CCAAK Sample Questions

CCAAK Sample Questions & Answers

Broker, producer and consumer cluster configuration carries the most weight, alongside Kafka's core components built on ZooKeeper or KRaft, monitoring metrics, authorization paired with authentication, Kafka Connect, and deployment for high availability.

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Showing 10 of 20 free samples.

  1. Question 1Intermediate

    Kafka Connect · Understanding fault tolerance and rebalancing in Kafka Connect.

    An administrator is setting up a Kafka Connect cluster in distributed mode to sink data from a Kafka topic to a database. To ensure high availability and fault tolerance, how does the Connect cluster handle a worker node failure?

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    Correct answer: C

    When a worker in a distributed Kafka Connect cluster fails or leaves the group, the group coordinator triggers a rebalance. During this rebalance, all tasks from the failed worker (and potentially other workers) are redistributed among the surviving members of the cluster, ensuring that data processing continues with minimal interruption.

  2. Question 2Intermediate

    Apache Kafka Security · Configuring prefixed ACLs for resource access control.

    You are designing a security policy for a multi-tenant Kafka cluster. You need to grant a team, represented by the user principal user:data-science, the ability to consume from any topic prefixed with ds-, but prevent them from consuming from any other topics. Which ACL entry correctly implements this policy?

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    Correct answer: C

    This is the correct command. It specifies the operation (Read), the principal (user:data-science), the resource name (ds-), and crucially, sets the --resource-pattern-type to prefixed. This tells the authorizer to match any topic whose name begins with ds-. Don't forget that you also need to grant Read access to the consumer group.

  3. Question 3Advanced

    Troubleshooting · Diagnosing consumer performance issues and rebalance problems.

    During a routine check, an administrator notices that the consumer lag for a critical application is steadily increasing. The application runs a single consumer as part of a consumer group subscribed to a topic with 12 partitions. The consumer's max.poll.records is set to 500 (the default), and max.poll.interval.ms is 300000 (5 minutes). Logs show that the consumer is not being removed from the group, but processing a single batch of 500 records takes, on average, 6 minutes. What is the most direct cause of the increasing consumer lag?

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    Correct answer: B

    The max.poll.interval.ms setting defines the maximum time allowed between calls to the poll() method. If the consumer takes longer than this to process the records from a single poll (6 minutes > 5 minutes), the broker's group coordinator will assume the consumer has failed and kick it out of the group, triggering a rebalance. The logs might not show it immediately, but this constant rebalancing and reprocessing is the direct cause of the lag.

  4. Question 4Beginner

    Observability · Using command-line tools for cluster health checks.

    Which of the following Kafka command-line tools would an administrator use to check for under-replicated partitions in a cluster?

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    Correct answer: B

    The kafka-topics.sh --describe command provides detailed information about topics, including the leader, replicas, and the In-Sync Replica (ISR) set for each partition. By comparing the list of replicas with the ISR list, an administrator can identify any partitions that are under-replicated.

  5. Question 5Intermediate

    Deployment Architecture · Configuring rack awareness for high availability.

    A media company uses Kafka to process video streams. They want to deploy a cluster across three availability zones (AZs) for high availability. To ensure that replicas for any given partition are spread across these AZs, which broker configuration property must be set?

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    Correct answer: C

    The broker.rack property is used to enable Kafka's rack awareness feature. By setting this property on each broker to the name of the availability zone it resides in (e.g., us-east-1a), Kafka will make a best effort to spread replicas of a partition across different racks (AZs), preventing a single AZ failure from causing data loss or unavailability.

  6. Question 6Intermediate

    Apache Kafka Cluster Configuration · Understanding idempotent producers and delivery guarantees.

    A development team has configured a producer with acks=all and enabled idempotence (enable.idempotence=true). What is the primary guarantee provided by this combination of settings?

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    Correct answer: C

    Enabling idempotence ensures that producer retries do not result in duplicate messages being written to the log. This, combined with the ordering guarantees within a single producer session, provides exactly-once, in-order delivery semantics for all messages produced to a specific topic partition.

  7. Question 7Advanced

    Deployment Architecture · Designing a multi-datacenter, highly available, and scalable Kafka architecture.

    Case Study

    Company Background:
    LogiCorpus, a rapidly growing logistics company, relies on a central Apache Kafka cluster for real-time tracking of its fleet of over 10,000 vehicles. Each vehicle sends a location update message every 5 seconds to a single topic named vehicle-tracking. The company is expanding into two new geographic regions, which will triple the number of vehicles and messages within the next six months. The current cluster is deployed on-premises in a single data center.

    Current Situation:
    The existing cluster is beginning to show signs of strain during peak hours, with increased producer latency and occasional consumer lag. The vehicle-tracking topic has 24 partitions with a replication factor of 3. The current on-premises hardware is nearing its capacity limits. A single team of administrators manages the entire platform, and they are concerned about operational overhead with the upcoming expansion.

    Requirements & Constraints:

    1. Scalability: The architecture must scale to handle at least 30,000 vehicles sending updates every 5 seconds.
    2. High Availability: The system must be resilient to a single data center failure.
    3. Low Latency: Real-time tracking is critical; end-to-end latency must remain low.
    4. Reduced Operational Overhead: The solution should minimize the management burden on the small admin team.
    5. Data Sovereignty: Data originating from a specific geographic region must be processed primarily within that region's data center.

    Which solution best meets all of LogiCorpus's requirements?

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    Correct answer: C

    This solution best meets all requirements. Confluent Cloud provides scalability and reduces operational overhead by managing the underlying infrastructure. A multi-zone deployment ensures high availability across data centers. Cluster Linking offers a more robust, lower-latency, and operationally simpler alternative to MirrorMaker for creating consistent data copies, and having regional clusters addresses the data sovereignty constraint.

  8. Question 8Intermediate

    Observability · Interpreting key JMX metrics for consumer performance.

    When monitoring a Kafka cluster using JMX, which MBean attribute provides the most direct measure of consumer lag for a given partition?

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    Correct answer: C

    This JMX metric, exposed on the consumer client, directly reports the estimated number of messages that the consumer is behind the end of the log for a specific partition. It is calculated as the difference between the log-end-offset and the consumer's last committed offset.

  9. Question 9Beginner

    Apache Kafka Fundamentals · Understanding internal Kafka topics.

    What is the primary role of the __consumer_offsets topic in Apache Kafka?

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    Correct answer: B

    The __consumer_offsets topic is a critical internal topic used by Kafka brokers to store the committed offsets for every consumer group. When a consumer commits an offset, a message is written to this topic. This allows Kafka to track the progress of each group and ensure that consumers can resume from the correct position after a restart or rebalance.

  10. Question 10AdvancedSelect 2

    Apache Kafka Cluster Configuration · Managing compatibility during cluster upgrades.

    An administrator is performing a rolling upgrade of a Kafka cluster. To ensure that clients can continue to function correctly during the upgrade process, which two configuration settings are most critical to manage? (Select TWO)

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    Correct answers: B, D

    This property defines the version of the communication protocol used between brokers. During a rolling upgrade, the cluster will have brokers running different software versions. This setting must be temporarily set to the older version across all brokers to ensure they can communicate with each other until the entire cluster is upgraded.

    This topic-level or broker-level property specifies the on-disk message format version. Similar to the inter-broker protocol, it must be kept at the older version until all brokers are upgraded and all consumers have been updated to support the new format. Changing this prematurely can make data unreadable to older clients.

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