Distributed web crawling is a technique that utilizes multiple machines to crawl websites in parallel, addressing scalability and speed limitations faced by single-node crawlers. While single-node crawlers are simpler and cost-effective for smaller tasks, distributed systems offer higher throughput, reliability, and fault tolerance by eliminating single points of failure and allowing horizontal scaling across nodes. However, distributed crawling introduces increased architectural complexity, requiring components like schedulers, worker nodes, and storage layers, while also demanding expertise in distributed systems. Real-world use cases such as e-commerce price monitoring and SEO market research benefit from distributed architectures by enabling faster data collection and improved anti-detection strategies, despite challenges like managing proxies and avoiding anti-bot systems. While distributed crawling provides significant advantages, teams often underestimate the complexity involved, leading to potential pitfalls such as single points of failure, retry spirals, and memory leaks. Solutions like Bright Data's Web Unlocker API can alleviate these burdens by providing managed anti-detection capabilities, allowing teams to focus on extracting valuable insights without the overhead of infrastructure maintenance.