Elastically Scale Apache Kafka in a Single Click | Confluent Cloud

This post introduces the self-serve capability to elastically scale dedicated Kafka clusters in Confluent Cloud by expanding and shrinking them in terms of CKUs. It details the user experience through the UI, CLI, and APIs, including cluster load metrics, resizing workflows, safeguards against adverse performance impacts (e.g., partition count exceeding CKU limits), billing implications, and the underlying two-step process of capacity adjustment and data rebalancing. Future plans for autoscaling based on policies are also mentioned.