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exponential rate limiting – Tony Finch

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Following my previous post on rate limiting with GCRA, leaky buckets without the buckets, I reviewed my old notes on rate limiting for Exim. I thought I should do a new write-up of the ideas that I hope will be more broadly interesting. Exponential rate limiting uses an exponentially-weighted moving average to measure the client’s rate. It is motivated by a shift of perspective: Algorithms like GCRA and leaky bucket don’t allow you to separate these two points because they don’t measure the client’s rate as a concrete number. A moving average allows more flexible policy enforcement because the rate measurement is meaningful even when you don’t apply back-pressure. For example, it’s useful in a dry run mode, or when diverting messages to a quarantine. An exponential rate limiter stores, for each client: This is a similar amount of space as leaky bucket. GCRA uses less space because it only needs to store a time. The main disadvantage is that an exponential rate limiter needs fairly comp

Following my previous post on rate limiting with GCRA, leaky buckets without the buckets , I reviewed my old notes on rate limiting for Exim . I thought I should do a new write-up of the ideas that I hope will be more broadly interesting. Edit: I have written some more recent notes on ratelimiting . Exponential rate limiting uses an exponentially-weighted moving average to measure the client’s rate. It is motivated by a shift of perspective: first measure the client’s rate, then compare it to the limit. Algorithms like GCRA and leaky bucket don’t allow you to separate these two points because

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