Apache Kafka Complete Practice Exam 2025 – All-in-One Prep

Kafka ensures high availability and fault tolerance through a well-defined mechanism when a broker fails. When a broker goes down, the first step taken by Kafka is to promote one of its replica partitions to become the new leader for that particular partition.

In Kafka, each partition of a topic can be replicated across multiple brokers to ensure that data is not lost even if one broker becomes unavailable. Each partition has one leader, which handles all read and write requests, and multiple followers that replicate the data. When the leader broker fails, Kafka will designate one of the available follower replicas as the new leader. This process is crucial for maintaining the continuity and reliability of service without requiring human intervention, allowing clients to continue their read and write operations seamlessly.

This automatic leader election process relies on Kafka’s coordination system, typically Zookeeper, which tracks the health of brokers and manages the state of partitions. This mechanism enables Kafka to maintain resilience and ensures that the data remains accessible even in the event of broker failures.

Other responses suggest different methods that Kafka does not actually employ, such as replacing brokers with spares or shutting down the entire cluster, which would lead to service interruptions. Kafka’s design focuses on maintaining uptime and availability through the promotion of replicas rather than stopping operations altogether