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

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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Comprehensive and Detailed Explanation From Exact Extract:

✅ C. Consumers can consume both committed and uncommitted transactions.By default, Kafka consumers only read committed messages if they are configured with isolation.level=read_committed. However, if configured as read_uncommitted, they can also consume uncommitted (potentially aborted) transactional messages.

From Kafka Documentation:

"The isolation.level setting controls whether the consumer will read only committed messages or all messages, including uncommitted messages from ongoing or aborted transactions."

✅ D. Information about producers and their transactions is stored in the _transaction_state topic.Kafka uses an internal topic named __transaction_state to maintain metadata about producer transactions. This topic is essential for tracking the transaction lifecycle, fencing, and recovery.

From Kafka Internals:

“Kafka stores the state of active and completed transactions in an internal topic called __transaction_state.”

RetriableException is a subclass of KafkaException, indicating transient issues that might succeed if retried. Examples include:

LeaderNotAvailableException: Happens when metadata is not yet propagated or leader election is in progress.

NotEnoughReplicasException: Happens when the number of in-sync replicas is insufficient. This can be transient if replicas come back online.

From the Apache Kafka Java Client documentation:

"These exceptions (like LeaderNotAvailableException, NotEnoughReplicasException) are transient and the client will retry them automatically depending on retry configuration."

RecordTooLargeException and AuthorizationException are non-retriable as they indicate client-side or permission errors.