Apache Kafka Practice Exam 2025 – The Complete All-in-One Guide for Exam Success!

The resilience and fault tolerance of Apache Kafka is significantly enhanced by the replication of data across brokers. When data is produced to Kafka, it is not just stored on a single broker; instead, it is replicated to multiple brokers in a Kafka cluster. This means that if one broker fails, there are copies of the data available on other brokers, ensuring that data is not lost and can still be accessed.

Replication also plays a crucial role in maintaining data availability and consistency. The number of replicas can be configured, allowing users to choose how many copies of each message should be kept across the cluster. This way, even in the event of hardware failures or network issues, Kafka can continue processing messages without interruption, as there will always be a replica available to handle requests.

The other options do not contribute to Kafka's resilience in the same way. Centralized data processing could create a single point of failure, while the use of relational databases is not a feature of Kafka and does not align with its design as a distributed messaging system. Single-threaded message consumption can limit performance but is not related to the core resilience features of the architecture. Therefore, replication is the key mechanism that ensures Kafka's ability to withstand failures while maintaining data integrity.