How I Run 77 Web Scrapers on a Schedule Without Breaking the Bank

In 2024, I was running 12 scrapers on my laptop. A cron job that silently died at 3 AM. Data gaps I only noticed when a client asked why their dashboard was empty. By 2026, I manage 77 web scrapers. They run on schedule, retry on failure, alert me when something breaks, and cost me less than $15/month total. Here is the exact setup. The Problem Nobody Talks About Building a scraper is the easy part. Running it reliably is the hard part. Most tutorials end at python scraper.py . They never cover: What happens when the target site changes its HTML? How do you retry failed runs without duplicate data? How do you monitor 77 scrapers without going insane? Architecture: 3 Layers Layer 1: Scrapers (Python scripts, each <200 lines) Layer 2: Orchestration (GitHub Actions / cron on VPS) Layer 3: Monitoring (dead simple: webhook → Telegram) Layer 1: Keep Scrapers Stupid Simple Each scraper does ONE thing: Fetch data from ONE source Parse it into JSON Save to ONE output file # scraper_hackernews.p