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

The replication factor is a crucial setting in Kafka because it directly impacts data availability and fault tolerance. By defining how many copies of each message are stored across different brokers in a Kafka cluster, the replication factor ensures that even if one or more brokers fail, the data remains accessible. For instance, if the replication factor is set to three, each message will be stored on three different brokers. This redundancy means that if one broker goes down, the data can still be retrieved from the other two brokers, thus increasing the system's resilience against data loss.

A higher replication factor generally leads to greater fault tolerance since it provides more copies of the data. However, it also increases the resources required for storage and can have performance implications due to the additional overhead involved in replicating messages. Balancing the replication factor is essential depending on the specific requirements for availability and durability in a production environment.

The other options do not accurately represent the role of the replication factor. It does not control message compression, determine the number of partitions, or define user access levels, as these are governed by different settings in Kafka. Thus, recognizing the importance of the replication factor in enabling data reliability is critical for effectively managing a Kafka cluster.