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| Certification Vendor: | Confluent |
|---|---|
| Exam Name: | Confluent Certified Developer for Apache Kafka (CCDAK) Certification Exam |
| Exam Number: | CCDAK |
| Related Certifications: | Confluent Certified Administrator for Apache Kafka (CCAK) Confluent Certified Developer for Apache Kafka (CCDAK) |
| Exam Duration: | 90 minutes |
| Real Exam Qty: | 60 |
| Exam Format: | Multiple choice, Multiple select |
| Certificate Validity Period: | 3 years |
| Exam Price: | $150 USD |
| Passing Score: | 70% |
| Available Languages: | English |
| Recommended Training: | Apache Kafka Developer Training (Confluent) Kafka Fundamentals Course |
| Exam Registration: | Confluent Training and Exams Confluent Certification Portal |
| Sample Questions: | Confluent CCDAK Sample Questions |
| Exam Way: | Online proctored exam or authorized testing center |
| Pre Condition: | Basic understanding of Java or another JVM language and familiarity with distributed systems concepts is recommended. |
| Official Syllabus URL: | https://www.confluent.io/certification/ |
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The CCDAK certification exam is a valuable credential for developers who work with Kafka. It not only validates their knowledge and skills but also enhances their career opportunities. The CCDAK certification is recognized by the industry and can help developers stand out in the job market. By investing time and effort in preparing for the CCDAK certification exam, developers can take their Kafka expertise to the next level.
The CCDAK certification program is designed for developers who are looking to improve their skills and knowledge in Kafka development. Confluent Certified Developer for Apache Kafka Certification Examination certification program provides a comprehensive and structured approach to learning Kafka and its related technologies. By passing the CCDAK certification exam, developers can demonstrate their proficiency in Kafka development, which can lead to better job opportunities and higher salaries. The CCDAK Certification program is an excellent way for developers to validate their skills and knowledge in Kafka development, and it is a valuable asset for individuals and organizations that use Kafka for data streaming and processing.
Achieving the CCDAK Certification is a valuable credential for developers who work with Apache Kafka. Confluent Certified Developer for Apache Kafka Certification Examination certification demonstrates a high level of proficiency in working with Kafka and can help developers advance their careers and open up new job opportunities. Additionally, the certification is recognized by industry leaders and demonstrates a commitment to professional development and staying up-to-date with the latest trends and technologies in the field.
NEW QUESTION # 74
A bank uses a Kafka cluster for credit card payments. What should be the value of the property unclean.leader.
election.enable?
Answer: B
Explanation:
Setting unclean.leader.election.enable to true means we allow out-of-sync replicas to become leaders, we will lose messages when this occurs, effectively losing credit card payments and making our customers very angry.
NEW QUESTION # 75
(You need to set alerts on key broker metrics to trigger notifications when a Kafka cluster is unhealthy.
What are three minimum broker metrics to monitor for cluster health?
Select three.)
Answer: A,C,D
Explanation:
The Apache Kafka monitoring and operations documentation highlights several controller-level metrics that are critical indicators of cluster health.
ActiveControllerCount must always be 1 in a healthy cluster. A value of 0 indicates no active controller, while values greater than 1 indicate a serious split-brain condition. This metric is fundamental for cluster stability.
OfflinePartitionsCount is one of the most important health metrics. Any value greater than 0 means that some partitions have no available leader, making them unavailable for producers and consumers. This directly indicates a degraded or unhealthy cluster.
UncleanLeaderElectionsPerSec tracks the rate of unclean leader elections. Unclean elections can cause data loss, and any non-zero value is a strong signal of broker failures or misconfiguration and should immediately trigger alerts.
The remaining options are not minimum health indicators. LastCommittedRecordOffset is not a standard health metric, and TopicsToDeleteCount only indicates pending administrative operations, not cluster instability.
Therefore, the three minimum and officially recommended broker metrics for monitoring Kafka cluster health are UncleanLeaderElectionsPerSec, ActiveControllerCount, and OfflinePartitionsCount.
NEW QUESTION # 76
You create a topic named loT-Data with 10 partitions and replication factor of three.
A producer sends 1 MB messages compressed with Gzip.
Which two statements are true in this scenario?
(Select two.)
Answer: A,B
Explanation:
* A:Kafka batches storecompression metadata in their headers, indicating how the batch was compressed.
* B:Compression is controlled via theproducer config compression.type, which defaults to none.
Producers explicitly set Gzip or other formats.
FromKafka Producer Docs:
"Compression is done by the producer, and the type is stored in the message batch metadata. The broker does not recompress."
* C is false: messages are serializedbeforecompression.
* D is false: messages without keys are distributed acrossmultiple partitions.
Reference:Kafka Producer Configs > compression.type
NEW QUESTION # 77
Select all the way for one consumer to subscribe simultaneously to the following topics - topic.history, topic.
sports, topic.politics? (select two)
Answer: A,C
Explanation:
Multiple topics can be passed as a list or regex pattern.
NEW QUESTION # 78
Which statement is true about how exactly-once semantics (EOS) work in Kafka Streams?
Answer: B
Explanation:
Kafka Streams uses transactional producers to guarantee exactly-once semantics (EOS). This ensures that both the output records and state store updates are committed atomically, avoiding duplication or partial writes.
From Kafka Streams Documentation > Processing Guarantees:
"Kafka Streams leverages Kafka's transactional APIs to commit the output records and internal state updates as a single atomic unit, thereby providing exactly-once semantics." Option A is incorrect because log compaction is not disabled for EOS.
Option C incorrectly describes a checkpointing system Kafka Streams does not use.
Option D refers to deduplication, which is not how EOS is achieved in Streams.
Reference: Kafka Streams Processing Guarantees
NEW QUESTION # 79
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