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Apache Kafka Interview Questions and Answers

Experienced / Expert level questions & answers

Ques 1. What ensures load balancing of the server in Kafka?

As the main role of the Leader is to perform the task of all read and write requests for the partition, whereas Followers passively replicate the leader. Hence, at the time of Leader failing, one of the Followers takeover the role of the Leader. Basically, this entire process ensures load balancing of the servers.

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Ques 2. What roles do Replicas and the ISR play?

  • Basically, a list of nodes that replicate the log is Replicas. Especially, for a particular partition. However, they are irrespective of whether they play the role of the Leader.
  • In addition, ISR refers to In-Sync Replicas. On defining ISR, it is a set of message replicas that are synced to the leaders.

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Ques 3. Why are Replications critical in Kafka?

Because of Replication, we can be sure that published messages are not lost and can be consumed in the event of any machine error, program error or frequent software upgrades.

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Ques 4. If a Replica stays out of the ISR for a long time, what does it signify?

Simply, it implies that the Follower cannot fetch data as fast as data accumulated by the Leader.

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Ques 5. In the Producer, when does QueueFullException occur?

Whenever the Kafka Producer attempts to send messages at a pace that the Broker cannot handle at that time QueueFullException typically occurs. However, to collaboratively handle the increased load, users will need to add enough brokers, since the Producer doesn’t block.

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Ques 6. What is the main difference between Kafka and Flume?

The main difference between Kafka and Flume are:

Types of tool:
Apache Kafka: As Kafka is a  general-purpose tool for both multiple producers and consumers.
Apache Flume: Whereas, Flume is considered as a special-purpose tool for specific applications.

Replication feature:
Apache Kafka:  Kafka can replicate the events.
Apache Flume: Whereas, Flume does not replicate the events.

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Ques 7. Is Apache Kafka is a distributed streaming platform and what you can do with it?

Undoubtedly, Kafka is a streaming platform. It can help:
  • To push records easily
  • Also, can store a lot of records without giving any storage problems
  • Moreover, it can process the records as they come in.

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Ques 8. What is the purpose of retention period in Kafka cluster?

However, retention period retains all the published records within the Kafka cluster. It doesn’t check whether they have been consumed or not. Moreover, the records can be discarded by using a configuration setting for the retention period. And, it results as it can free up some space.

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Ques 9. What is Geo-Replication in Kafka?

For our cluster, Kafka MirrorMaker offers geo-replication. Basically, messages are replicated across multiple data centers or cloud regions, with MirrorMaker. So, it can be used in active/passive scenarios for backup and recovery; or also to place data closer to our users, or support data locality requirements.

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Ques 10. Explain Multi-tenancy in Kafka?

We can easily deploy Kafka as a multi-tenant solution. However, by configuring which topics can produce or consume data, Multi-tenancy is enabled. Also, it provides operations support for quotas.

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