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

According to the official Apache Kafka Connect documentation, RegexRouter is the SMT specifically designed to dynamically change the destination topic name of records produced by a connector. It works by applying a regular expression to the original topic name and rewriting it to a new topic name.

This makes RegexRouter the correct choice when some records must be routed to a different topic, typically in combination with connector-level logic, predicates, or multiple connectors. It is commonly used for topic renaming, topic versioning, or routing records to alternate topics.

InsertField (Option B) only adds metadata fields (such as topic, partition, or timestamp) to the record payload and does not affect routing. TombstoneHandler (Option C) is used to manage null-value records, especially with compacted topics. HeaderFrom (Option D) copies fields into headers but does not change the target topic.

Therefore, RegexRouter is the only SMT that directly supports changing the output topic, as documented in the Kafka Connect SMT reference.

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According to the official Apache Kafka producer metrics documentation, the I/O thread ratio and I/O thread wait ratio indicate how busy the producer’s network I/O thread is and how much time it spends waiting. When both metrics are low, it means the I/O thread is underutilized and not blocked on network operations.

This strongly suggests that the bottleneck is not network-related. If there were network latency or a bad data link (Option B), the I/O thread wait ratio would be high. Similarly, large batches (Option A) or compression (Option D) generally increase throughput and would result in higher I/O utilization.

An expensive or blocking callback function (for example, heavy logic in onCompletion()) executes in the producer’s sender thread context. Kafka documentation explicitly warns that slow callbacks can throttle producer throughput because they delay the processing of acknowledgements and subsequent sends.

Therefore, the most likely and documented cause of low producer throughput with low I/O utilization is expensive callback logic in the producer code.

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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.