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Confluent CCDAK Exam Questions
- Topic 1: Apache Kafka® Fundamentals: This section of the exam measures the skills of a Kafka Developer and covers the essential concepts required to work effectively with Kafka. It includes understanding how Kafka operates under the hood, including its architecture, brokers, topics, partitions, replication, producers, and consumers. A strong grasp of Kafka fundamentals is necessary to build scalable, fault-tolerant applications, and this section ensures the developer can configure and manage these components properly.
- Topic 2: Apache Kafka® Application Development: This section of the exam assesses a Data Engineer's ability to build applications using Kafka APIs. It focuses on the development of producer and consumer applications, the use of Kafka client libraries, and how to properly handle serialization and deserialization. Candidates are expected to know how to write code that interacts efficiently with Kafka, manage offset commits, and ensure message reliability and ordering within their applications.
- Topic 3: Apache Kafka® Streams: This section of the exam measures the skills of a Kafka Developer and focuses on using Kafka Streams to build real-time, event-driven applications. It includes the basics of stream processing, such as stateless and stateful transformations, windowing, joins, and interactive queries. Developers need to demonstrate the ability to use Kafka Streams to process and analyze data in motion with scalability and fault tolerance in mind.
- Topic 4: Kafka Connect: This part evaluates the Data Engineer's ability to use Kafka Connect for integrating external systems with Kafka. It covers both source and sink connectors, configuration of connectors, and the management of data pipelines between Kafka and various data systems like databases, cloud storage, or file systems. Engineers are expected to show an understanding of how Kafka Connect simplifies large-scale data ingestion and export tasks.
- Topic 5: Application Testing: This section of the exam tests a Kafka Developer’s knowledge of testing Kafka-based applications. It includes techniques for unit testing, integration testing, and mocking Kafka for development environments. Candidates should be familiar with best practices for ensuring application correctness and stability when interacting with Kafka systems.
- Topic 6: Application Observability: This section measures the skills of a Data Engineer in observing and maintaining Kafka-based applications. It focuses on the use of logging, metrics, and tracing to monitor system behavior and performance. Engineers are expected to understand how to troubleshoot Kafka clients and identify issues related to throughput, latency, and resource utilization using appropriate observability tools and practices.
Free Confluent CCDAK Exam Actual Questions
Note: Premium Questions for CCDAK were last updated On Jun. 29, 2025 (see below)
What are the requirements for a Kafka broker to connect to a Zookeeper ensemble? (select two)
Each broker must have a unique broker id and connect to the same zk ensemble and root zNode
Where are KSQL-related data and metadata stored?
metadata is stored in and built from the KSQL command topic. Each KSQL server has its own in-memory version of the metastore.
Suppose you have 6 brokers and you decide to create a topic with 10 partitions and a replication factor of 3. The brokers 0 and 1 are on rack A, the brokers 2 and 3 are on rack B, and the brokers 4 and 5 are on rack C. If the leader for partition 0 is on broker 4, and the first replica is on broker 2, which broker can host the last replica? (select two)
When you create a new topic, partitions replicas are spreads across racks to maintain availability. Hence, the Rack A, which currently does not hold the topic partition, will be selected for the last replica
What is the risk of increasing max.in.flight.requests.per.connection while also enabling retries in a producer?
Some messages may require multiple retries. If there are more than 1 requests in flight, it may result in messages received out of order. Note an exception to this rule is if you enable the producer settingenable.idempotence=true which takes care of the out of ordering case on its own. Seehttps://issues.apache.org/jira/browse/KAFKA-5494
Select the Kafka Streams joins that are always windowed joins.
Seehttps://docs.confluent.io/current/streams/developer-guide/dsl-api.html#joining
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