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CCAAK Free Vce Dumps, Pass CCAAK Rate

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CCAAK Study Materials: Confluent Certified Administrator for Apache Kafka & CCAAK Certification Training

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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

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 3

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 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

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.

Confluent Certified Administrator for Apache Kafka Sample Questions (Q32-Q37):

NEW QUESTION # 32
What is the relationship between topics and partitions? (Choose two.)

A. Atopic may have more than one partition.
B. There is no relationship between topics and partitions.
C. A partition is always linked to a single topic.
D. Atopic always has one partition.
E. A partition may have more than one topic.

Answer: A,C

Explanation:
Kafka topics are split into one or more partitions to enable parallelism and scalability.
Each partition belongs to exactly one topic; it cannot span multiple topics.

NEW QUESTION # 33
How can load balancing of Kafka clients across multiple brokers be accomplished?

A. Connectors
B. Replicas
C. Offsets
D. Partitions

Answer: D

Explanation:
Partitions are the primary mechanism for achieving load balancing in Kafka. When a topic has multiple partitions, Kafka clients (producers and consumers) can distribute the load across brokers hosting these partitions.

NEW QUESTION # 34
Which statements are correct about partitions? (Choose two.)

A. A partition size is determined after the largest segment on a disk.
B. A partition is comprised of one or more segments on a disk.
C. A partition in Kafka will be represented by a single segment on a disk.
D. All partition segments reside in a single directory on a broker disk.

Answer: B,D

NEW QUESTION # 35
Which model does Kafka use for consumers?

A. Push
B. Pull
C. Enrollment
D. Publish

Answer: B

Explanation:
Kafka uses a pull model for consumers, where consumers poll the broker to retrieve messages at their own pace. This model gives consumers more control over flow and backpressure, improving scalability and reliability.

NEW QUESTION # 36
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 message on DR cluster got over-written accidently by another application.
B. The message was updated on source cluster, but the update did not flow into destination DR cluster and errored.
C. The DR cluster is lagging behind updates; once the DR cluster catches up, the messages will match.
D. The offsets for the messages on the source, destination cluster may not match.

Answer: D

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 # 37
......

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