Rate Limit

A rate limit is a restriction an API provider imposes on how many requests a single application, API key, or user can make within a given time window — for example, "100 requests per minute" or "10,000 requests per day" — designed to protect the provider's infrastructure from overload, prevent abuse, and (for paid APIs) enforce plan-tier pricing boundaries. Why it matters for no-code builders specifically: rate limits are one of the most common causes of "my automation randomly stopped working" bugs, because a workflow that runs fine at low volume (10 automations a day) can silently start failing once usage scales (10,000 automations a day suddenly hitting a provider's 5,000/day cap), and the failure often looks like intermittent, hard-to-diagnose errors rather than a clear "you're over your limit" message unless the builder specifically checks for a 429 status code. Understanding rate limits is also essential when designing automations that process bulk data — looping an automation over 50,000 spreadsheet rows, each triggering an individual API call, will almost always hit a rate limit partway through unless the workflow includes deliberate throttling or batching. How it works: APIs typically communicate rate limit status through response headers (e.g., `X-RateLimit-Limit: 100`, `X-RateLimit-Remaining: 23`, `X-RateLimit-Reset: 1719856800`) so a well-built client can proactively slow down before hitting the wall, and return an HTTP 429 "Too Many Requests" status code when the limit is actually exceeded, often with a `Retry-After` header indicating how long to wait before trying again. Worked example — handling a rate limit in a Make scenario that enriches 2,000 leads via a third-party data API capped at 60 requests/minute: instead of firing all 2,000 requests as fast as possible (guaranteed to trigger 429 errors after the first minute), the builder adds a "Sleep" module after every batch of 50 records — pausing the scenario for a calculated delay before continuing — and wraps each API call in an error handler that catches a 429 response specifically, reads the `Retry-After` header, waits that long, then retries the same request rather than failing the entire run. Production-grade no-code automations dealing with high-volume API calls should always build for rate limits defensively (batching, throttling, retry-with-backoff) rather than reactively (only adding handling after the automation starts failing in production). Some APIs also enforce burst limits distinct from sustained rate limits (e.g., "10 requests per second, up to 1,000 per day") — hitting either ceiling produces the same 429 response, so a robust automation checks the response headers rather than assuming a single fixed threshold.