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| Vendor: | Confluent |
|---|---|
| Exam Code: | CCAAK |
| Exam Name: | Certified Administrator for Apache Kafka |
| Exam Questions: | 54 |
| Last Updated: | February 27, 2026 |
| Related Certifications: | Confluent Certified Administrator |
| Exam Tags: | Advanced Kafka Administrators and Site Reliability Engineers (SREs) |
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You are using Confluent Schema Registry to provide a RESTful interface for storing and retrieving schemas.
Which types of schemas are supported? (Choose three.)
Avro is the original and most commonly used schema format supported by Schema Registry.
Confluent Schema Registry supports JSON Schema for validation and compatibility checks.
Protocol Buffers (Protobuf) are supported for schema management in Schema Registry.
You want to increase Producer throughput for the messages it sends to your Kafka cluster by tuning the batch size ('batch size') and the time the Producer waits before sending a batch ('linger.ms').
According to best practices, what should you do?
Increasing batch.size allows the producer to accumulate more messages into a single batch, improving compression and reducing the number of requests sent to the broker.
Increasing linger.ms gives the producer more time to fill up batches before sending them, which improves batching efficiency and throughput.
This combination is a best practice for maximizing throughput, especially when message volume is high or consistent latency is not a strict requirement.
What is the correct permission check sequence for Kafka ACLs?
What is the correct permission check sequence for Kafka ACLs?
Kafka checks permissions in the following sequence:
1. Super Users: If the user is a super user (defined via super.users), access is granted immediately.
2. Allow ACL: If there is a matching Allow ACL, Kafka proceeds to the next step.
3. Deny ACL: If there is a matching Deny ACL, access is denied (even if an Allow exists).
4. Deny: If no matching ACLs are found, access is denied by default.
This order ensures that super users bypass ACLs, denials override allows, and default is deny.
A topic 'recurring payments' is created on a Kafka cluster with three brokers (broker id '0', '1', '2') and nine partitions. The 'min.insync replicas' is set to three, and producer is set with 'acks' as 'all'. Kafka Broker with id '0' is down.
Which statement is correct?
With 9 partitions spread across 3 brokers, each broker typically hosts 3 leaders (assuming even distribution). When Broker 0 fails, the partitions for which it was leader will elect new leaders on brokers 1 or 2 if enough in-sync replicas (ISRs) remain. But since min.insync.replicas=3 and only 2 brokers are up, no partition can meet the minimum in-sync replica requirement, so producers with acks=all will fail to write. However, for partitions where Broker 0 is not the leader, consumers can still read committed messages. Given that only 3 partitions likely had Broker 0 as leader, six partitions remain accessible for reads, but not writes.
The Consumer property 'auto offset reset' determines what to do if there is no valid offset for a Consumer Group.
Which scenario is an example of a valid offset and therefore the 'auto.offset.reset' does NOT apply?
In this scenario, the offset itself is still valid, even though the record at that offset was compacted away. The consumer can continue consuming from the next available record. Therefore, auto.offset.reset does NOT apply, because there is a valid offset present.
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