Hands-On System Programming with Go

Leaky bucket

We saw how to build a rate limiter using ticker in the previous chapters: by using time.Ticker to force a client to await its turn in order to get served. There is another take on rate limiting of services and libraries that's known as the leaky bucket. The name evokes an image of a bucket with a few holes in it. If you are filling it, you have to be careful to not put too much water into the bucket, otherwise it's going to overflow. Before adding more water, you need to wait for the level to drop – the speed at which this happens will depend on the size of the bucket and the number of the holes it has. We can easily understand what this concurrency pattern does by taking a look at the following analogy:

•  The water going through ...