Conquer Apache Kafka 2025 – Dive into Data Streaming Dominance!

Allowing an out of sync replica to become a leader introduces a significant risk to data consistency and can lead to potential data loss. In Apache Kafka, each topic partition has one leader and multiple followers (replicas). The leader is responsible for all reads and writes for that partition, while followers replicate the data from the leader.

When a replica falls out of sync, it means that it has missed some of the updates that have occurred in the leader. If this out of sync replica is then promoted to be the leader, any data that was held only on the previous leader but not replicated to the new leader is no longer accessible. This situation can lead to a scenario where clients reading from the new leader may receive incomplete or outdated information. Ultimately, this compromises the integrity of the data being served, which is critical for ensuring that clients receive consistent and reliable information.

Understanding the importance of having a fully synchronized replica as a leader is essential for maintaining data integrity within the Kafka ecosystem. In scenarios where data consistency is crucial, promoting an out of sync replica can severely undermine the system's reliability.