In Kafka Streams, when an instance is shut down via the close() API, we intentionally skip sending a LeaveGroup request. This is because often the shutdown is not due to a scaling down event but instead some transient closure, such as during a rolling bounce. In cases where the instance is expected to start up again shortly after, we originally wanted to avoid that member's tasks from being redistributed across the remaining group members since this would disturb the stable assignment and could cause unnecessary state migration and restoration. We also hoped
to limit the disruption to just a single rebalance, rather than forcing the group to rebalance once when the member shuts down and then again when it comes back up. So it's really an optimization for the case in which the shutdown is temporary.
That said, many of those optimizations are no longer necessary or at least much less useful given recent features and improvements. For example rebalances are now lightweight so skipping the 2nd rebalance is not as worth optimizing for, and the new assignor will take into account the actual underlying state for each task/partition assignment, rather than just the previous assignment, so the assignment should be considerably more stable across bounces and rolling restarts.
Given that, it might be time to reconsider this optimization. Alternatively, we could introduce another form of the close() API that forces the member to leave the group, to be used in event of actual scale down rather than a transient bounce.