Kafka is also a system that can make pretty good general use of more CPUs and more storage, but doesn't have much need for RAM. Tying the CPU and RAM together whether by CPU model or cloud vendor offerings is annoying if you're trying to scale only vertically.
I find that if you are seeking lots of consumers around large topics no amount of RAM is really sufficient, and if you are mostly sticking to the tails like a regular Kafka user, even 64GB is usually way more than enough.
CPU isn't usually a problem until you start using very large compactions, and then suddenly it can be a massive bottleneck. (Actually I would love to abuse more RAM here but log.cleaner.dedupe.buffer.size has a tiny maximum value!)
Kafka Streams (specifically) is also configured to transact by default, even though most applications aren't written to be able to actually benefit from that. If you run lots of different consumer services this results in burning a lot of CPU on transactions in a "flat profile"-y way that's hard to illustrate to application developers since each consumer, individually, is relatively small - there's just thousands of them.
