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Confluent Certified Administrator for Apache Kafka Questions 11–15 (page: 4)

Updated On: 10-Feb-2026

When a broker goes down, what will the Controller do?

  1. Wait for a follower to take the lead.
  2. Trigger a leader election among the remaining followers to distribute leadership.
  3. Become the leader for the topic/partition that needs a leader, pending the broker return in the cluster.
  4. Automatically elect the least loaded broker to become the leader for every orphan's partitions.

Answer(s): B

Explanation:

When a broker goes down, the Controller detects the failure and triggers a leader election for all partitions that had their leader on the failed broker. The leader is chosen from the in-sync replicas (ISRs) of each partition.



Which technology can be used to perform event stream processing? (Choose two.)

  1. Confluent Schema Registry
  2. Apache Kafka Streams
  3. Confluent ksqlDB
  4. Confluent Replicator

Answer(s): B,C

Explanation:

Kafka Streams is a client library for building real-time applications that process and analyze data stored in Kafka.
ksqlDB enables event stream processing using SQL-like queries, allowing real-time transformation and analysis of Kafka topics.



How can load balancing of Kafka clients across multiple brokers be accomplished?

  1. Partitions
  2. Replicas
  3. Offsets
  4. Connectors

Answer(s): A

Explanation:

Partitions are the primary mechanism for achieving load balancing in Kafka.
When a topic has multiple partitions, Kafka clients (producers and consumers) can distribute the load across brokers hosting these partitions.



A company is setting up a log ingestion use case where they will consume logs from numerous systems. The company wants to tune Kafka for the utmost throughput. In this scenario, what acknowledgment setting makes the most sense?

  1. acks=0
  2. acks=1
  3. acks=all
  4. acks=undefined

Answer(s): A

Explanation:

acks=0 provides the highest throughput because the producer does not wait for any acknowledgment from the broker. This minimizes latency and maximizes performance. However, it comes at the cost of no durability guarantees -- messages may be lost if the broker fails before writing them. This setting is suitable when throughput is critical and occasional data loss is acceptable, such as in some log ingestion use cases where logs are also stored elsewhere.



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?

  1. One
  2. two
  3. three
  4. Four

Answer(s): A

Explanation:

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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