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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Monitoring and Operations | 5-10% | - Disaster Recovery - Cross-region Replication - Kafka Metrics and Monitoring - Log Compaction - Consumer Lag and Health Checks |
| Schema Management | 5-10% | - Schema Registration and Retrieval - Avro Schemas - Protobuf and JSON Schemas - Schema Evolution and Compatibility - Schema Registry Architecture |
| Kafka Connect | 10-15% | - Connect Architecture (Workers, Connectors, Tasks) - Source and Sink Connectors - Converters and Transforms - Connector Configuration - Offset Management in Connect - Single Message Transformations (SMT) |
| Installing and Configuring Kafka | 5-10% | - Topic Creation and Configuration - ZooKeeper vs KRaft Mode - Broker Configuration Parameters - Partition Assignment Strategies |
| Kafka Fundamentals | 10-15% | - Log Segments and Retention - Brokers and Clusters - Producer and Consumer Basics - Replication Factor and ISR - Topics, Partitions, and Offsets |
| Developing with Kafka Consumers | 15-20% | - Consumer Groups and Rebalancing - Commit Strategies (Auto, Manual, Cooperative) - Offset Management - Multi-threaded Consumers - Consumer Configuration and Tuning - Consumer Interceptors - Deserialization |
| Developing with Kafka Producers | 15-20% | - Producer Interceptors - Producer Configuration and Tuning - Partitioning Strategies - Exactly-Once Semantics - Idempotent Producers - Serialization (JSON, Avro, Protobuf) - Error Handling and Retry Logic |
| Security | 5-10% | - Authorization (ACLs) - Authentication (SASL, SSL/TLS) - Securing Schema Registry - Encryption in Transit |
| Kafka Streams | 20-25% | - Transformation Operations (map, filter, join, aggregate) - Windowed Operations (Tumbling, Hopping, Session) - Exactly-Once Processing - Interactive Queries - Testing Kafka Streams Applications - Streams Architecture and Topology - State Stores and Processors |
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:
1. Which configuration determines how many bytes of data are collected before sending messages to the Kafka broker?
A) max.block.size
B) batch.size
C) send.buffer.bytes
D) buffer.memory
2. (You started a new Kafka Connect worker.
Which configuration identifies the Kafka Connect cluster that your worker will join?)
A) cluster.id
B) worker.id
C) group.id
D) connector.id
3. Your application is consuming from a topic with one consumer group.
The number of running consumers is equal to the number of partitions.
Application logs show that some consumers are leaving the consumer group during peak time, triggering a rebalance. You also notice that your application is processing many duplicates.
You need to stop consumers from leaving the consumer group.
What should you do?
A) Add more consumer instances.
B) Increase session.timeout.ms property.
C) Reduce max.poll.records property.
D) Split consumers in different consumer groups.
4. (You create an Orders topic with 10 partitions.
The topic receives data at high velocity.
Your Kafka Streams application initially runs on a server with four CPU threads.
You move the application to another server with 10 CPU threads to improve performance.
What does this example describe?)
A) Horizontal Scaling
B) Plain Scaling
C) Vertical Scaling
D) Scaling Out
5. (You create a topic with five partitions.
What can you assume about messages read from that topic by a single consumer group?)
A) All messages will be read from exactly one broker by the consumer group.
B) The consumer group can only read the same number of messages from all the partitions.
C) Messages from one partition can be consumed by any of the consumers in a group for faster processing.
D) Messages can be consumed by a maximum of five consumers in the same consumer group.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: D |
