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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	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 3	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 4	Apache Kafka® Security: This section of the exam measures skills of a Site Reliability Engineer and focuses on securing Kafka environments. It includes authentication mechanisms such as TLS and SASL, authorization using ACLs, and encrypting data at rest and in transit to ensure secure communication and access control.
Topic 5	Troubleshooting: This section of the exam measures skills of a Kafka Administrator and includes diagnosing common issues in Kafka clusters. It covers problem areas such as performance bottlenecks, message delivery failures, replication issues, and consumer lag, along with techniques to resolve them effectively.
Topic 6	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 (Q32-Q37):

NEW QUESTION # 32
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 replication factor and increase the number of Connect Tasks.
B. Increase the number of partitions.
C. Increase the number of Connect Tasks (tasks max value).
D. Increase the number of Connect Nodes.

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 # 33
Which property in broker configuration specifies that a broker belongs to a particular rack?
Which property in broker configuration specifies that a broker belongs to a particular rack?

A. zookeeper.rack
B. broker.rack
C. kafka.rack
D. client.rack

Answer: B

Explanation:
The broker.rack property is used in a Kafka broker's configuration to specify the rack or availability zone the broker belongs to. This is important for rack-aware replica placement, allowing Kafka to distribute replicas across different racks for fault tolerance.

NEW QUESTION # 34
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. Thrift
C. Avro
D. gRPC
E. Protobuf

Answer: A,C,E

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 # 35
What is the primary purpose of Kafka quotas?

A. Limit the total number of Partitions in the Kafka cluster
B. Throttle clients to prevent them from monopolizing Broker resources.
C. Guarantee faster response times for some clients.
D. Limit the number of clients that can connect to the Kafka cluster.

Answer: B

Explanation:
Kafka quotas are used to limit the throughput (bytes/sec) of producers and consumers to ensure fair resource usage and prevent any single client from overwhelming the brokers.

NEW QUESTION # 36
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?

A. The Consumer Group started for the first time.
B. The Consumer offset is less than the smallest offset in the partition (log start offset).
C. The Consumer offset is greater than the last offset in the partition (log end offset).
D. When an offset points to a message that has been removed by compaction but is still within the current partition.offset range.

Answer: D

Explanation:
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.

NEW QUESTION # 37
......

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