CCDAK Exam Dumps : Confluent Certified Developer for Apache Kafka Certification Examination

To send failed records to a dead letter queue (DLQ), you must configure:

errors.tolerance=all: Tells the connector to not fail on errors but handle them (e.g., send to DLQ).

errors.deadletterqueue.topic.name=DLQ-Topic: Specifies the DLQ topic.

errors.deadletterqueue.context.headers.enable=true: Includes error context in message headers.

From Kafka Connect Error Handling Docs:

“Kafka Connect supports directing problematic records to a separate topic (DLQ) using errors.* configs. Headers can include failure metadata.”

Options D, E, F are related to logging, not DLQ behavior.

Low I/O thread activity with blocked throughput often indicates that producer callbacks are consuming too much time, causing the sender thread to block while waiting for onCompletion() to finish.

From Kafka Producer Performance Guide:

“Expensive logic in callbacks (e.g., I/O or complex computation) can block the sender thread, reducing throughput.”

Compression (A) may slightly impact CPU but not I/O thread usage.

Large batches (B) improve throughput if managed correctly.

A Layer 2 network issue (C) would lead to packet loss, not specifically low callback metrics.

With acks=all and min.insync.replicas=2, Kafka requires at least two in-sync replicas to acknowledge a write. If only one broker is alive, the condition fails, and NotEnoughReplicasException is thrown by the producer.

From Kafka Producer Exception Docs:

“NotEnoughReplicasException is thrown when the number of in-sync replicas is insufficient to satisfy acks=all with min.insync.replicas.”

NetworkException is generic and not raised here.

NotCoordinatorException is related to consumer group coordination.

NotLeaderForPartitionException is unrelated unless accessing an unassigned leader.