KAFKA Interview Questions and Answers 2023 (FAQ): Tricky, Advanced, & More

KAFKA Interview Questions and Answers 2023 | Kafka Interview Questions For 7 Years Experience | Kafka Scenario-Based Interview Questions | Spring Boot Kafka Interview Questions | Tricky Kafka Interview Questions

KAFKA Interview Questions and Answers 2023 | Kafka Interview Questions Advanced: Kafka is a Scala-based open-source subscriber-publisher mechanism. Because of its low latency and high throughput, it is a popular data processing tool. Scalability, low latency, and data splitting are all possible. These characteristics have resulted in a diverse spectrum of occupations for competent workers in Kafka. Now, let’s delve into the abundance of often-requested Kafka interview questions and answers for both freshers and experienced candidates. We’ve collected a list of the most often asked Kafka interview questions to help you ace your next Kafka interview. Basic, Tricky, and Advanced Kafka Interview Questions have been organized into three sections. Here you may get the Upcoming Interview Questions

Tricky Kafka Interview Questions

  • What is meant by partition offset?
  • What is a Smart producer/ dumb broker?
  • What is load balancing?
  • What is Kafka producer Acknowledgement?
  • What is fault tolerance?
  • What are the benefits of using Kafka?
  • What advantages does Kafka have over Flume?
  • Discuss the architecture of Kafka.
  • What is the role of Kafka Producer API play?
  • What are replications dangerous in Kafka?

Kafka Interview Questions for Freshers

  • What are the major components of Kafka?
  • What do you mean by zookeeper in Kafka and what are its uses?
  • Describe the partitioning key in Kafka.
  • What is the purpose of partitions in Kafka?
  • How do you start a Kafka server?
  • Explain the concept of Leader and Follower in Kafka.

Kafka Interview Questions and Answers for Freshers

What is the maximum size of a message that Kafka can receive?

  • The maximum size of a Kafka message is set at 1MB by default (megabyte).
  • You may change the size in the broker settings. Kafka, on the other hand, is built to accommodate 1KB messages.

What does it mean if a replica is not an In-Sync Replica for a long time?

A copy that has been out of ISR for an extended amount of time shows that the follower is unable to acquire data as quickly as the leader.

What are some of the disadvantages of Kafka?

The following are the disadvantages of Kafka :

  • When messages are tweaked, Kafka’s performance suffers. Kafka works effectively when the message does not need to be updated.
  • Kafka does not allow the use of wildcard topics. The precise topic name must be matched.
  • When dealing with large messages, brokers and consumers degrade Kafka’s performance by compressing and decompressing the messages. This has an effect on the throughput and performance of Kafka.
  • Kafka does not support some message paradigms, such as point-to-point queues and requests/replies.
  • Kafka lacks a comprehensive set of monitoring tools.

What are the benefits of using clusters in Kafka?

  • A Kafka cluster is essentially a collection of brokers.
  • They are used to keep the load balanced. Because Kafka brokers are stateless, they rely on Zookeeper to maintain the state of their cluster.
  • A single Kafka broker instance can handle hundreds of thousands of reads and writes per second, and each broker can process TBs of messages without slowing down. Zookeeper may be used to select the leader of the Kafka broker.
  • Thus, having a cluster of Kafka brokers significantly improves performance.

What are the use cases of Kafka monitoring?

The following are the use cases of Kafka monitoring :

  • Track System Resource Consumption: It may be used to monitor the consumption of system resources like memory, CPU, and disc space over time.
  • Monitor threads and JVM usage: Kafka relies on the Java garbage collector to free up memory, which ensures that it runs often, keeping the Kafka cluster alive.
  • Keep a watch on the broker, controller, and replication statistics so that partition and replica statuses may be changed as needed.
  • Identifying performance bottlenecks and determining which apps are producing excessive demand may aid in the speedy resolution of performance issues.

Can we use Kafka without Zookeeper?

  • As of version 2.8, Kafka may be utilized without ZooKeeper. When Kafka 2.8.0 was released in April 2021, we all had the opportunity to check it out without ZooKeeper. This version, however, is not yet suitable for production and missing certain critical features.
  • It was not feasible to connect directly to the Kafka broker without going via Zookeeper in prior versions. This is due to the Zookeeper’s inability to fulfill client requests when it is down.

What are some of the features of Kafka?

  • A Topic is a built-in patriation scheme in Kafka.
  • Kafka also has a replication option.
  • Kafka offers a queue for transferring messages from one sender to another.
  • Kafka can also store messages and duplicate them throughout the cluster.
  • Kafka works with Zookeeper to coordinate and synchronize with other services.
  • Kafka provides excellent support for Apache Spark.

Explain the concept of Leader and Follower in Kafka.

  • Each partition in Kafka has one server acting as a Leader and one or more servers acting as Followers.
  • The partition’s read and write requests are handled by the Leader, while the Followers are in charge of passively replicating the Leader.
  • If the Leader fails, one of the Followers will take over as leader.

Why is Topic Replication important in Kafka? What do you mean by ISR in Kafka?

Topic replication is essential for building Kafka installations that are both long-lasting and highly available. When one broker fails, topic replicas on other brokers save data from being lost and the Kafka deployment from being interrupted. The replication factor determines how many copies of a subject are stored across the Kafka cluster. It occurs at the partition level and is specified at the topic level. For example, a replication factor of two will store two copies of a subject for each partition.

  • Each partition has an elected leader, while other brokers keep a backup in case it is needed.
  • Logically, the replication factor cannot be more than the entire number of brokers in the cluster.
  • An In-Sync Replica (ISR) is one that is in sync with the partition’s leader.

What are the traditional methods of message transfer? How is Kafka better from them?

Message Queuing

  • The message queuing pattern employs a point-to-point approach. A message in the queue will be discarded after it has been eaten, similar to how a message in the Post Office Protocol is removed from the server once it has been delivered. These queues support asynchronous messaging.
    If a network difficulty, such as a consumer being unavailable, causes a message to be kept in the queue until it can be sent, the message will be retained in the queue until it can be delivered. As a result, messages are not always transmitted in the same order. They are instead distributed on a first-come, first-served basis, which can increase efficiency in some cases.

Publisher – Subscriber Model

  • Publishers generate (“Publish”) messages in several categories, whereas subscribers consume published messages from the different categories to which they are subscribed. In contrast to point-to-point texting, a message is only withdrawn when it has been digested by all category subscribers.
    Kafka caters to a single consumer abstraction, the consumer group, which includes both of the aforementioned. The following are the advantages of adopting Kafka over standard communications transmission methods:

    • Scalable: A group of devices is utilized to segment and simplify data, increasing storage capacity.
    • Faster: Because a single Kafka broker can handle gigabytes of reads and writes per second, it can serve thousands of customers.
    • Durability and fault Tolerance: By replicating the data in the clusters, the data is kept permanent and resilient to any hardware faults.

What do you mean by Geo-Replication in Kafka?

  • Geo-Replication is a feature of Kafka that allows messages in one cluster to be replicated across many data centers or cloud regions.
  • Geo-replication means reproducing all files and storing them around the world as needed.
  • Kafka’s MirrorMaker Tool can do geo-replication.
  • Geo-replication is a method of backing up data.

Kafka Interview Questions for Experienced

  • Tell me about some of the use cases where Kafka is not suitable
  • What do you understand about log compaction and quotas in Kafka?
  • What are the guarantees that Kafka provides?
  • What do you mean by an unbalanced cluster in Kafka? How can you balance it?
  • Differentiate between Redis and Kafka
  • Describe in what ways Kafka enforces security
  • Differentiate between Kafka and Java Messaging Service(JMS)
  • What do you understand about Kafka MirrorMaker?
  • Differentiate between Kafka and Flume
  • What do you mean by confluent kafka? What are its advantages?
  • How will you expand a cluster in Kafka?
  • What do you mean by the graceful shutdown in Kafka?
  • Differentiate between Kafka streams and Spark Streaming
  • How will you change the retention time in Kafka at runtime?
  • What do you mean by multi-tenancy in Kafka?
  • What is a Replication Tool in Kafka? Explain some of the replication tools available in Kafka
  • Differentiate between Rabbitmq and Kafka
  •  What are the parameters that you should look for while optimizing Kafka for optimal performance?

Basic Kafka Interview Questions and Answers

What is the role of the offset?

In partitions, messages are assigned a unique ID number called the offset. The role is to identify each message in the partition uniquely.

Can Kafka be used without ZooKeeper?

It is not possible to connect directly to the Kafka Server by bypassing ZooKeeper. Any client request cannot be serviced if ZooKeeper is down.

In Kafka, why are replications critical?

Replications are critical as they ensure published messages can be consumed in the event of any program error or machine error and are not lost.

What is a partitioning key?

Ans. The partitioning key indicates the destination partition of the message within the producer. A hashing based partitioner determines the partition ID when the key is given.

What is the critical difference between Flume and Kafka?

Kafka ensures more durability and is scalable even though both are used for real-time processing.

When does QueueFullException occur in the producer?

QueueFullException occurs when the producer attempts to send messages at a pace not handleable by the broker.

What is a partition of a topic in Kafka Cluster?

Partition is a single piece of Kafka topic. More partitions allow excellent parallelism when reading from the topics. The number of partitions is configured based on per topic.

Explain Geo-replication in Kafka.

The Kafka MirrorMaker provides Geo-replication support for clusters. The messages are replicated across multiple cloud regions or datacenters. This can be used in passive/active scenarios for recovery and backup.

What do you mean by ISR in Kafka environment?

ISR is the abbreviation of In sync replicas. They are a set of message replicas that are synced to be leaders.

How can you get precisely one messaging during data production?

To get precisely one messaging from data production, you have to follow two things avoiding duplicates during data production and avoiding duplicates during data consumption. For this, include a primary key in the message and de-duplicate on the consumer.

How do consumers consumes messages in Kafka?

The transfer of messages is done in Kafka by making use of send file API. The transfer of bytes occurs using this file through the kernel-space and the calls between back to the kernel and kernel user.

What is Zookeeper in Kafka?

One of the basic Kafka interview questions is about Zookeeper. It is a high performance and open source complete coordination service used for distributed applications adapted by Kafka. It lets Kafka manage sources properly.

What is a replica in the Kafka environment?

The replica is a list of essential nodes needed for logging for any particular partition. It can play the role of a follower or leader.

What does follower and leader in Kafka mean?

Partitions are created in Kafka based on consumer groups and offset. One server in the partition serves as the leader, and one or more servers act as a follower. The leader assigns itself tasks that read and write partition requests. Followers follow the leader and replicate what is being told.

Name various components of Kafka.

The main components are:

  1. Producer – produces messages and can communicate to a specific topic
  2. Topic: a bunch of messages that come under the same topic
  3. Consumer: One who consumes the published data and subscribes to different topics
  4. Brokers: act as a channel between consumers and producers.

Why is Kafka so popular?

Kafka acts as the central nervous system that makes streaming data available to applications. It builds real-time data pipelines responsible for data processing and transferring between different systems that need to use it.

What are consumers in Kafka?

Kafka tags itself with a user group, and every communication on the topic is distributed to one use case. Kafka provides a single-customer abstraction that discovers both publish-subscribe consumer group and queuing.

What is a consumer group?

When more than one consumer consumes a bunch of subscribed topics jointly, it forms a consumer group.

How is a Kafka Server started?

To start a Kafka Server, the Zookeeper has to be powered up by using the following steps:

> bin/zookeeper-server-start.sh config/zookeeper.properties

> bin/kafka-server-start.sh config/server.properties

How does Kafka work?

Kafka combines two messaging models, queues them, publishes, and subscribes to be made accessible to several consumer instances.

Kafka Interview Questions and Answers Advanced

What do you understand by multi-tenancy?

  • One of the most often requested advanced Kafka interview questions.
  • Kafka may be used in a multi-tenant environment.
  • The setting for various subjects where data will be consumed or created is enabled.

How is Kafka tuned for optimal performance?

  • To tune Kafka, it is essential to tune different components first.
  • This includes tuning Kafka producers, brokers, and consumers.

What are the benefits of creating Kafka Cluster?

  • When we enlarge the cluster, there is no downtime in the Kafka cluster.
  • The cluster is in charge of message data replication and durability.
  • Because of its cluster-centric architecture, the cluster has a high level of resilience.

Who is the producer in Kafka?

  • The client who releases and transmits the record is known as the producer.
  • The data is sent to the broker service by the producer.
  • Producer apps write data on subjects that are ready for consumption by consumer applications.

Tell us the cases where Kafka does not fit.

  • The Kafka environment is quite challenging to establish, and implementation knowledge is required.
  • It is ineffective in cases when monitoring tools are few, and there is no wildcard option for selecting subjects.

What is the consumer lag?

  • Ans Reads in Kafka lag behind Writes as there is always some delay between writing and consuming the message.
  • This delta between the consuming offset and the latest offset is called consumer lag.

What do you know about Kafka Mirror Maker?

The Kafka Mirror Maker application aids in the replication of data across two Kafka clusters in separate or identical data centres.

Is getting a message offset possible after production?

  • This is not achievable from a producer class since, like other queue systems, its function is to forget and shoot the messages.
  • The offset is obtained as a message consumer from a Kaka broker.

How can the Kafka cluster be rebalanced?

  • Partitions are not automatically balanced when a client adds additional discs or nodes to existing nodes.
  • If the replication factor is already equal for numerous nodes in a topic, additional discs will not help with rebalancing.
  • After adding additional hosts, the Kafka-reassign-partitions operation is suggested instead.

How does Kafka communicate with servers and clients?

  • The clients and servers communicate via a high-performance, simple, language-independent TCP protocol.
  • This protocol is backward compatible with the previous version.

How is the log cleaner configured?

  • It is activated by default and begins the cleaner thread pool.
  • Add log.cleanup.policy=compact to enable log cleaning on a specific topic.
  • This may be done with the modify topic command or during the subject creation process.

What are the three broker configuration files?

The essential configuration files are broker.id, log.dirs, zookeeper.connect.

What are the traditional methods of message transfer?

The typical approach entails the following steps:

  • Queuing- a pool of consumers reads a message from the server, and each message is sent to a different consumer.
  • Publish-subscribe: Messages are sent to all subscribers.

What is a broker in Kafka?

The broker term is used to refer to Server in the Kafka cluster.

How can churn be reduced in ISR, and when does the broker leave it?

ISR has received all of the committed messages. It should have all replicas until a true failure occurs. If a replica deviates from the leader, it is removed from ISR.

If replica stays out of ISR for a long time, what is indicated?

If a copy is out of ISR for an extended period of time, it shows that the follower cannot acquire data as quickly as it is accumulated at the leader.

What happens if the preferred replica is not in the ISR?

The controller will fail to move leads to the preferred replica if it is not in the ISR.

What is meant by SerDes?

SerDes (Serializer and Deserializer) materialises data for any Kafka stream when SerDes is available for all records and record values.

What maximum message size can the Kafka server receive?

The maximum message size that a Kafka server can receive is 10 lakh bytes.

How can the throughput of a remote consumer be improved?

If the customer is not in the same data center as the broker, the socket buffer size must be adjusted to compensate for the lengthy network delay.


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