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Confluent CCAAK Exam Syllabus Topics:

Topic
Details

Topic 1

Apache Kafka® Fundamentals: This section of the exam measures skills of a Kafka Administrator and covers core concepts such as Kafka architecture, components, and data flow. It assesses the candidate’s understanding of topics like topics and partitions, brokers, producers, consumers, and message retention.

Topic 2

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 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

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

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 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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CCAAK Test Questions - CCAAK Latest Dumps Files

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Confluent Certified Administrator for Apache Kafka Sample Questions (Q27-Q32):

NEW QUESTION # 27
A developer is working for a company with internal best practices that dictate that there is no single point of failure for all data stored.
What is the best approach to make sure the developer is complying with this best practice when creating Kafka topics?

A. Set 'min.insync.replicas' to 1.
B. Set the topic replication factor to 3.
C. Use the parameter --partitions=3 when creating the topic.
D. Make sure the topics are created with linger.ms=0 so data is written immediately and not held in batch.

Answer: B

Explanation:
Replication factor determines how many copies of each partition exist across different brokers. A replication factor of 3 ensures that even if one or two brokers fail, the data is still available, thus eliminating a single point of failure.

NEW QUESTION # 28
Where are Apache Kafka Access Control Lists stored'?

A. ZooKeeper
B. Connect
C. Schema Registry
D. Broker

Answer: A

Explanation:
In Apache Kafka (open-source), Access Control Lists (ACLs) are stored in ZooKeeper. Kafka brokers retrieve and enforce ACLs from ZooKeeper at runtime.

NEW QUESTION # 29
Why does Kafka use ZooKeeper? (Choose two.)

A. To prevent replication between clusters
B. To scale the number of brokers in the cluster
C. For controller election
D. To access information about the leaders and partitions

Answer: C,D

Explanation:
ZooKeeper stores metadata such as partition leadership and ISR (in-sync replicas), which brokers use to coordinate.
Kafka uses ZooKeeper to perform leader election for the Controller broker, which manages cluster metadata and leadership changes.

NEW QUESTION # 30
How does Kafka guarantee message integrity after a message is written on a disk?

A. Only message metadata can be altered using command line (CLI) tools.
B. A message can be edited by the producer, producing to the message offset.
C. 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

Answer: C

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 # 31
When a broker goes down, what will the Controller do?

A. Trigger a leader election among the remaining followers to distribute leadership.
B. Become the leader for the topic/partition that needs a leader, pending the broker return in the cluster.
C. Wait for a follower to take the lead.
D. Automatically elect the least loaded broker to become the leader for every orphan's partitions.

Answer: A

Explanation:
When a broker goes down, the Controller detects the failure and triggers a leader election for all partitions that had their leader on the failed broker. The leader is chosen from the in-sync replicas (ISRs) of each partition.

NEW QUESTION # 32
......

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