Rate limiting controls how many requests you can send to a website or API within a specific time window. Think of it as a traffic cop for web servers. If you send 100 requests per minute but the site only allows 10, the server will start rejecting your extra requests.
What rate limiting does
When you scrape a website, every page request hits their server. Rate limiting tracks these requests by identifier, usually your IP address, API key, or session. Once you exceed the allowed threshold, the server pushes back.
Most rate limits work on simple rules like "50 requests per minute per IP" or "1,000 API calls per hour per account." The numbers vary wildly depending on the website and their infrastructure capacity.
Why websites use rate limiting
Websites implement rate limits for three main reasons:
- Server stability: Too many requests from one source can slow down or crash servers, affecting all users
- Fair resource distribution: Prevents any single scraper from hogging bandwidth that regular visitors need
- Security protection: Blocks aggressive bots, credential stuffing attacks, and DDoS-like behavior
What happens when you hit a rate limit
The most common response is HTTP 429 "Too Many Requests." This status code tells you to slow down and wait before trying again. Some servers include helpful headers like Retry-After that specify exactly how long to pause.
If you ignore the warning and keep hammering the server, expect escalation. The site might upgrade from temporary 429 responses to permanent HTTP 403 "Forbidden" errors or outright IP bans.
Handling rate limits when scraping
Smart scrapers work within rate limits rather than trying to bypass them. Here are practical strategies:
- Add delays between requests: A 2 to 5 second pause between pages keeps you well under most thresholds
- Randomize your timing: Perfectly regular intervals look robotic. Add random variation to mimic human browsing patterns
- Respect Retry-After headers: When you get a 429, wait at least as long as the server suggests
- Use exponential backoff: If you hit repeated rate limits, double your wait time each time before retrying
- Rotate IP addresses carefully: For large projects, spreading requests across multiple IPs keeps each one under per-IP limits
Best practices for staying under the radar
Start conservative. Begin with a very low request rate and only increase it while monitoring for errors. Track response times and status codes so you notice when a site starts struggling.
Check the site's robots.txt file and API documentation. Many services clearly state their rate limits and expected behavior. Following these rules keeps your scraper running smoothly and reduces your ban risk.
Avoid scraping during peak traffic hours when servers are already under load. Early morning or late night requests are less likely to trigger aggressive rate limiting.
How Browse AI handles rate limiting
Building rate limit logic into custom scrapers takes time and constant tweaking. Browse AI handles this automatically. The platform manages request timing, respects server limits, and adjusts scraping speeds to avoid triggering blocks. You get the data you need without writing retry logic or managing IP rotation yourself.
