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[Hardware] CCAAK Exam Vce Format, CCAAK Exam Voucher

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【Hardware】 CCAAK Exam Vce Format, CCAAK Exam Voucher

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Confluent CCAAK Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 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
  • 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.
Topic 4
  • 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 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
  • 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.

Confluent Certified Administrator for Apache Kafka Sample Questions (Q50-Q55):NEW QUESTION # 50
You have a Kafka cluster with topics t1 and t2. In the output below, topic t2 shows Partition 1 with a leader "-1".
What is the most likely reason for this?
...
$ kafka-topics --zookeeper localhost:2181 --describe --topic t1
Topic:t1 PartitionCount 1 ReplicationFactor 1 Configs:
Topic: t1 Partition: 0 Leader: 0 Replicas: 0 Isr: 0
$ kafka-topics --zookeeper localhost:2181 --describe --topic t2
Topic:t2 PartitionCount 2 ReplicationFactor 1 Configs:
Topic: t2 Partition: 0 Leader: 0 Replicas: 0 Isr: 0
Topic: t2 Partition: 1 Leader: -1 Replicas: 1 Isr:
  • A. Leader shows "-1" while the log cleaner thread runs on Broker 1.
  • B. Compression has been enabled on Broker 1.
  • C. Broker 1 has another partition clashing with the same name.
  • D. Broker 1 failed.
Answer: D
Explanation:
A Leader of -1 indicates that no broker is currently the leader for that partition. This usually happens when the only replica for that partition is unavailable, often due to the associated broker (in this case, Broker 1) failing or being offline. Kafka cannot elect a leader if no replica is in the in-sync replica (ISR) list, which leads to leader = -1.

NEW QUESTION # 51
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. Avro
  • B. gRPC
  • C. Thrift
  • D. Protobuf
  • E. JSON
Answer: A,D,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 # 52
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 # 53
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 offset is less than the smallest offset in the partition (log start offset).
  • B. The Consumer Group started for the first time.
  • C. When an offset points to a message that has been removed by compaction but is still within the current partition.offset range.
  • D. The Consumer offset is greater than the last offset in the partition (log end offset).
Answer: C
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 # 54
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 DR cluster is lagging behind updates; once the DR cluster catches up, the messages will match.
  • B. The offsets for the messages on the source, destination cluster may not match.
  • C. The message was updated on source cluster, but the update did not flow into destination DR cluster and errored.
  • D. The message on DR cluster got over-written accidently by another application.
Answer: B
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 # 55
......
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