Apache Kafka has become the de facto standard for data streaming, but managing its capacity and scaling can be challenging due to unpredictable spikes in demand. Traditional approaches to capacity management, such as provisioning resources based on anticipated peak demand or scaling up and down during predictable periods, come with significant operational overhead and costs. In contrast, serverless clusters that autoscale to demand offer a more cost-effective solution, providing instant scalability without the need for manual intervention or upfront provisioning of resources. By automating capacity planning and scaling, these clusters can reduce infrastructure costs by 75%, engineering time and resources by over 50%, and downtime risk by up to 100x, resulting in significant cost savings that can be upwards of $750,000 per year. With the release of Enterprise clusters on both AWS and Azure, this solution is now more accessible and affordable than ever.