Managing rolling updates is a crucial aspect of Kafka operations. In a production environment, it’s essential to ensure that rolling updates cause minimal disruption to eliminate the potential impact on the cluster’s availability and client applications. Automating this process with Kubernetes is not straightforward, as it lacks knowledge about Kafka clusters and how to maximise their availability during updates. Strimzi has a component known as KafkaRoller, which manages coordination of rolling restarts and reconfiguration of Kafka nodes. In this session, we will delve into KafkaRoller’s decision making process and the safety assessment when performing rolling updates, leveraging various data sources such as Kafka metrics, Admin API and Kubernetes API.