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Confluent Certified Developer for Apache Kafka (CCDAK) Certification Exam is a rigorous certification program designed for developers who are interested in validating their skills and understanding of Apache Kafka. Confluent Certified Developer for Apache Kafka Certification Examination certification program is offered by Confluent, a leading data streaming platform that provides enterprise-grade solutions for managing and processing data in real-time. The CCDAK certification program is designed to measure a developer's proficiency in Kafka development and ensures that they have the necessary skills to build and maintain Kafka-based applications.

The CCDAK Certification Exam is a computer-based exam that consists of 60 multiple-choice questions. CCDAK exam is timed and lasts for 90 minutes. The passing score for the exam is 70%, meaning that candidates need to answer at least 42 questions correctly to pass the exam. CCDAK exam can be taken online or at a certified testing center.

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The CCDAK exam is a comprehensive assessment of a developer's knowledge of the Kafka ecosystem and its various components, such as Kafka Connect, Kafka Streams, and Schema Registry. CCDAK exam covers a broad range of topics, including Kafka architecture, data modeling, event-driven design, and security. Developers who pass the CCDAK exam will have demonstrated their ability to develop Kafka-based applications that are scalable, reliable, and secure, and they will be recognized as experts in the Kafka ecosystem. The CCDAK Certification is an essential credential for developers who wish to work with Kafka and Confluent's platform and is highly valued by organizations that use Kafka as their messaging and streaming platform.

Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q90-Q95):

NEW QUESTION # 90
You want to connect with username and password to a secured Kafka cluster that has SSL encryption.
Which properties must your client include?

A. security.protocol=SASL_SSL
sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username='myUser' password='myPassword';
B. security.protocol=SSL
sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username='myUser' password='myPassword';
C. security.protocol=PLAINTEXT
sasl.jaas.config=org.apache.kafka.common.security.ssl.TlsLoginModule required username='myUser' password='myPassword';
D. security.protocol=SASL_PLAINTEXT
sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username='myUser' password='myPassword';

Answer: A

Explanation:
ForSASL/PLAIN authentication over SSL, the correct combination is:
* security.protocol=SASL_SSL
* sasl.jaas.config=...PlainLoginModule required username=... password=...
FromKafka Security Documentation:
"For SASL/PLAIN over SSL, configure security.protocol=SASL_SSL and provide login module configuration using sasl.jaas.config." Options B and D are incorrect because they do not pair the correct protocol with the authentication method.
Reference:Apache Kafka Security Configs > SASL_SSL, PLAIN mechanism

NEW QUESTION # 91
Your producer is producing at a very high rate and the batches are completely full each time. How can you improve the producer throughput? (select two)

A. Increase batch.size
B. Decrease batch.size
C. Enable compression
D. Disable compression
E. Decrease linger.ms
F. Increase linger.ms

Answer: A,C

Explanation:
batch.size controls how many bytes of data to collect before sending messages to the Kafka broker. Set this as high as possible, without exceeding available memory. Enabling compression can also help make more compact batches and increase the throughput of your producer. Linger.ms will have no effect as the batches are already full

NEW QUESTION # 92
You create a producer that writes messages about bank account transactions from tens of thousands of different customers into a topic.
Your consumers must process these messages with low latency and minimize consumer lag Processing takes ~6x longer than producing Transactions for each bank account must be processed in orderWhich strategy should you use?

A. Use the timestamp of the message's arrival as its key.
B. Use a combination of the bank account number and the transaction timestamp as the message key.
C. Use a unique identifier such as a universally unique identifier (UUID) as the message key.
D. Use the bank account number found in the message as the message key.

Answer: D

Explanation:
To maintain message ordering per bank account, the message key must be the account number. Kafka guarantees ordering per partition, and the partition is selected based on the hash of the key.
From Kafka Producer Docs:
"All records with the same key will be sent to the same partition, and Kafka preserves the order of records in a partition." Using account number ensures:
All messages for the same account go to the same partition
Order is maintained
Workload is evenly distributed if account keys are varied
Other options break ordering or introduce unnecessary randomness.
Reference: Kafka Producer Concepts > Partitions and Keys

NEW QUESTION # 93
Which actions will trigger partition rebalance for a consumer group? (select three)

A. Increase partitions of a topic
B. Remove a broker from the cluster
C. A consumer in a consumer group shuts down
D. Add a new consumer to consumer group
E. Add a broker to the cluster

Answer: A,C,D

Explanation:
Rebalance occurs when a new consumer is added, removed or consumer dies or paritions increased.

NEW QUESTION # 94
An ecommerce wesbite sells some custom made goods. What's the natural way of modeling this data in Kafka streams?

A. Purchase as stream, Product as stream, Customer as stream
B. Purchase as table, Product as table, Customer as table
C. Purchase as stream, Product as table, Customer as table
D. Purchase as stream, Product as table, Customer as stream

Answer: C

Explanation:
Mostly-static data is modeled as a table whereas business transactions should be modeled as a stream.

NEW QUESTION # 95
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