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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	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	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.

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Confluent Certified Administrator for Apache Kafka Sample Questions (Q38-Q43):

NEW QUESTION # 38
Which out-of-the-box Kafka Authorizer implementation uses ZooKeeper?

A. RBAC
B. LDAP
C. ACLs
D. Ranger

Answer: C

Explanation:
Kafka's built-in ACL (Access Control List) authorizer stores and manages permissions using ZooKeeper by default. This implementation controls access at the resource level (topics, consumer groups, etc.).

NEW QUESTION # 39
Which use cases would benefit most from continuous event stream processing? (Choose three.)

A. Historical dashboards
B. Fraud detection
C. Context-aware product recommendations for e-commerce
D. Log monitoring/application fault detection
E. End-of-day financial settlement processing

Answer: B,C,D

Explanation:
Real-time analysis of transactions helps detect suspicious activity instantly.
Context-aware product recommendations for e-commerce requires real-time user behavior tracking to serve personalized recommendations.
Log monitoring/application fault detection needs immediate processing to alert on system issues or failures.

NEW QUESTION # 40
Your organization has a mission-critical Kafka cluster that must be highly available. A Disaster Recovery (DR) cluster has been set up using Replicator, and data is continuously being replicated from source cluster to the DR cluster. However, you notice that the message on offset 1002 on source cluster does not seem to match with offset 1002 on the destination DR cluster.
Which statement is correct?

A. The offsets for the messages on the source, destination cluster may not match.
B. The DR cluster is lagging behind updates; once the DR cluster catches up, the messages will match.
C. The message on DR cluster got over-written accidently by another application.
D. The message was updated on source cluster, but the update did not flow into destination DR cluster and errored.

Answer: A

Explanation:
When using Confluent Replicator (or MirrorMaker), offsets are not preserved between the source and destination Kafka clusters. Messages are replicated based on content, but they are assigned new offsets in the DR (destination) cluster. Therefore, offset 1002 on the source and offset 1002 on the DR cluster likely refer to different messages, which is expected behavior.

NEW QUESTION # 41
A company is setting up a log ingestion use case where they will consume logs from numerous systems. The company wants to tune Kafka for the utmost throughput.
In this scenario, what acknowledgment setting makes the most sense?

A. acks=undefined
B. acks=all
C. acks=1
D. acks=0

Answer: D

Explanation:
acks=0 provides the highest throughput because the producer does not wait for any acknowledgment from the broker. This minimizes latency and maximizes performance.
However, it comes at the cost of no durability guarantees - messages may be lost if the broker fails before writing them. This setting is suitable when throughput is critical and occasional data loss is acceptable, such as in some log ingestion use cases where logs are also stored elsewhere.

NEW QUESTION # 42
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 # 43
......

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Free Confluent CCAAK Exam Questions updates for up to 365 days

Confluent CCAAK Exam Syllabus Topics:

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Confluent Certified Administrator for Apache Kafka Sample Questions (Q38-Q43):

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