At supermassive scale, a perennial problem with Kafka is "high fan-in" -- a large number of producers sending records to a small number of brokers. Even a relatively modest amount of data can overwhelm a broker when there are hundreds of thousands of concurrent producer requests.

This talk discusses a few real-world applications where high fan-in becomes a problem, and presents a few strategies for dealing with it. These include: fronting Kafka with an ingestion layer; separating brokers into read-only and write-only subsets; implementing specialized partitioning strategies; and scaling across clusters with "smart clients".