Last Updated: December 31, 2025
A web crawler, also known as a spider or bot, is a system that automatically browses the internet to discover and collect web pages. The collected data is typically stored and indexed for use in applications such as search engines, analytics, or archiving.
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For example, Google Search relies heavily on web crawlers to continuously fetch and update its index of billions of pages.
In recent years, they’ve also become essential for training large language models (LLMs) by collecting massive amounts of publicly available text data from across the internet.
Web crawlers serve many purposes beyond search engines. They power price comparison sites, archive the web for historical preservation, gather data for machine learning datasets, monitor brand mentions, and detect copyright violations.
The core challenges remain the same regardless of the use case: discover URLs efficiently, download content politely, handle failures gracefully, and manage the sheer volume of data.
In this article, we’ll walk through the end-to-end design of a scalable, distributed web crawler.
Let’s begin by clarifying the requirements.