Redis ──► Celery Worker ──► HTTP Request
                                        │                  │
                                        │                  ▼
                                        │            Target Service
                                        │                  │
                                        └──────────────────┘
                                           (Update Status)

Component Breakdown

Component	Technology	Purpose
Web Server	Flask + Gunicorn	REST API & UI rendering
Message Broker	Redis	Task queue & pub/sub
Task Workers	Celery	Async HTTP request execution
Scheduler	Celery Beat	Cron-based task scheduling
Database	PostgreSQL (Neon)	Persistent storage
Frontend	HTMX + TailwindCSS	Reactive SPA-like experience
Containerization	Docker Compose	Multi-service orchestration

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✨ Features

🎨 Frontend

• Zero-JavaScript Framework: Pure HTMX for reactive updates
• Real-time Polling: Auto-refresh every 5 seconds without page reload
• Responsive Design: Mobile-first TailwindCSS styling
• Smooth Animations: CSS keyframe animations with staggered delays
• Dark Theme: Custom dot-grid background with glassmorphism effects
• HTTP Basic Auth: Password-protected admin dashboard

⚙️ Backend

• Asynchronous Task Queue: Celery with Redis broker
• Intelligent Scheduling: Per-target configurable ping intervals
• Retry Logic: Exponential backoff (3 retries, 15s delay)
• Browser Impersonation: curl-cffi for bypassing bot detection
• ORM Layer: SQLAlchemy for database abstraction
• Environment Variables: python-dotenv for configuration management

🐳 DevOps

• Multi-Stage Dockerfile: Optimized Python 3.13 image
• Docker Compose: 4-service orchestration (web, worker, beat, redis)
• Health Checks: Container dependency management
• Volume Persistence: Redis data persistence
• Network Isolation: Internal Docker network

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🛠️ Tech Stack

Backend Framework

Flask 3.0          # Lightweight WSGI web framework
Flask-SQLAlchemy   # ORM integration
python-dotenv      # Environment variable management

Task Queue & Scheduling

Celery 5.3         # Distributed task queue
Redis 7.0          # Message broker & result backend
celery-beat        # Periodic task scheduler

Database

PostgreSQL 16      # Production-grade RDBMS
psycopg2-binary    # PostgreSQL adapter
Neon Database      # Serverless Postgres hosting

HTTP Client

curl-cffi          # HTTP/2 client with browser impersonation
requests           # Fallback HTTP library

Frontend

HTMX 1.9           # Hypermedia-driven interactions
TailwindCSS 3.0    # Utility-first CSS framework
Idiomorph          # DOM morphing for smooth updates

DevOps

Docker 24.0        # Containerization
Docker Compose 3.8 # Multi-container orchestration

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🚀 Installation & Setup

Prerequisites

• Docker & Docker Compose installed
• Python 3.13+ (for local development)
• PostgreSQL database (or use Neon free tier)
• Redis server (or use Docker)

Option 1: Docker Compose (Recommended)

# Clone the repository
git clone https://github.com/indiser/WatchDog.git
cd WatchDog

# Create environment file
cat > .env << EOF
DATABASE_URL=postgresql://user:pass@host:5432/dbname
ADMIN_USER=admin
ADMIN_PASS=your_secure_password
CELERY_BROKER_URL=redis://redis:6379/0
EOF

# Build and start all services
docker-compose up --build -d

# View logs
docker-compose logs -f

# Access dashboard
open http://localhost:5000

Option 2: Local Development

# Create virtual environment
python -m venv env
source env/bin/activate  # Windows: env\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Set environment variables
export DATABASE_URL="postgresql://..."
export ADMIN_USER="admin"
export ADMIN_PASS="password"
export CELERY_BROKER_URL="redis://localhost:6379/0"

# Terminal 1: Start Flask
python app.py

# Terminal 2: Start Celery Worker
celery -A tasks.celery worker --pool=solo --loglevel=info

# Terminal 3: Start Celery Beat
celery -A tasks.celery beat --loglevel=info

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⚙️ Configuration

Environment Variables

Variable	Description	Default
DATABASE_URL	PostgreSQL connection string	sqlite:///local_test.db
CELERY_BROKER_URL	Redis connection URL	redis://localhost:6379/0
ADMIN_USER	Dashboard username	admin
ADMIN_PASS	Dashboard password	super_secret_default

Docker Compose Services

services:
  redis:      # Message broker (port 6379)
  web:        # Flask application (port 5000)
  worker:     # Celery task executor
  beat:       # Celery scheduler

Database Schema

class TargetURL(db.Model):
    id                 # Primary key
    url                # Target URL to monitor
    interval_minutes   # Ping frequency (default: 5)
    is_active          # Enable/disable monitoring
    last_pinged_at     # Last successful ping timestamp

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📖 Usage

Adding a Target

1. Navigate to http://localhost:5000
2. Enter credentials (ADMIN_USER / ADMIN_PASS)
3. Input target URL and interval (minutes)
4. Click "Monitor"

Dashboard Features

• Real-time Stats: Total/Active/Paused targets
• Target Management: Toggle active status, delete targets
• Live Updates: Auto-refresh every 5 seconds
• Mobile Responsive: Card layout on small screens

Monitoring Behavior

# Celery Beat runs every minute
@celery.task
def queue_due_pings():
    # Check each active target
    # If (now - last_ping) >= interval:
    #     Queue ping_url.delay(url)
    #     Update last_pinged_at

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🔌 API Reference

Authentication

All endpoints require HTTP Basic Auth.

Endpoints

GET /

Returns the main dashboard HTML.

POST /add_target_ui

Add a new monitoring target.

Form Data:

url: string (required)
interval_minutes: integer (default: 5)

GET /targets_partial

Returns HTMX-compatible table body HTML.

DELETE /delete_target/<id>

Removes a target from monitoring.

PATCH /toggle_target/<id>

Toggles target active/paused status.

GET /stats

Returns real-time statistics HTML fragment.

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📊 Performance Metrics

Scalability

• Concurrent Workers: Configurable Celery pool size
• Request Throughput: 100+ pings/minute per worker
• Database Connections: SQLAlchemy connection pooling
• Memory Footprint: ~150MB per container

Reliability

• Retry Mechanism: 3 attempts with 15s exponential backoff
• Timeout Handling: 10s HTTP timeout per request
• Graceful Degradation: Failed pings don't block queue

Monitoring

# Check Celery worker status
celery -A tasks.celery inspect active

# View Redis queue length
redis-cli LLEN celery

# Monitor container health
docker-compose ps

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🔒 Security

Implemented Measures

• ✅ HTTP Basic Authentication: Password-protected dashboard
• ✅ Environment Variables: Secrets stored in .env (gitignored)
• ✅ SQL Injection Prevention: SQLAlchemy ORM parameterization
• ✅ CSRF Protection: Form-based actions only
• ✅ Docker Network Isolation: Internal service communication

Recommendations

• Use strong passwords for ADMIN_PASS
• Enable HTTPS with reverse proxy (Nginx/Caddy)
• Rotate database credentials regularly
• Implement rate limiting for production
• Use secrets management (AWS Secrets Manager, Vault)

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🚧 Future Enhancements

Planned Features

• Webhook Notifications: Slack/Discord alerts on downtime
• Prometheus Metrics: Grafana dashboard integration
• Multi-User Support: Role-based access control
• Response Time Tracking: Historical latency graphs
• Status Page: Public uptime dashboard
• API Key Authentication: RESTful API access
• Kubernetes Deployment: Helm charts for K8s
• Email Alerts: SMTP integration for notifications

Technical Debt

• Implement comprehensive unit tests (pytest)
• Add CI/CD pipeline (GitHub Actions)
• Database migration system (Alembic)
• API rate limiting (Flask-Limiter)
• Logging aggregation (ELK stack)

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📁 Project Structure

WatchDog/
├── app.py                 # Flask application & routes
├── tasks.py               # Celery tasks & scheduling
├── requirements.txt       # Python dependencies
├── dockerfile             # Container image definition
├── docker-compose.yml     # Multi-service orchestration
├── .env                   # Environment variables (gitignored)
├── static/
│   └── style.css         # Custom CSS animations
├── templates/
│   ├── index.html        # Main dashboard
│   ├── _stats_bar.html   # Stats component
│   ├── _target_row.html  # Table row partial
│   └── ...               # Other HTMX partials
└── README.md             # This file

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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/AmazingFeature)
3. Commit changes (git commit -m 'Add AmazingFeature')
4. Push to branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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📄 License

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

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👨‍💻 Author

Indiser

• GitHub: indiser
• Email: indiser01@gmail.com

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🙏 Acknowledgments

• Flask team for the excellent web framework
• Celery project for distributed task processing
• HTMX for revolutionizing frontend interactivity
• TailwindCSS for rapid UI development
• Neon for serverless PostgreSQL hosting

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⭐ Star this repository if you find it useful!

Built with ❤️ using Flask, Celery, Redis, and Docker