CCAAK Vce & CCAAK최고품질덤프샘

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Confluent CCAAK 시험을 한번에 합격할수 없을가봐 두려워 하고 계시나요? 이 글을 보고 계신 분이라면 링크를 클릭하여 저희 사이트를 방문해주세요. 저희 사이트에는Confluent CCAAK 시험의 가장 최신 기출문제와 예상문제를 포함하고 있는 Confluent CCAAK덤프자료를 제공해드립니다.덤프에 있는 문제와 답을 완벽하게 기억하시면 가장 빠른 시일내에 가장 적은 투자로 자격증 취득이 가능합니다.

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Confluent CCAAK 시험요강:

주제	소개
주제 1	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.
주제 2	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.
주제 3	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.
주제 4	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.
주제 5	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.
주제 6	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.

최신 Confluent Certified Administrator CCAAK 무료샘플문제 (Q31-Q36):질문 # 31
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 was updated on source cluster, but the update did not flow into destination DR cluster and errored.
• B. The offsets for the messages on the source, destination cluster may not match.
• C. The message on DR cluster got over-written accidently by another application.
• D. The DR cluster is lagging behind updates; once the DR cluster catches up, the messages will match.
  

정답：B
설명：
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.

질문 # 32
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. 250 GB
• C. 750 GB
• D. 300 GB
  

정답：D
설명：
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.

질문 # 33
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. Use the parameter --partitions=3 when creating the topic.
• C. Set the topic replication factor to 3.
• D. Set 'min.insync.replicas' to 1.
  

정답：C
설명：
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.

질문 # 34
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. If topic deletion is enabled on the brokers, delete the topic using Kafka command line tools.
• B. Delete the offsets for that topic from the consumer offsets topic.
• C. Delete the log files and their corresponding index files from the leader broker.
• D. The consumer should send a message with a 'null' key.
  

정답：A
설명：
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.

질문 # 35
Which statements are correct about partitions? (Choose two.)

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

정답：B,C

질문 # 36
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