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The Confluent Certified Developer for Apache Kafka Certification Examination certification is an opportunity for developers to demonstrate their understanding of Kafka and its ecosystem components, as well as their hands-on experience in building Kafka-based applications. Confluent Certified Developer for Apache Kafka Certification Examination certification exam validates the candidate's Kafka knowledge, skillset, and ability to develop solutions that solve real-world Kafka use cases. Moreover, the CCDAK certification is recognized worldwide, making it a valuable credential that can help software developers secure their next Kafka development role.
Confluent CCDAK Certification Exam covers a range of topics, including Kafka core concepts, producers and consumers, Kafka Streams, Kafka Connect, and security. CCDAK exam is designed to test a developer's understanding of Kafka architecture and best practices for building scalable and reliable Kafka applications. CCDAK exam is conducted online and consists of 60 multiple-choice questions that need to be answered in 90 minutes.
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Confluent Certified Developer for Apache Kafka (CCDAK) Certification Exam is a hands-on exam that tests developers' ability to work with Kafka and Confluent's platform. CCDAK exam covers a wide range of topics related to Kafka and Confluent's tools, and passing the exam demonstrates a developer's ability to work with Kafka and Confluent's platform at a high level. The CCDAK Certification Exam is an important certification for developers who want to work with Kafka and Confluent's platform, and it can help advance their careers and increase their earning potential.
NEW QUESTION # 66
(You started a new Kafka Connect worker.
Which configuration identifies the Kafka Connect cluster that your worker will join?)
Answer: A
Explanation:
As documented in the official Apache Kafka Connect framework documentation, Kafka Connect workers form a logical cluster by using a Kafka consumer group. The configuration property that identifies this cluster is group.id.
All Kafka Connect workers configured with the same group.id automatically join the same Connect cluster.
Kafka's group coordination protocol is then used to distribute connector and task configurations among the workers, providing fault tolerance, scalability, and automatic rebalancing.
Option A (cluster.id) is a Kafka internal identifier used by brokers and is not configurable for Kafka Connect workers. Option B (worker.id) does not exist as a valid Kafka Connect configuration. Option D (connector.id) identifies individual connectors within a Connect cluster, not the worker cluster itself.
Therefore, the group.id property is the correct and officially documented configuration that determines which Kafka Connect cluster a worker belongs to.
NEW QUESTION # 67
To produce data to a topic, a producer must provide the Kafka client with...
Answer: A
Explanation:
All brokers can respond to a Metadata request, so a client can connect to any broker in the cluster and then figure out on its own which brokers to send data to.
NEW QUESTION # 68
(You want to read messages from all partitions of a topic in every consumer instance of your application.
How do you do this?)
Answer: A
Explanation:
According to the Apache Kafka Consumer API documentation, the assign() method allows a consumer to manually assign specific partitions to itself, bypassing Kafka's consumer group coordination and rebalancing mechanism. When a consumer uses assign() with all partitions of a topic, that consumer will read from every partition, regardless of how many other consumers exist.
This behavior is required when every consumer instance must independently read the full dataset, such as in auditing, monitoring, or replication use cases. In contrast, subscribe() is designed for consumer group usage, where partitions are distributed among consumers, ensuring that each partition is consumed by only one consumer in the group.
Option B is invalid because assign() requires a collection of TopicPartition objects, not just a topic name.
Option C still uses group coordination and does not guarantee all partitions per consumer. Option D is invalid because an empty group ID is not supported by Kafka.
Thus, explicitly calling assign() with all topic partitions is the only correct and documented way to ensure each consumer reads from all partitions.
NEW QUESTION # 69
What are the requirements for a Kafka broker to connect to a Zookeeper ensemble? (select two)
Answer: B,D
Explanation:
Each broker must have a unique broker id and connect to the same zk ensemble and root zNode
NEW QUESTION # 70
Select all that applies (select THREE)
Answer: A,C,F
Explanation:
acks is a producer setting min.insync.replicas is a topic or broker setting and is only effective when acks=all
NEW QUESTION # 71
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