Pass the Confluent Certified Administrator CCAAK Questions and answers with ValidTests

Kafka supports quotas to limit the broker resources each client can use. This is used to prevent one client from monopolizing cluster bandwidth.

From Kafka documentation:

“Quotas can be applied to both producers and consumers. These quotas are enforced based on the number of bytes per second, and they are applied to ensure fair usage of broker resources.”

A. Quotas → Correct: Admins can define quotas on throughput per client ID or user.

B. Consumer Groups → Incorrect: This controls parallelism in consumption but not resource fairness.

C. Rebalancing → Incorrect: This helps with load balancing but not with resource limitation.

D. ACLs → Incorrect: ACLs define access permissions but not resource usage.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 10 (“Administering Kafka”), p. 306–308

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Confluent Schema Registry supports the following schema types for use with Kafka:

Avro

Protobuf

JSON Schema

These schemas are officially supported for subject versioning, compatibility checks, and REST interface integration.

From Confluent documentation:

“The Confluent Schema Registry supports Avro, JSON Schema, and Protobuf formats.”

Incorrect Options:

gRPC is not supported as a schema format.

Thrift is not supported in Schema Registry.

Page Reference:

Confluent Kafka: The Definitive Guide, 1st Edition, Chapter 7, p. 208–210

Confluent Schema Registry Documentation: Overview Section (Schema Types)

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Kafka's Controller is a broker that also performs controller duties. It is not a dedicated node. Therefore, it continues to host topics, partitions, and leaders just like any other broker.

From Kafka documentation:

“The controller is one of the brokers in the cluster and continues to perform all normal broker functions.”

A → Correct: The controller is also a normal broker with partitions.

B/C/D → Incorrect: Replication and consumer fetches are not tied to the controller.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 6, p. 190

Apache Kafka Documentation: Kafka Controller Behavior

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Kafka Connect is a framework for connecting Kafka with external systems like databases, key-value stores, file systems, etc. It handles ingestion and egress of data using scalable and fault-tolerant connectors.

From Kafka documentation:

“Kafka Connect is a scalable and fault-tolerant component for efficiently streaming data between Kafka and other systems.”

A → Correct: Purpose-built for data integration.

B → For stream processing, not integration.

C → Manages schemas, not data movement.

D → For HTTP-based Kafka interaction.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 8, p. 239–241

Apache Kafka Documentation: Kafka Connect Overview

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In Kafka, a Leader ID of -1 indicates that no broker is currently the leader for that partition. This typically happens when the only replica for the partition (broker 1 in this case) is offline or unavailable.

From Kafka documentation:

“If the leader for a partition is not available, the leader ID will be reported as -1.”

A → Correct: The broker hosting the sole replica is down.

B/C/D → Incorrect and unrelated to leader election behavior.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 6, p. 191

Apache Kafka Documentation: Topic Description Output and Leader Election

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In Kafka Connect, sink connectors consume data from Kafka topics and send it to external systems (e.g., databases, object storage, search indexes).

From Kafka documentation:

“Sink connectors receive data from Kafka topics and write it to external systems.”

A → Correct: Moves data out of Kafka.

B → Moves data into Kafka.

C → Not a connector type.

D → Not a standard connector classification.

Page Reference:

Kafka: The Definitive Guide, 1st Edition, Chapter 8, p. 241

Apache Kafka Documentation: Kafka Connect – Sink Connectors

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