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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"".