Web Scraping at Scale: Architecture and Best Practices

Web scraping becomes exponentially more complex as you scale from hundreds to hundreds of thousands of pages. Here's how I built a system that handles 500K+ pages daily.

Architecture Overview

Our scraping infrastructure consists of:

• Queue System: BullMQ with Redis
• Worker Nodes: Puppeteer clusters
• Proxy Rotation: Smart proxy management
• Data Pipeline: Real-time processing and storage

Core Components

1. Queue Management

Use BullMQ with priority, delay, and exponential backoff retry strategies.

2. Puppeteer Cluster

Run multiple browser contexts with concurrency control.

3. Anti-Detection Strategies

Stealth mode, random delays, and user agent rotation.

Scaling Strategies

Deploy multiple worker instances with Docker and monitor memory usage for graceful restarts.

Results

• Throughput: 500K+ pages/day
• Success Rate: 98.5%
• Uptime: 99.9%
• Average Processing Time: 2.3 seconds per page