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【General】 Providing You High Hit Rate Online CCAAK Training Materials with 100% Passing Gu

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Confluent CCAAK Exam Syllabus Topics:
TopicDetails
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
  • 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 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
  • 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 5
  • 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 6
  • 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.

Confluent Certified Administrator for Apache Kafka Sample Questions (Q50-Q55):NEW QUESTION # 50
You want to increase Producer throughput for the messages it sends to your Kafka cluster by tuning the batch size ('batch size') and the time the Producer waits before sending a batch ('linger.ms').
According to best practices, what should you do?
  • A. Decrease 'batch.size' and decrease 'linger.ms'
  • B. Increase 'batch.size' and decrease 'linger.ms'
  • C. Decrease 'batch.size' and increase 'linger.ms'
  • D. Increase 'batch.size' and increase 'linger.ms'
Answer: D
Explanation:
Increasing batch.size allows the producer to accumulate more messages into a single batch, improving compression and reducing the number of requests sent to the broker.
Increasing linger.ms gives the producer more time to fill up batches before sending them, which improves batching efficiency and throughput.
This combination is a best practice for maximizing throughput, especially when message volume is high or consistent latency is not a strict requirement.

NEW QUESTION # 51
What is the primary purpose of Kafka quotas?
  • A. Limit the number of clients that can connect to the Kafka cluster.
  • B. Limit the total number of Partitions in the Kafka cluster
  • C. Guarantee faster response times for some clients.
  • D. Throttle clients to prevent them from monopolizing Broker resources.
Answer: D
Explanation:
Kafka quotas are used to limit the throughput (bytes/sec) of producers and consumers to ensure fair resource usage and prevent any single client from overwhelming the brokers.

NEW QUESTION # 52
You have a cluster with a topic t1 that already has uncompressed messages. A new Producer starts sending messages to t1 with compression enabled.
Which condition would allow this?
  • A. Only if Kafka is also enabled for encryption.
  • B. Never, because topic t1 already has uncompressed messages.
  • C. Only if the new Producer disables batching.
  • D. If the new Producer is configured to use compression.
Answer: D
Explanation:
Kafka allows mixed compression formats within the same topic and even the same partition. Each message batch includes metadata indicating whether and how it is compressed. Therefore, a new producer can send compressed messages to a topic that already contains uncompressed messages, as long as it is configured with a compression codec (e.g., compression.type=gzip, snappy, etc.).

NEW QUESTION # 53
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. The consumer should send a message with a 'null' key.
  • B. Delete the log files and their corresponding index files from the leader broker.
  • C. If topic deletion is enabled on the brokers, delete the topic using Kafka command line tools.
  • D. Delete the offsets for that topic from the consumer offsets topic.
Answer: C
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 # 54
Why does Kafka use ZooKeeper? (Choose two.)
  • A. To prevent replication between clusters
  • B. To scale the number of brokers in the cluster
  • C. To access information about the leaders and partitions
  • D. For controller election
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 # 55
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