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How google crawls website

:::info Research Cost Breakdown

Total Cost: $0.0020

Token Usage:

  • Input Tokens: 7,157
  • Output Tokens: 4,979
  • Total Tokens: 12,136

Cost by Phase:

  • Brief: $0.0002 (512 tokens)
  • Queries: $0.0001 (611 tokens)
  • Findings: $0.0004 (2,618 tokens)
  • News: $0.0002 (874 tokens)
  • Report: $0.0012 (7,521 tokens)

Model Used: google/gemini-2.5-flash

Generated on: 2025-12-02 18:30:25 :::

How Google Crawls Websites

Google's crawling process is a complex, multi-stage operation designed to discover new and updated web pages for potential inclusion in its search index. This process relies on a distributed infrastructure and a sophisticated set of algorithms and automated programs known as Googlebot.

1. Discovery and URL Generation

Before Google can crawl a page, it must first discover its URL. Google uses several primary mechanisms for URL discovery:

2. Prioritization and Crawl Budget

Google does not crawl every discovered URL immediately or with equal frequency. Instead, it prioritizes crawling based on a concept called "Crawl Budget."

  • Crawl Budget Definition: This refers to the number of URLs Googlebot can and wants to crawl on a website within a given timeframe. It's an aggregate of "crawl demand" (how much Google wants to crawl a site) and "crawl capacity" (how much the site's server can handle).
  • Factors Influencing Crawl Demand:
    • PageRank and Authority: Pages with higher PageRank or perceived authority are generally crawled more frequently.
    • Update Frequency: Pages that are updated often (e.g., news articles, blog posts) are crawled more frequently than static pages.
    • Content Freshness: Google aims to keep its index fresh, so recently updated or new content often receives higher crawl priority.
    • Site-wide Authority/Popularity: Websites with a strong overall reputation and high traffic tend to have a larger crawl budget allocated to them.
    • Number of Internal Links: Pages with many internal links are often deemed more important and crawled more.
    • Crawl Errors: A high number of crawl errors (e.g., 404s, server errors) can signal to Google that a site is poorly maintained, potentially reducing its crawl demand.
  • Factors Influencing Crawl Capacity (Host Load):
    • Server Response Times: Faster server response times allow Googlebot to fetch more pages in a given time, increasing crawl capacity.
    • Server Load and Availability: If Googlebot detects that crawling is negatively impacting a server's performance, it will slow down its crawl rate to avoid overloading the server. Frequent server unavailability can lead to a reduction in crawl budget.
    • robots.txt directiives: Crawl-delay directives in robots.txt can explicitly request Googlebot to slow down.
  • Impact of Crawl Budget: If a website has a large number of pages but a limited crawl budget, some pages (especially less important or deeply nested ones) may be crawled less frequently or even missed, delaying their indexing or updates.

3. Crawling Agent (Googlebot) and Fetching

Once URLs are prioritized, Google dispatches its crawling agents, collectively known as Googlebot, to fetch the content.

  • Googlebot Types: Google uses various types of Googlebots, each with specific user-agent strings and purposes:
    • Googlebot Smartphone: The primary crawler for mobile-first indexing, simulating a mobile device.
    • Googlebot Desktop: Simulates a desktop browser.
    • Googlebot-Image: For crawling images.
    • Googlebot-Video: For crawling videos.
    • AdsBot-Google: For auditing landing pages of Google Ads.
    • Googlebot-News: For crawling news content.
    • Googlebot-Proactive: A less frequent crawler for discovery.
  • HTTP/HTTPS Requests: Googlebot sends standard HTTP or HTTPS requests to the web server for each URL.
  • Content Fetching: Googlebot fetches all accessible resources required to render a page, including:
    • HTML documents
    • CSS stylesheets
    • JavaScript files
    • Images (JPG, PNG, GIF, WebP, etc.)
    • Videos
    • PDFs and other document types
  • Politeness Policy (robots.txt): Before fetching any URL on a domain, Googlebot first checks the robots.txt file located in the site's root directory. This file instructs Googlebot which parts of the website it is allowed or disallowed to crawl. Google strictly adheres to these directives.
    • Disallow: Prevents crawling of specified directories or files.
    • Allow: Can be used to open up specific files within a disallowed directory.
    • Sitemap: Can point to the location of XML sitemaps.
    • Crawl-delay: (Less common for Googlebot, which manages its own crawl rate based on server load).
  • Server Response Codes: Googlebot interprets HTTP status codes:
    • 200 OK: Content is fetched successfully.
    • 3xx Redirects: Googlebot follows redirects (e.g., 301, 302) to the new URL, passing along link equity for 301s. It processes the content at the final destination.
    • 4xx Client Errors: (e.g., 404 Not Found, 403 Forbidden) Indicates a problem on the client side. Googlebot may eventually remove these URLs from its index if they persist.
    • 5xx Server Errors: (e.g., 500 Internal Server Error, 503 Service Unavailable) Indicates a problem on the server side. Googlebot will typically retry these URLs later. Persistent 5xx errors can lead to a reduced crawl rate.

4. Rendering and Processing

After fetching the raw content, Google needs to process and understand it. This is particularly crucial for modern web pages built with JavaScript.

  • Rendering Process: Google uses a modern, evergreen headless Chrome browser to render web pages. This means Googlebot executes JavaScript, fetches resources loaded by JavaScript, and builds the Document Object Model (DOM) of the page, much like a regular user's browser.
    • First Wave (HTML processing): Google initially processes the raw HTML response to extract links and some basic content.
    • Second Wave (Rendering): For pages that rely heavily on JavaScript, Google queues them for rendering. This rendering process can take some time (from a few seconds to several days) and happens in Google's data centers.
  • Resource Fetching for Rendering: During rendering, Googlebot needs to access all CSS, JavaScript, and image files that affect the page's layout and content. If these resources are blocked by robots.txt, Google may not be able to fully understand the page's content or layout, potentially impacting its ability to index and rank the page.
  • Content Extraction: Once rendered, Google extracts all visible and accessible content, including text, images, videos, and structured data. It also identifies all internal and external links on the page.
  • Canonicalization: During this stage, Google identifies the canonical version of a URL. If multiple URLs serve the same content (e.g., example.com/page and example.com/page?sessionid=123), Google tries to pick the best, canonical URL to avoid duplicate content issues in its index. rel="canonical" tags provide a strong hint, but Google may override it if it detects a better canonical.

5. Crawling Infrastructure

Google's crawling operation is distributed globally across numerous data centers.

  • Distributed System: Googlebot is not a single entity but a vast, distributed system of machines constantly requesting and processing web pages.
  • Global Network: Crawlers operate from various IP addresses around the world, though they primarily originate from IP ranges associated with Google.
  • Scalability: The infrastructure is designed to handle the immense scale of the web, efficiently crawling billions of pages daily while respecting website server loads.

6. Interaction with Indexing

It's important to differentiate crawling from indexing.

  • Crawling: The process of discovering and fetching content.
  • Indexing: The process of analyzing the fetched and rendered content, understanding its meaning, categorizing it, and storing it in Google's massive search index for retrieval.
  • Post-Crawl Analysis: After crawling and rendering, the extracted content and links are passed to the indexing pipeline. This pipeline analyzes the text, images, videos, and structured data, determines the page's topic, assesses its quality, and ultimately decides whether and how to include it in the search index. Not all crawled pages are indexed.

Recent News & Updates (May 2024 - May 2025)

The period between May 2024 and May 2025 has seen several notable developments regarding Google's crawling behavior and the broader landscape of web crawlers:

  • Surge in AI Bot Crawling: There has been a significant increase in overall crawler traffic, with AI-driven bots experiencing a substantial surge. Specifically, GPTBot's crawling activity saw a 305% increase, while Googlebot's activity also rose by 96%. This indicates a growing presence and importance of AI-specific crawlers alongside Google's traditional crawling efforts, potentially driven by the need to train large language models.
  • Google Addressing Crawling Issues: Google proactively identified and resolved an issue that began in August 2025, which caused reduced crawling for some websites. This highlights Google's continuous monitoring and maintenance of its crawling infrastructure to ensure efficient web coverage.
  • Independence of Crawling from Core Updates: Google has clarified that its crawling patterns and processes operate independently of its core algorithm updates. This means that changes in how Googlebot discovers and fetches content are not directly tied to major shifts in how content is ranked. Crawling is presented as a foundational step separate from the ranking algorithms.
  • Potential for Increased Crawl Requests Post-Core Updates: Despite the stated independence, some webmasters have observed a significant increase in Google crawl requests following Google Search Core updates. One reported a 5x increase in crawl requests and a corresponding 30% traffic bump. This suggests that while the crawling mechanism itself might be independent, core updates can trigger Google to re-evaluate and re-crawl relevant content more intensively to assess changes or re-confirm quality.

These updates underscore Google's ongoing efforts to refine its crawling mechanisms, adapt to new web technologies (like AI), and maintain optimal performance, even as the web evolves.

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