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Valid CCAAK Exam Cram - Valid CCAAK Exam Format

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Confluent CCAAK Exam Syllabus Topics:

Topic
Details

Topic 1

Apache Kafka® Cluster Configuration: This section of the exam measures skills of a Kafka Administrator and includes configuring broker properties, tuning for performance, managing topic-level settings, and applying best practices for production-grade environments.

Topic 2

Observability: This section of the exam measures skills of a Site Reliability Engineer and focuses on monitoring Kafka clusters. It assesses knowledge of metrics, logging, and alerting tools, including how to use them to maintain cluster health and performance visibility.

Topic 3

Kafka Connect: This section of the exam measures skills of a Site Reliability Engineer and addresses the use and management of Kafka Connect for data integration. It includes setting up connectors, managing configurations, and ensuring efficient movement of data between Kafka and external systems.

Topic 4

Deployment Architecture: This section of the exam measures skills of a Kafka Administrator and covers different Kafka deployment topologies. It evaluates understanding of high availability, disaster recovery, multi-data center replication, and the roles of Zookeeper or KRaft in the cluster architecture.

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Confluent Certified Administrator for Apache Kafka Sample Questions (Q18-Q23):

NEW QUESTION # 18
How does Kafka guarantee message integrity after a message is written on a disk?

A. A message cannot be altered once it has been written.
C A message can be grouped with message sharing the same key to improve read performance
B. A message can be edited by the producer, producing to the message offset.
C. Only message metadata can be altered using command line (CLI) tools.

Answer: A

Explanation:
Kafka ensures message immutability for data integrity. Once a message is written to a Kafka topic and persisted to disk, it cannot be modified. This immutability guarantees that consumers always receive the original message content, which is critical for auditability, fault tolerance, and data reliability.

NEW QUESTION # 19
You are managing a Kafka cluster with five brokers (broker id '0', '1','2','3','4') and three ZooKeepers. There are 100 topics, five partitions for each topic, and replication factor three on the cluster. Broker id '0' is currently the Controller, and this broker suddenly fails.
Which statements are correct? (Choose three.)

A. The Controller is responsible for reassigning partitions to the consumers in a Consumer Group.
B. The Controller is responsible for electing Leaders among the partitions and replicas.
C. The Controller uses the epoch number to prevent a split brain scenario.
D. The number of Controllers should always be equal to the number of brokers alive in the cluster.
E. Kafka uses ZooKeeper's ephemeral node feature to elect a controller.
F. The broker id is used as the epoch number to prevent a split brain scenario.

Answer: B,C,E

Explanation:
Kafka relies on ZooKeeper's ephemeral nodes to detect if a broker (controller) goes down and to elect a new controller.
The controller manages partition leadership assignments and handles leader election when a broker fails.
The epoch number ensures coordination and avoids outdated controllers acting on stale data.

NEW QUESTION # 20
Kafka Connect is running on a two node cluster in distributed mode. The connector is a source connector that pulls data from Postgres tables (users/payment/orders), writes to topics with two partitions, and with replication factor two. The development team notices that the data is lagging behind.
What should be done to reduce the data lag*?
The Connector definition is listed below:
{
"name": "confluent-postgresql-source",
"connector class": "PostgresSource",
"topic.prefix": "postgresql_",
& nbsp;& nbsp;& nbsp;...
"db.name": "postgres",
"table.whitelist": "users.payment.orders",
"timestamp.column.name": "created_at",
"output.data format": "JSON",
"db.timezone": "UTC",
"tasks.max": "1"
}

A. Increase the number of Connect Nodes.
B. Increase the number of partitions.
C. Increase the number of Connect Tasks (tasks max value).
D. Increase the replication factor and increase the number of Connect Tasks.

Answer: C

Explanation:
The connector is currently configured with "tasks.max": "1", which means only one task is handling all tables (users, payment, orders). This can create a bottleneck and lead to lag. Increasing tasks.max allows Kafka Connect to parallelize work across multiple tasks, which can pull data from different tables concurrently and reduce lag.

NEW QUESTION # 21
You are using Confluent Schema Registry to provide a RESTful interface for storing and retrieving schemas.
Which types of schemas are supported? (Choose three.)

A. JSON
B. Protobuf
C. Avro
D. gRPC
E. Thrift

Answer: A,B,C

Explanation:
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.

NEW QUESTION # 22
In certain scenarios, it is necessary to weigh the trade-off between latency and throughput. One method to increase throughput is to configure batching of messages.
In addition to batch.size, what other producer property can be used to accomplish this?

A. delivery.timeout.ms
B. compression
C. sendbufferbytes
D. linger.ms

Answer: D

Explanation:
The linger.ms property sets the maximum time the producer will wait before sending a batch, even if the batch isn't full. By increasing linger.ms, you allow more records to accumulate in the batch.

NEW QUESTION # 23
......

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