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

Having insufficient replicas in a Kafka cluster can lead to data loss during a leader failure. In Kafka, replication is crucial for ensuring data durability and availability. Each partition has one leader and one or more replicas. The leader is responsible for all read and write operations, while the replicas serve as backups.

If the number of replicas is low, there may not be enough copies of the data to rely on in the event that the leader fails. In this scenario, if the leader goes down and there are not enough replicas to take over as a new leader, any unreplicated data that was written to the partition when the leader was active could be lost. This situation can compromise the reliability of the system and defeat the purpose of using Kafka for persistent message storage.

In contrast, other scenarios mentioned, such as data being replicated too frequently or the system slowing down due to synchronization, are not directly related to the number of replicas but rather to how replicas are managed or the configuration of the cluster. Additionally, while leading replicas might become overloaded, this is generally more about resource management rather than a direct consequence of having too few replicas. Thus, it is important to adequately configure replication factors to maintain data reliability and prevent loss during failures.