That's the basics yes. You have a pletora of things coming next. One is "Windowing" mentioned in the article, it's well explained there, and maybe it looks simple, but when you start with it, takes some time to wrap your mind around it.
The other things in kafka world are stateful transformations, which you would normally do using Java's Flink. The closest in python is Faust (the fork) [0]. What are stateful aggregations? something like doing SQL on top of a topic: group_by, count, reduce, and joins. So similar to SQL that you have kSQL [1].
Consumer groups IMO falls under basic usage, if you need to scale, take a look at it, and what are partitions and replicas, with that in mind, you'll be ok.
The other things in kafka world are stateful transformations, which you would normally do using Java's Flink. The closest in python is Faust (the fork) [0]. What are stateful aggregations? something like doing SQL on top of a topic: group_by, count, reduce, and joins. So similar to SQL that you have kSQL [1].
Consumer groups IMO falls under basic usage, if you need to scale, take a look at it, and what are partitions and replicas, with that in mind, you'll be ok.
[0]: https://github.com/faust-streaming/faust
[1]: https://www.confluent.io/blog/ksql-streaming-sql-for-apache-...