How to Elastically Scale Apache Kafka Clusters on Confluent Cloud

Elasticity is a fundamental feature of mature cloud services, enabling users to adjust capacity based on demand fluctuations, and Confluent Cloud now supports this capability for dedicated Apache Kafka clusters. Users can expand or shrink Kafka clusters in terms of Confluent Units (CKUs) through a self-serve model available via Confluent Cloud's UI, CLI, and public APIs. This allows for alignment with business needs and cost optimization while maintaining performance. Monitoring cluster load is essential before resizing, as high loads can increase latency and throttling, while low loads may suggest a cost-saving opportunity. The process involves adding or removing CKUs and rebalancing data, which takes a few hours depending on the size adjustment. Safeguards prevent adverse impacts during resizing, and billing adjusts according to the actual capacity used. The blog post emphasizes user experience, covering key aspects such as the control plane's role in resizing operations and introducing features like cluster load metrics. Future plans include enabling autoscaling based on user-defined policies to further ease capacity management.