What are some common mistakes with API rate limiting?
An example of an AI chatbot conversation about common API rate limiting mistakes.
What are some common mistakes with API rate limiting?
Common mistakes include not setting limits based on user behavior, ignoring burst traffic, and failing to communicate limits.
How can I effectively implement rate limiting?
You can implement rate limiting by using algorithms like Token Bucket or Leaky Bucket, and adjusting limits based on usage patterns.
What happens if I exceed the rate limit?
Exceeding the rate limit typically results in HTTP 429 Too Many Requests responses, which inform users to slow down.
Can rate limiting affect user experience?
Yes, if not implemented carefully, it can lead to frustration for users, especially if they hit limits unexpectedly.
What tools can help with monitoring API usage?
Tools like API Gateway, Prometheus, and Grafana can help monitor and visualize API usage effectively.
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