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Confluent CCDAK Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Kafka Connect | 15% | - Source and sink connectors configuration - Data transformation and integration patterns - Connect architecture: workers, connectors, tasks, converters |
| Topic 2: Apache Kafka Streams | 12% | - Streams API concepts: topology, processors, state stores - Error handling and state management - Windowing and time semantics - Stream processing operations: map, filter, join, aggregation |
| Topic 3: Application Testing | 8% | - Integration testing and test clusters - Unit testing producers and consumers - Mocking and test utilities |
| Topic 4: Application Observability | 13% | - Tracing and performance tuning - Logging and monitoring metrics - Error diagnosis and troubleshooting |
| Topic 5: Apache Kafka Fundamentals | 23% | - Kafka architecture and data flow - Delivery semantics: at-most-once, at-least-once, exactly-once - Configuration basics and cluster setup - Core concepts: brokers, topics, partitions, replicas, offsets |
| Topic 6: Apache Kafka Application Development | 28% | - Transactional messaging and idempotence - Producer API: configuration, serialization, partitioning, error handling - Schema management: Confluent Schema Registry, compatibility rules, evolution - Consumer API: configuration, offset management, consumer groups, rebalancing |
Confluent Certified Developer for Apache Kafka Certification Examination Sample Questions:
1. What is accomplished by producing data to a topic with a message key?
A) Consumers can filter messages in real time based on the message key without processing unrelated messages.
B) It provides a mechanism for encrypting messages at the partition level to ensure secure data transmission.
C) Kafka brokers allow you to add more partitions to a given topic, without impacting the data flow for existing keys.
D) Messages with the same key are routed to a deterministically selected partition, enabling order guarantees within that partition.
2. Match each configuration parameter with the correct deployment step in installing a Kafka connector.
3. Match the topic configuration setting with the reason the setting affects topic durability.
(You are given settings like unclean.leader.election.enable=false, replication.factor, min.insync.replicas=2)
4. You have a consumer group with default configuration settings reading messages from your Kafka cluster.
You need to optimize throughput so the consumer group processes more messages in the same amount of time.
Which change should you make?
A) Disable auto commit and have the consumers manually commit offsets.
B) Increase the number of bytes the consumers read with each fetch request.
C) Decrease the session timeout of each consumer.
D) Remove some consumers from the consumer group.
5. 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 a combination of the bank account number and the transaction timestamp as the message key.
B) Use a unique identifier such as a universally unique identifier (UUID) as the message key.
C) Use the bank account number found in the message as the message key.
D) Use the timestamp of the message's arrival as its key.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: Only visible for members | Question # 3 Answer: Only visible for members | Question # 4 Answer: B | Question # 5 Answer: C |








