Lessons from running a web scraper processing millions of pages daily

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A developer who built a large-scale scraping platform processing millions of pages daily at 95% extraction success shared the key failure points encountered along the way. Unbounded queues caused memory overflows in the message broker, while fixed retry backoffs accidentally triggered DDoS-like traffic spikes on struggling target sites. URL deduplication at enqueue time, rather than after fetching, proved critical to cutting costs and reducing block risk from duplicate content. Silent data degradation — where extraction appeared successful but key fields quietly returned null — was caught only by tracking field-level fill rates and alerting on deviations from baseline. Using multiple extraction strategies in parallel, such as embedded JSON, microdata, and DOM selectors, helped maintain high success rates when site redesigns broke individual methods.

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