Version 3.2.0 of Kafka for JUnit has been released. It increases all Kafka dependencies to 3.2.0.

Sampling data from a continuous stream of data is a useful technique to efficiently extrapolate information from a potentially large body of data. There are a couple of sampling strategies in literature that vary in their degree of complexity. I'd like to introduce you to a rather simple sampling strategy that is easy to implement as well as easy to reason about and might take you a long way until you have to go for more advanced solutions. I'm talking about Bernoulli sampling.

Version 3.1.0 of Kafka for JUnit has been released. It increases all Kafka dependencies to 3.1.0.