Yes — replication reduces the risk of data loss in Kafka but doesn't eliminate it, since the producer's acknowledgment setting determines how many replicas must confirm a write before it's considered safe.
Key Points: • With acks=1, only the partition leader needs to acknowledge the write; if the leader crashes before followers replicate it, that record is lost even though replication is configured. • Setting acks=all ensures all in-sync replicas confirm the write, but without min.insync.replicas set appropriately, a single in-sync replica could still be enough, weakening the guarantee. • Unclean leader election (electing a replica that wasn't fully in sync) can also cause data loss if enabled and a non-ISR replica becomes leader after a failure. • Consumer-side data loss can also occur if offsets are committed before messages are fully processed, and a crash happens in between.
Example: A team running acks=1 might see recently produced records disappear if the leader broker crashes moments after acknowledging the write but before followers finish replicating it — switching to acks=all with min.insync.replicas=2 closes that gap.
Interview Tip: A concise interview answer is:
"Yes, data loss is still possible with replication if acks=1 is used and the leader fails before followers catch up, or if unclean leader election is enabled — the fix is acks=all combined with an appropriate min.insync.replicas and disabling unclean leader election for critical topics."