Certified Developer for Apache Kafka · 40% of the exam

Apache Kafka Fundamentals: free practice questions

5 sample questions from our 18-question bank for this domain — answers and explanations included. These are the same scenario-based style as the real Confluent exam.

1. Which delivery semantic means a consumer may process a message more than once if a failure occurs after processing but before the offset is committed?

  • A. At-least-once✓ Correct
  • B. At-most-once
  • C. Exactly-once
  • D. No-delivery
Explanation

At-least-once delivery commits offsets after processing; if a failure happens before the commit, the message is reprocessed on restart (possible duplicates). At-most-once (B) commits before processing (possible loss), exactly-once (C) avoids both with additional guarantees, and 'no-delivery' (D) isn't a semantic.

2. A developer wants a consumer to start reading a topic from the very beginning when no committed offset exists. Which configuration achieves this?

  • A. auto.offset.reset=earliest✓ Correct
  • B. auto.offset.reset=latest
  • C. enable.auto.commit=false only
  • D. acks=all
Explanation

`auto.offset.reset=earliest` makes a consumer with no committed offset start from the earliest available message. `latest` (B) would start from new messages only, disabling auto-commit (C) controls when offsets are committed (not where to start), and acks (D) is a producer setting.

3. A consumer group experiences a REBALANCE. What triggers this?

  • A. A change in group membership or subscribed partitions (e.g., a consumer joins/leaves or partitions change)✓ Correct
  • B. A producer changing its acks setting
  • C. A schema being registered in the Schema Registry
  • D. Increasing the log retention time
Explanation

A rebalance redistributes partition assignments when group membership changes (a consumer joins, leaves, or fails) or the set of subscribed partitions changes. Producer acks (B), schema registration (C), and retention changes (D) don't trigger consumer-group rebalances.

4. Which statement about Kafka topics and partitions is TRUE?

  • A. A topic is a logical stream split into one or more partitions distributed across brokers✓ Correct
  • B. A topic must always have exactly one partition
  • C. Partitions are stored only on consumers
  • D. A topic cannot be replicated
Explanation

A topic is a named logical event stream divided into partitions that are distributed (and replicated) across brokers for scalability and fault tolerance. A topic can have many partitions (not exactly one, B), partitions live on brokers not consumers (C), and topics are replicated per the replication factor (D).

5. Two messages with the SAME key are produced to a topic. What does Kafka guarantee about them?

  • A. They go to the same partition, preserving their relative order✓ Correct
  • B. They are load-balanced across different partitions
  • C. They are deduplicated automatically
  • D. They are always delivered exactly once with no configuration
Explanation

Kafka's default partitioner hashes the key so all messages with the same key land in the same partition, and order is guaranteed within a partition. Different partitions (B) would break ordering, Kafka doesn't auto-deduplicate by key (C), and exactly-once (D) requires specific configuration.

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