Apache Kafka Interview Questions

Top 30 Apache Kafka Interview Questions

The world of technology brings new advancement that keeps transforming the IT sector continuously. Apache Kafka is one in the long list of technological advancements that have revised the conventions in data analytics. As one of the notable real-time data streaming tools, Apache Kafka deserves more recognition, and it rightly gets the same. Therefore, many aspiring professionals search for Apache Kafka interview questions.

Originally developed by LinkedIn in 2011, Apache Kafka subsequently became an open-source project. Today, over 750 companies use Kafka in their tech stacks with some notable names, including Netflix, Uber, Spotify, Pinterest, LinkedIn, Slack, and Activision. Therefore, the promising career prospects with official training in Apache Kafka drive the interests of many IT professionals towards Kafka.

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Table of Contents

Frequently Asked Apache Kafka Interview Questions

The attention on Apache Kafka interview questions and answers is very important for candidates as they should showcase their expertise in Kafka to potential employers. Interview questions are different than those in a written exam. You have to answer the questions in an interview with precision and focus on important points.

Most important of all, your response should be brief yet capable of convincing the interviewer about your expertise in Kafka. The following discussion would point out some of the top Kafka interview questions and their answers. Aspiring candidates can utilize the following guide to prepare for the simplest to toughest questions they can possibly encounter in an interview for a Kafka-based job role.

1. What is Kafka?

This is probably one of the first Apache Kafka interview questions that candidates encounter. Many candidates assume that it is the simplest of all questions. However, you should be careful while presenting your response to this question as it would determine your initial impression on the interviewer.

Apache Kafka is a publish-subscribe open-source message brokering application. The foundation of Apache Kafka is the Scala programming language. You can find that the design pattern of Kafka relies primarily on the design of transactional logs. Apache Kafka’s design also enables its role as an open-source stream-processing software platform, thereby adding stream processing capabilities to it.

2. How is Kafka messaging system different than other messaging frameworks?

The answer to such Kafka interview questions should be straightforward. Candidates can outline their response in the form of bullet points that differentiate Kafka from other messaging or real-time data streaming platforms. Here are the pointers that separate Kafka from the rest of its competition.

  • The design follows a public-subscribe model.
  • Seamless support for Spark and other Big Data technologies.
  • Support for cluster mode operation.
  • Fault tolerance capability for reducing concerns of message loss.
  • Support for Scala and Java programming languages.
  • Ease of coding and configuration.
  • Ideal for web service architecture as well as big data architecture.

3. Do You know the different components of Kafka?

This is a frequently asked Kafka interview question for which candidates should prepare well. Kafka has four major components, such as Topic, Producer, Brokers, and Consumers. The topic in Kafka is a stream of messages that are of the same type.

The Producer in Kafka helps in publishing messages to a topic. Brokers are the set of servers that store the published messages by producers. Consumers are the Kafka component, which helps in subscribing to different topics and pulling data from the brokers.

4. What is an offset in Kafka?

The offset in Kafka is the sequential ID number allocated to messages in the partition. The offsets help in the unique identification of each message in a particular partition.

5. Define a consumer group in Kafka?

Candidates can face such entries among the most common Kafka interview questions. First of all, it is essential to note that Consumer Groups is a concept exclusively specific for Apache Kafka. Each consumer group in Kafka comprises of one or more consumers consuming an assortment of subscribed topics, in collaboration.

6. What is the importance of Zookeeper in Kafka?

This is also one of the notable Kafka interview questions that you may come across. Zookeeper is primarily responsible for developing coordination between the different nodes in a cluster. Zookeeper can help in recovery from previously committed to offsetting in the event of failure of a node because it works as periodically commit offset.

In addition, Zookeeper also helps in leader detection, configuration management, synchronization, and detecting any node leaving or joining the cluster. Furthermore, Kafka implements Zookeeper as storage for offsets of consumed messages regarding a specific topic. Zookeeper also helps in partitioning the offsets of messages according to specific Consumer Groups.

7. Can I use Kafka without Zookeeper?

No. You cannot bypass Zookeeper for a direct connection with the Kafka server. In addition, it is also essential to note that servicing client requests becomes impossible when Zookeeper is experiencing downtime.

Also Read: Real-time Big Data Pipeline with Hadoop, Spark, and Kafka

8. What are the advantages of Kafka?

Candidates can expect such Kafka interview questions easily in their interviews for Kafka-based job roles. The primary advantages of Kafka include fault-tolerance, higher throughput, scalability, lower latency, and durability. Kafka does not require any large-scale hardware components and shows exceptional performance in the management of high-volume and high-velocity data.

Most important of all, it can support message throughput at the rate of thousand messages per second. Kafka depicts promising resistance to the failure of nodes or machines within a cluster. Lower latency of Kafka can help in easily managing the messages within milliseconds. In addition, Kafka also ensures message replication, thereby reducing any concerns of message loss. Another critical benefit of Apache Kafka is the scalability that it ensures through the addition of more nodes.

9. What do you mean by leader and follower in Kafka?

Candidates should prepare for such the latest Kafka interview questions that dig deeper into the architecture of Kafka. Each partition in Kafka is associated with one server that plays the role of Leader, and the other servers play the role of Followers.

A leader is responsible for performing all the read and write requests for the concerned partition. On the other hand, followers have to replicate the leader passively. If the Leader fails, then one of the Followers could assume the role of a Leader to ensure load balancing.

10. What are the different use cases of Apache Kafka?

The different use cases of Kafka include Kafka metrics, stream processing, and Kafka log aggregation. Kafka is suitable for the operational monitoring of data. In addition, Kafka also includes an aggregation of statistics from distributed applications to develop centralized feeds of operational data.

Kafka’s durability is a strong factor for validating its use in stream processing. In addition, Kafka is also ideal for the collection of logs from various services throughout an organization.

11. Do you know about stream processing in Kafka?

Candidates can expect such Kafka interview questions commonly, especially considering the large-scale applications of Kafka in real-time data streaming. Stream processing involves continuous, concurrent, and real-time processing of data by following a record-by-record approach.

12. What are some of the unique features of Kafka Stream?

Kafka Stream is the ideal real-time data streaming tool for different reasons. Here are the unique features that establish the popularity of Kafka Stream.

  • High scalability and fault tolerance.
  • Easy deployment to the cloud, containers, bare metal or virtual machines.
  • Through integration with Kafka security.
  • Facility for writing standard Java applications.
  • One-time processing semantics.
  • Suitable for the small, medium as well as large use cases.
  • No requirement of separate processing clusters.

13. How do you know that Kafka is a Distributed Streaming Platform?

Candidates should always prepare for such Kafka interview questions. Apache Kafka contains the following three capabilities that prove its identity as a distributed streaming platform. First of all, it can help in pushing records easily.

In addition, Apache Kafka also helps you with storing lots of records without encountering storage issues. Most important of all, Kafka has the capability for processing records as they arrive. These capabilities clearly establish Kafka as a reliable distributed streaming platform.

14. Can you explain the process of starting a Kafka Server?

This is one of the best Kafka interview questions from the perspective of candidates. Start your answer by emphasizing the fact that you cannot start the Kafka server without Zookeeper. So, it is important to start Zookeeper’s server. Then, we have to use the convince script that comes packaged with Kafka to obtain a raw yet effective single-node instance of Zookeeper. Here is an example,


Following this, the Kafka server starts like in the example below,


15. What is a Kafka Cluster, and what are its key benefits?

Candidates could expect such advanced Kafka interview questions as they proceed to higher stages in an interview. Kafka cluster is a group containing more than one broker. It has zero downtime during the expansion of clusters and can help in the replication of message data and management of persistence.

The cluster-centric design of the Kafka cluster improves durability. Most important of all, one of the brokers in a cluster manages the states of replicas and partitions. The concerned broker is also responsible for performing administrative tasks such as the reassignment of partitions.

Apache Kafka as a real-time data streaming tool can send data to other platforms for streaming analytics for the purpose of analysis. Here’s the list of Top Real-time Data Streaming tools you should know about.

16. What are some of the use cases where Kafka is not suitable?

First of all, you need promising knowledge regarding the setup and configuration of the Kafka ecosystem to use it properly. In addition, there are other notable use cases where Kafka is not applicable. If you don’t have a monitoring tool or the Wildcard option for the selection of the topic, then Kafka is not suitable.

Most important of all, you need in-depth expertise and understanding for the management of cluster-based infrastructure in Kafka alongside Zookeeper.

17. Define consumer lag and ways to monitor it.

This is one of the difficult Kafka interview questions that you may come across. Kafka follows a publisher-subscriber model in which the producer writes to a particular topic, and one or more consumers read from the concerned topic. On the other hand, the reads in Kafka tend to lag behind the writes due to delay between the moment of writing a message and the moment of consuming a message.

Therefore, Consumer Lag is the delay between the Latest Offset and the Consumer Offset. One of the unique tools for monitoring consumer lag is LinkedIn Burrow. In addition, the Confluent Kafka provides innovative tools for measuring Consumer Lag.

18. Define Geo-replication in Kafka.

This is also a notable entry among common Kafka interview questions. The geo-replication feature helps in replication throughout different clusters and different data. Kafka Mirror is the ideal tool for enabling geo-replication with a process known as mirroring. The mirroring process is slightly different from replication throughout different nodes in one cluster. The Kafka Mirror Maker ensures replication of messages from topics belonging to one or more Kafka clusters to the destination cluster having similar topic names.

19. What is the importance of Replicas in Kafka?

Replicas in Kafka are basically a list of nodes that replicate the log for a specific partition without considering whether the nodes serve as the Leader. Replicas are highly significant in Kafka because of the safety of published messages. Replication ensures that users can consume published messages even in circumstances such as program error, regular software updates, or machine errors.

20. Do you know about System Tools in Kafka?

System tools are a common element in many Kafka interview questions. Kafka has three prominent categories of System tools. The Kafka Mirror Maker helps in mirroring one Kafka cluster to another. The Kafka Migration Tool ensures the migration of a broker from a specific version to another. Another common System tool that you can find with Kafka is the Consumer Offset Checker. The Consumer Offset Checker shows the Topic, Owner, and Partitions for a particular set of Topics and Consumer Group.

21. What is the significance of the Replication Tool?

The Replication Tool in Kafka is a helpful addition to promoting higher availability and better durability. Some of the common types of replication tools include the Create Topic tool, List Topic tool, and Add Partition tool.

22. What is the relationship between Apache Kafka and Java?

Candidates should also prepare adequately for such insightful Kafka interview questions for better chances of qualifying interviews. The foremost relationship between Java and Apache Kafka is that the former supports the standard requirement of high processing rates in Kafka. In addition, Java also provides exceptional community support for all Kafka consumer clients. Therefore, one of the best practices for implementing Kafka is to choose Java for the implementation.

23. Does Kafka provide any guarantees?

This is one of the tricky Kafka interview questions that test the deeper knowledge of candidates in Kafka. Kafka provides the guarantee of tolerating up to N-1 server failures without losing any record committed to the log. In addition, Kafka also ensures that the order of messages sent by the producer to the specific topic partition will be the same for multiple messages. Kafka also provides the guarantee that consumer instance can view records in the order of their storage in the log.

Preparing for a Big Data interview? Go through these top Big Data Interview Questions and get yourself ready to ace the interview.

24. How is Apache Kafka better than RabbitMQ?

Candidates could also expect such the latest Kafka interview questions. RabbitMQ is the most notable alternative for Apache Kafka. The features of Kafka as a distributed, highly available, and a durable system for data sharing and replication are better than RabbitMQ, which does not have these features. The performance rate of Apache Kafka could extend up to 100,000 messages per second. On the other hand, RabbitMQ has a limited performance rate of around 20,000 messages per second.

25. What do you mean by the retention period in a Kafka Cluster?

This is also one of the notable Kafka interview questions that you may come across. First of all, the retention period involves retaining all published records in the Kafka cluster. The retention period does not check for the consumption status of the published records. In addition, it is possible to discard records with the use of a specific configuration setting for the concerned retention period. As a result, it can also free up adequate space.

26. Do you know about Log Compaction?

Candidates should be prepared for such expert-level Kafka interview questions too for their interview. The log cleaner manages log compaction in Apache Kafka. The log cleaner is a collection of background threats for recopying log segment files. It removes records with their key appearing in the head of the log.

The compactor thread selects the log with the highest log head to the log tail ratio. In addition, it also creates a brief summary of the last offset for every key in the head of the log. The log cleaner recopies the log from the start to the end by excluding keys, which can possibly occur later in the log.

Then, the log cleaner swaps clean segments into the log immediately, thereby restricting the requirement of additional disk space to only one additional segment. Therefore, log compaction does not require additional storage for the full copy of the log. You can find the summary of the log head as a space-compact hash table that uses precisely 24 bytes for every entry. Therefore, a cleaner buffer of 8GB can purge 366GB of log head in a cleaner iteration.

27. What do you know about Quotas in Apache Kafka?

One of the prominent topics for Kafka interview questions is quotas. Every Kafka cluster comes with the ability to enforce quotas on the requests for controlling broker resources that clients use. Kafka brokers can employ two different types of client quotas for a different group of clients sharing a particular quota.

For example, network bandwidth quotas help in defining the byte-rate thresholds. This feature is available since version 0.9. Another quota implemented by Kafka refers to request rate quotas. Request rate quotas provide a clear definition of the CPU usage thresholds in terms of I/O threads and percentage of the network.

28. Do you know about Client Groups in Kafka?

Candidates should be prepared for such Kafka interview questions that deal directly with basic components. The user-principal represents the identity of a Kafka client by denoting a specific authenticated user in a secure cluster. The user-principal is generally a combination of unauthenticated users selected by a broker using a configurable PrincipalBuilder in a cluster supporting unauthenticated clients.

Client-id provides a logical grouping of clients, along with a meaningful name allocated by the client application. In addition, the tuple of user and client-id define the secure logical group of clients involved in sharing user principal as well as client-id.

29. When does the QueueFullException happen in the producer in Kafka?

Candidates can find such technical Kafka interview questions also in their interview for Kafka-based job roles. QueueFullException generally happens at the time when Kafka Produces aims to send messages at a speed which the Broker could not handle at that instant. However, it is possible to overcome the QueueFullException by adding an adequate number of brokers because the Producer does not block the addition of brokers.

30. What are some of the notable Apache Kafka operations?

Candidates should also prepare for technical Kafka interview questions for ensuring the best results possible in their interview for a Kafka-based job role. Here are the important Apache Kafka operations that you should note.

  • Modification of Kafka Topics.
  • Locating the position of the Consumer.
  • Automatic migration of data.
  • Adding and deleting Kafka Topics.
  • Distinguished Turnoff.
  • Expansion of Kafka cluster.
  • Mirroring of data between different Kafka clusters.
  • Datacenters.
  • Retirement of servers.

Have any questions about Apache Kafka? Join us and get connected with our experts to get answers to your questions. You can also write your query in Whizlabs Forum to get answers.

31. Difference between Apacke streaming and Spark Streaming.

Kafka Streams Spark Streaming
It is fault-tolerant by the utilization of partitions and replicas. Spark can be able to restore partitions with the usage of Cache and RDD (Resilient Distributed Dataset).
It can be able to handle real-time streams Handle both real-time and batch tasks.
Long-persistent of messages in the Kafka log To retain the data durably, it uses data frame or another data structure.
Interactive modes are not present in Kafka. The data produced by the producer can be simply managed by the broker and then it waits for the client to read it. Interactive modes will be available.

32. What does “graceful shutdown” in Kafka mean?’

Any broker failure or shutdown will be automatically detected by the Apache cluster. In this case, new leaders will be selected for partitions that were previously managed by that device. When a server fails or is shut down for repair or configuration updates, it will occur. When a server is intentionally brought down, Kafka offers a graceful way to end the server rather than destroying it.

33. How to change the retention time in Kafka at runtime?

Starting with version 0.9.0 and later, the correct command to modify the configurations of a currently operating topic in Kafka is “kafka-configs.sh –alter.”

Prior to version 0.9.0, the command to use was “kafka-topics.sh –alter.” However, from version 0.9.0 onwards, the “kafka-configs.sh” command should be used for altering topic configurations.

To modify the retention time of a topic, you can use the following command:

Replace <bootstrap-server> with the address and port of the Kafka bootstrap server, <topic-name> with the name of the topic you want to modify, and <retention-time-in-milliseconds> with the desired retention time in milliseconds.

34. What is meant by Znodes in Kafka Zookeeper?

Znodes are the nodes in a ZooKeeper tree. Znodes maintains version numbers in a structure for timestamps, ACL changes, and data alterations. The version number and timestamp are used by ZooKeeper to validate the cache and ensure that updates are coordinated. The version number associated with the data on Znode increases each time when it changes.

35. Define confluent kafka.

Confluent serves as an Apache Kafka-based data streaming platform and it is a full-scale streaming platform capable of storing and processing information within the stream in addition to publish-and-subscribe functionality. A more thorough version of Apache Kafka is Confluent Kafka. By incorporating tools for maintaining and optimising Kafka clusters as well as techniques for assuring the security of the streams, it improves Kafka’s integration capabilities.


So, do you think that you are up for a Kafka interview right now? Even if the questions and answers in the above-mentioned discussion improve the prospects of qualifying an interview easily, you should explore further. Try to find some advanced questions such as Kafka performance tuning interview questions and their answers on different online platforms. Considering the rising popularity of Apache Kafka, more and more enterprises are joining the Kafka bandwagon.

Therefore, qualifying a Kafka interview can definitely open new and promising opportunities for IT professionals. The use of Kafka in stream processing is also a notable milestone in the field of data analytics. Therefore, the ever-increasing scope of applications of Apache Kafka complemented with new updates, and features drive further interest in Kafka interview questions to build a successful career in Apache Kafka.

Aspiring to learn Apache Kafka and build a successful career in Big Data? Enroll in the Apache Kafka Training Course and lay the foundation of a bright future ahead!

About Aditi Malhotra

Aditi Malhotra is the Content Marketing Manager at Whizlabs. Having a Master in Journalism and Mass Communication, she helps businesses stop playing around with Content Marketing and start seeing tangible ROI. A writer by day and a reader by night, she is a fine blend of both reality and fantasy. Apart from her professional commitments, she is also endearing to publish a book authored by her very soon.

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