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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	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	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.

Confluent Certified Administrator for Apache Kafka Sample Questions (Q35-Q40):

NEW QUESTION # 35
A company has an existing Kafka cluster running without SSL/TLS enabled. The customer wants to enable SSL on brokers to secure data in transit, but they would like to give applications connecting to this cluster some time to migrate to using SSL connection instead of putting a hard stop.
Which solution will meet the customer's requirements?

A. Create a new listener with SSL enabled.
B. Enable SSL on the current Listener, and do not enable mTLS.
C. Modify the advertised listeners setting on brokers to use SSL.
D. Enable SSL on the current listener, and do not implement SSL on application side.

Answer: A

Explanation:
Kafka supports multiple listeners, allowing you to run PLAINTEXT and SSL simultaneously. By creating a new SSL-enabled listener (e.g., on a different port), existing applications can continue using PLAINTEXT while gradually migrating to the SSL listener. This approach avoids downtime and gives clients time to adapt without enforcing a hard cutover.

NEW QUESTION # 36
If the Controller detects the failure of a broker that was the leader for some partitions, which actions will be taken? (Choose two.)

A. The Controller sends the new leader and ISR list changes to all producers and consumers.
B. The Controller sends the new leader and ISR list changes to all brokers.
C. The Controller waits for a new leader to be nominated by ZooKeeper.
D. The Controller persists the new leader and ISR list to ZooKeeper.

Answer: B,D

Explanation:
The Controller updates ZooKeeper with the new leader and in-sync replica (ISR) information to maintain metadata consistency.
Brokers need this information to correctly route client requests and continue replication.

NEW QUESTION # 37
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. Make sure the topics are created with linger.ms=0 so data is written immediately and not held in batch.
B. Set 'min.insync.replicas' to 1.
C. Use the parameter --partitions=3 when creating the topic.
D. Set the topic replication factor to 3.

Answer: D

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 # 38
A Kafka cluster with three brokers has a topic with 10 partitions and a replication factor set to three. Each partition stores 25 GB data per day and data retention is set to 24 hours.
How much storage will be consumed by the topic on each broker?

A. 75 GB
B. 300 GB
C. 750 GB
D. 250 GB

Answer: B

Explanation:
10 partitions × 25 GB/day = 250 GB total per day for the topic (primary data).
With a replication factor of 3, there are 3 full copies of the data: 250 GB × 3 = 750 GB total across the entire cluster.
The cluster has 3 brokers, and Kafka tries to distribute replicas evenly among them: 750 GB ÷ 3 brokers = 250 GB per broker on average.
However, due to replication, some partitions have leaders and followers, so there's some overlap and not-perfect distribution. Each broker stores approximately 2/3 of the total topic data (since each broker holds replicas for around 2/3 of the partitions).
2/3 × 750 GB = 500 GB, but this is shared, so each broker ends up storing ~300 GB of replicated data, including its share of leaders and followers.

NEW QUESTION # 39
You have an existing topic t1 that you want to delete because there are no more producers writing to it or consumers reading from it.
What is the recommended way to delete the topic?

A. Delete the offsets for that topic from the consumer offsets topic.
B. The consumer should send a message with a 'null' key.
C. Delete the log files and their corresponding index files from the leader broker.
D. If topic deletion is enabled on the brokers, delete the topic using Kafka command line tools.

Answer: D

Explanation:
The recommended and safe method to delete a topic is to use the Kafka CLI tool kafka-topics.sh --delete command, provided that delete.topic.enable=true is set on the brokers.

NEW QUESTION # 40
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