# API Rate Limits
Learn about API rate limits and how to work with them.
The Bounsel API employs several safeguards to protect the application from brute force and denial of service attacks or bursts of incoming traffic in general to maximize its stability. Clients who send many requests in a short timeframe may see error responses that show up as status code 429.
Treat these limits as maximums and don’t generate unnecessary load. See Handling limiting gracefully for advice on handling 429s.
The configuration of these API rate limits might be different for various Bounsel applications or different endpoints depending on the complexity of the underlying operation or security requirements. Furthermore, these API limits can change at any moment without notice to prevent abuse.
# Handling limiting gracefully
Rate limiting can occur under a variety of conditions, but the most common is running a large volume of closely-spaced requests. Often this is part of an analytical or migration operation. When engaging in these activities, you should try to control the request rate on the client-side.
When the API rate limit is hit then the Bounsel API will set to additional response headers:
x-ratelimit-reset: Number of seconds that tells when the current rate limit will be reset. When you want to retry your request then retry after that time.
x-ratelimit-remaining: Number of requests left per minute that allow that endpoint.
x-ratelimit-limit: Number of requests per minute that allow that endpoint.
A basic technique for integrations to gracefully handle limiting is to watch for 429 status codes and build in a retry mechanism. The retry mechanism should follow an exponential backoff schedule to reduce request volume when necessary. We’d also recommend building some randomness into the backoff schedule to avoid a thundering herd effect.
You can only optimize individual requests to a limited degree, so an even more sophisticated approach would be to control traffic to Bounsel at a global level, and throttle it back if you detect substantial rate limiting. A common technique for controlling rate is to implement something like a token bucket rate-limiting algorithm on the client-side. Ready-made and mature implementations for token buckets are available in almost any programming language.