Originally published on proxymint.
Web scraping architecture splits a scraper into scheduler, fetcher, parser, storage and monitoring layers. How it changes with scale, and where proxies belong.
TL;DR
- Five components, five failure modes. A scraping system splits into a scheduler and queue, a fetcher with its proxy layer, a parser with validation, storage, and monitoring. Each one gets its own metrics and retry rule.
- Rate limits live in the scheduler. A concurrency budget per target domain, enforced centrally, keeps every worker inside it. Adding exit IPs never raises that budget.
- The proxy layer is an interface, not a loop. Workers ask for an egress by job type and country; rotation is chosen per job shape and DNS resolves at the proxy with CONNECT or socks5h.
- Some errors mean stop. A 429 means wait as long as Retry-After says; a 403 or challenge page means the job for that target stops and a person reviews access.
Key takeaways
- Check for an official API or data export first. Scraping is the fallback for public pages where no such route exists.
- Store raw responses before parsing. A broken selector then costs a replay over stored pages, with no new requests to the target.
- Enforce robots.txt and per-domain budgets before the queue. Cache robots.txt for at most 24 hours, as RFC 9309 says, and share one limiter across all workers.
- Give each job shape its own egress profile. A new IP per request for independent pages, a timed session for paginated flows, a static address for long logins on accounts the team owns.
- Alert on change per layer. Parse yield, 429 share per domain and data freshness catch problems the day they start.
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