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Confluent CCAAK Exam Questions
- Topic 1: Apache Kafka® Fundamentals: This section of the exam measures skills of a Kafka Administrator and covers core concepts such as Kafka architecture, components, and data flow. It assesses the candidate’s understanding of topics like topics and partitions, brokers, producers, consumers, and message retention.
- Topic 2: Apache Kafka® Security: This section of the exam measures skills of a Site Reliability Engineer and focuses on securing Kafka environments. It includes authentication mechanisms such as TLS and SASL, authorization using ACLs, and encrypting data at rest and in transit to ensure secure communication and access control.
- Topic 3: Deployment Architecture: This section of the exam measures skills of a Kafka Administrator and covers different Kafka deployment topologies. It evaluates understanding of high availability, disaster recovery, multi-data center replication, and the roles of Zookeeper or KRaft in the cluster architecture.
- Topic 4: Kafka Connect: This section of the exam measures skills of a Site Reliability Engineer and addresses the use and management of Kafka Connect for data integration. It includes setting up connectors, managing configurations, and ensuring efficient movement of data between Kafka and external systems.
- Topic 5: Apache Kafka® Cluster Configuration: This section of the exam measures skills of a Kafka Administrator and includes configuring broker properties, tuning for performance, managing topic-level settings, and applying best practices for production-grade environments.
- Topic 6: Observability: This section of the exam measures skills of a Site Reliability Engineer and focuses on monitoring Kafka clusters. It assesses knowledge of metrics, logging, and alerting tools, including how to use them to maintain cluster health and performance visibility.
- Topic 7: Troubleshooting: This section of the exam measures skills of a Kafka Administrator and includes diagnosing common issues in Kafka clusters. It covers problem areas such as performance bottlenecks, message delivery failures, replication issues, and consumer lag, along with techniques to resolve them effectively.
Free Confluent CCAAK Exam Actual Questions
Note: Premium Questions for CCAAK were last updated On Jul. 26, 2025 (see below)
Why does Kafka use ZooKeeper? (Choose two.)
ZooKeeper stores metadata such as partition leadership and ISR (in-sync replicas), which brokers use to coordinate.
Kafka uses ZooKeeper to perform leader election for the Controller broker, which manages cluster metadata and leadership changes.
You have a cluster with a topic t1 that already has uncompressed messages. A new Producer starts sending messages to t1 with compression enabled.
Which condition would allow this?
Kafka allows mixed compression formats within the same topic and even the same partition. Each message batch includes metadata indicating whether and how it is compressed. Therefore, a new producer can send compressed messages to a topic that already contains uncompressed messages, as long as it is configured with a compression codec (e.g., compression.type=gzip, snappy, etc.).
Why does Kafka use ZooKeeper? (Choose two.)
ZooKeeper stores metadata such as partition leadership and ISR (in-sync replicas), which brokers use to coordinate.
Kafka uses ZooKeeper to perform leader election for the Controller broker, which manages cluster metadata and leadership changes.
Which property in broker configuration specifies that a broker belongs to a particular rack?
Which property in broker configuration specifies that a broker belongs to a particular rack?
The broker.rack property is used in a Kafka broker's configuration to specify the rack or availability zone the broker belongs to. This is important for rack-aware replica placement, allowing Kafka to distribute replicas across different racks for fault tolerance.
Your Kafka cluster has four brokers. The topic t1 on the cluster has two partitions, and it has a replication factor of three. You create a Consumer Group with four consumers, which subscribes to t1.
In the scenario above, how many Controllers are in the Kafka cluster?
In a Kafka cluster, only one broker acts as the Controller at any given time. The Controller is responsible for managing cluster metadata, such as partition leadership and broker status. Even if the cluster has multiple brokers (in this case, four), only one is elected as the Controller, and others serve as regular brokers. If the current Controller fails, another broker is automatically elected to take its place.
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