Smart Rate Limiting

When a new target is first scraped, our system enters a profiling phase. It sends a small number of probe requests at conservative intervals, analyzes response times, HTTP headers, and content signatures, and uses this to infer the site's infrastructure and tolerance thresholds. This profile is typically established within the first 50-100 requests and is then used to calculate safe operating rates for all subsequent scraping.

Jitter refers to random time variation added between requests. Without jitter, even human-like average delays create mathematically regular request intervals that are trivially detectable by statistical analysis. Our jitter engine draws delays from probability distributions (log-normal, Weibull) that match real human browsing behavior, making request timing indistinguishable from an actual user navigating the site.

Yes. You can configure per-site rate policies including target requests-per-minute, maximum concurrency, minimum delay floors, time-of-day schedules, and geographic distribution preferences. These policies coexist with the adaptive engine — the AI will always stay at or below your configured maximums while dynamically adjusting within that ceiling.

Block detection latency is under 50 milliseconds from the moment a suspicious response is received. When triggered, the system immediately pauses requests to that target, enters a backoff period (configurable, default 30-90 seconds with exponential increase), rotates to a fresh IP and session, and resumes scraping at a reduced rate. The data collection gap from a block event is typically under 2 minutes.

Rate limiting is factored into your data delivery SLA at setup. We provision sufficient infrastructure capacity for your specific freshness requirements, meaning your target update frequency (hourly, 15-minute, etc.) is always achievable even with conservative per-request delays, by distributing requests across many concurrent sessions and IP pools.

Yes. Cloudflare's rate limiting operates at the IP and session level. Our rate limiting system works in concert with our proxy rotation and fingerprint masking to ensure that from Cloudflare's perspective, each IP sees a low, human-like request frequency. The aggregate throughput across our distributed infrastructure remains high even while each individual IP looks completely benign.

A token bucket algorithm controls request flow by maintaining a bucket that fills with tokens at a steady rate. Each request consumes one token, and requests are only permitted when tokens are available. If the bucket is empty, the request must wait. The bucket has a maximum capacity, which allows short bursts of traffic up to the bucket size while enforcing a long-term average rate. This approach is widely used in web scraping because it naturally smooths out request patterns while allowing brief acceleration when needed.

Rate limiting sets a hard ceiling on the number of requests allowed within a given time window and rejects or queues excess requests. Throttling, by contrast, slows down request processing rather than rejecting them outright — adding delays to space requests over time. In practice, effective scraping systems use both: throttling to maintain a steady, human-like request cadence, and rate limiting as a safety valve to prevent accidentally overwhelming a target server.

Exponential backoff is a retry strategy where the wait time between successive retry attempts doubles after each failure — for example, 1 second, 2 seconds, 4 seconds, 8 seconds, and so on. This pattern is critical for web scraping because it prevents a failing scraper from hammering a server that is already under stress. Most websites interpret rapid repeated requests to an error page as aggressive bot behavior, which triggers escalating defensive measures.

Websites analyze request timing using statistical methods to detect bots. Human browsing produces variable inter-request intervals that follow a roughly log-normal distribution with natural pauses for reading. Bot traffic typically shows either perfectly uniform intervals (a dead giveaway of fixed sleep timers) or unnaturally fast bursts. Advanced detection systems compute the coefficient of variation and entropy of request intervals to distinguish automated from human traffic patterns.

A fixed window rate limiter counts requests within discrete time blocks (e.g., 0-60 seconds, 60-120 seconds), which creates a vulnerability where a burst of requests at the boundary of two windows can effectively double the allowed rate. A sliding window rate limiter tracks requests over a continuously moving time period, providing smoother and more accurate rate enforcement. For scraping, sliding window detection is harder to game because there is no exploitable boundary between time periods.

The crawl-delay directive in robots.txt specifies the minimum number of seconds a crawler should wait between requests to that server. While not part of the original robots.txt standard and not universally supported by search engines, it provides a direct signal from the website operator about their preferred crawling pace. Respecting crawl-delay demonstrates good faith, reduces the risk of IP bans, and helps maintain long-term access to target sites.