This document summarizes techniques for workload distribution and rebalancing in Apache Kafka clusters. It begins by describing the workload distribution problem in stateful distributed systems like Kafka. It then covers manual rebalancing using built-in Kafka utilities, semi-automated rebalancing with the Kafka Assigner tool, and fully autonomous rebalancing with Cruise Control. Cruise Control provides centralized monitoring and automatic management of workloads and partitions in the Kafka cluster to optimize resource utilization and rebalance in response to failures or traffic changes. It allows rebalancing goals to be met without manual intervention.