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Confluent CCDAK Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Security	5-10%	- Securing Schema Registry - Encryption in Transit - Authentication (SASL, SSL/TLS) - Authorization (ACLs)
Topic 2: Monitoring and Operations	5-10%	- Log Compaction - Disaster Recovery - Consumer Lag and Health Checks - Cross-region Replication - Kafka Metrics and Monitoring
Topic 3: Kafka Streams	20-25%	- Windowed Operations (Tumbling, Hopping, Session) - Transformation Operations (map, filter, join, aggregate) - State Stores and Processors - Interactive Queries - Streams Architecture and Topology - Testing Kafka Streams Applications - Exactly-Once Processing
Topic 4: Schema Management	5-10%	- Protobuf and JSON Schemas - Schema Evolution and Compatibility - Schema Registry Architecture - Schema Registration and Retrieval - Avro Schemas
Topic 5: Developing with Kafka Consumers	15-20%	- Consumer Interceptors - Consumer Configuration and Tuning - Consumer Groups and Rebalancing - Multi-threaded Consumers - Deserialization - Commit Strategies (Auto, Manual, Cooperative) - Offset Management
Topic 6: Kafka Fundamentals	10-15%	- Log Segments and Retention - Producer and Consumer Basics - Replication Factor and ISR - Topics, Partitions, and Offsets - Brokers and Clusters
Topic 7: Kafka Connect	10-15%	- Source and Sink Connectors - Connect Architecture (Workers, Connectors, Tasks) - Offset Management in Connect - Single Message Transformations (SMT) - Converters and Transforms - Connector Configuration
Topic 8: Installing and Configuring Kafka	5-10%	- Broker Configuration Parameters - Partition Assignment Strategies - ZooKeeper vs KRaft Mode - Topic Creation and Configuration
Topic 9: Developing with Kafka Producers	15-20%	- Idempotent Producers - Partitioning Strategies - Producer Configuration and Tuning - Serialization (JSON, Avro, Protobuf) - Exactly-Once Semantics - Error Handling and Retry Logic - Producer Interceptors

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Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions (Q10-Q15):

NEW QUESTION # 10
Which configuration determines how many bytes of data are collected before sending messages to the Kafka broker?

A. max.block.size
B. buffer.memory
C. batch.size
D. send.buffer.bytes

Answer: C

Explanation:
Thebatch.sizeconfig sets themaximum number of bytes to batch per partitionbefore sending. This allows Kafka producers toamortize I/Oand improve throughput.
FromKafka Producer Configuration Docs:
"batch.size is the maximum amount of data per partition the producer will batch before sending."
* buffer.memory sets total memory for the producer, not per-batch.
* send.buffer.bytes is aTCP socket buffer, not a Kafka config.
* max.block.ms controls blocking time, not size.
Reference:Kafka Producer Configs > batch.size

NEW QUESTION # 11
What information isn't stored inside of Zookeeper? (select two)

A. Schema Registry schemas
B. Controller registration
C. Consumer offset
D. Broker registration info
E. ACL inforomation

Answer: C

Explanation:
Consumer offsets are stored in a Kafka topic __consumer_offsets, and the Schema Registry stored schemas in the _schemas topic.

NEW QUESTION # 12
(You are configuring a source connector that writes records to an Orders topic.
You need to send some of the records to a different topic.
Which Single Message Transform (SMT) is best suited for this requirement?)

A. HeaderFrom
B. InsertField
C. TombstoneHandler
D. RegexRouter

Answer: D

Explanation:
According to the official Apache Kafka Connect documentation, RegexRouter is the SMT specifically designed to dynamically change the destination topic name of records produced by a connector. It works by applying a regular expression to the original topic name and rewriting it to a new topic name.
This makes RegexRouter the correct choice when some records must be routed to a different topic, typically in combination with connector-level logic, predicates, or multiple connectors. It is commonly used for topic renaming, topic versioning, or routing records to alternate topics.
InsertField (Option B) only adds metadata fields (such as topic, partition, or timestamp) to the record payload and does not affect routing. TombstoneHandler (Option C) is used to manage null-value records, especially with compacted topics. HeaderFrom (Option D) copies fields into headers but does not change the target topic.
Therefore, RegexRouter is the only SMT that directly supports changing the output topic, as documented in the Kafka Connect SMT reference.

NEW QUESTION # 13
What is the function of Kafka Connect Converters?

A. Serialize data written to and deserialize data read from Kafka topics.
B. Isolate the producer and consumer work from the source and sink connectors.
C. Make simple updates to data as it is written to and read from Kafka topics.
D. Convert data from the structure used by the source system to the standard Connect structure.

Answer: A

NEW QUESTION # 14
To produce data to a topic, a producer must provide the Kafka client with...

A. all the brokers from the cluster and the topic name
B. any broker from the cluster and the topic name
C. the list of brokers that have the data, the topic name and the partitions list
D. any broker from the cluster and the topic name and the partitions list

Answer: B

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 # 15
......

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