I have not used Kafka, but what the book describes works with most queue systems. And those are great for localizing dynamic complexity. One part of your system behaving weirdly (spiking, dying, fluctuating etc. ) can’t affect other parts because they sit at the other end of a queue happily consuming the messages at their own pace. This means tour complex system becomes less complex in terms of behavior and is less likely to end up in some weird metstable state
This is sort of funny to me, since ActiveMQ had this exact problem. A single slow client could break the entire system because the broker would slow down producers to prevent exhausting the queue space. Which was exactly some "weird" state because it wasn't obvious what happened until you spent a lot of time debugging.