In what cases and under what conditions can data loss occur in Kafka?

Data loss in Kafka can occur in the following cases:

• Incorrect configuration of replication and acknowledgments (acks): if the producer is configured with acks=0 or acks=1 and the broker crashes before data is replicated to other brokers, data may be lost.
• Insufficient number of replicas: if the number of replicas is less than 2, and a broker with data crashes before replication, data will be lost.
• Using an incorrect topic cleanup policy: for example, using the delete cleanup policy with a short retention time (retention.ms) can lead to data being deleted before consumers read it.
• Errors in producer or consumer: if the producer does not handle write errors, or the consumer does not commit offsets, data may be skipped.
• Hardware failures without backups: if a broker loses data due to disk failure and there are no replicas or backups.

To minimize data loss, it is recommended to use acks=all, sufficient number of replicas, properly configure retention, and carefully handle errors on the producer and consumer sides.