Apache Kafka Interview Questions

This Apache Kafka Interview Questions blog will review its features, capabilities, use cases and benefits.

Apache Kafka is an open-source distributed event streaming framework used for real-time data pipelines and streaming apps.

Apache Kafka has quickly become one of the go-to solutions for organizations looking to enhance data management and analytics due to its low latency processing and massive data volumes.

No matter your experience with Kafka, this Apache Kafka Interview Questions and Answersblog can provide helpful insight into this powerful streaming technology.

Let’s embark and discover Apache Kafka!

1. What is Apache Kafka?

Apache Kafka is a distributed published-subscribe messaging system that solves the problem of data pipelines by decoupling producers and consumers.

2. What are the benefits of using Apache Kafka?

The benefits of using Apache Kafka include high throughput, data scalability, fault tolerance, and data loss protection.

Kafka is also legally scalable, allowing for scaling up or down without downtime.

3. What is Kafka architecture, and how does it create total parallelism in processing messages?

Kafka architecture consists of a producer producing messages to a topic with three partitions and three consumers consuming from these partitions.

This creates total parallelism in processing messages, allowing for high throughput and low latency.

4. What is the Confluent Control Center?

Confluent Control Center is a web-based management and monitoring tool for the Confluent Platform that allows the visualisation and configuration of various platform aspects.

5. What are data pipelines, and why are they essential in real-time scenarios?

Data pipelines are essential in real-time scenarios as they connect different systems or services, enabling communication and exchange between them.

They help organisations manage complex systems and improve their overall efficiency and effectiveness.

6. What is the purpose of a while true loop in a consumer in an event-driven software?

To continuously check for messages and log them to standard out.

7. What is the role of a broker in a Kafka cluster?

A broker is responsible for storing and processing messages for a topic in a Kafka cluster.

8. What is a messaging system, and how does it simplify data pipelines?

A messaging system is a communication tool that enables remote communication, sending data across networks and providing a standard paradigm independent of platforms and languages.

It simplifies data pipelines by reducing communication complexity between systems, making it easier to manage and scale.

9. What is a Kafka broker’s responsibility?

A Kafka broker’s responsibility is to manage partitions and manage topics.

10. What is a patch of Kafka, and how does it differ from traditional queueing and published subscribe models?

A patch of Kafka is a distributed published-subscribe messaging system that differs from traditional queueing and published subscribe models.

In traditional queueing, a pool of consumers reads from a server, with each record going to one of them. In published subscribe, records are broadcasted to all consumers, making Kafka fast, scalable, and fault-tolerant.

11. What is the difference between a Kafka log and a message?

A Kafka log is an immutable record of events, while a Kafka message is a record that includes key-value pairs, timestamps, and optional headers.

12. What is replication in Kafka, and how does it guarantee fault tolerance?

Replication in Kafka is a feature that allows Kafka to replicate a topic into multiple brokers in a Kafka cluster.

A subject with a replication factor n can tolerate up to n minus one several failures without losing any record committed to the log.

This guarantees fault tolerance by allowing Kafka to continue functioning even in the presence of failures.

13. How are segments in Kafka created?

Segments in Kafka are created when messages are produced and expire when the newest record is older than the retention period.

14. What is a stream processor in Kafka, and what does it do?

A stream processor in Kafka is a component that takes continual streams of data from input topics, performs processing operations on this input, and produces continuous data streams to output topics.

Kafka provides a fully integrated stream API for more complex transformations, allowing for non-trivial processing like aggregation or joining streams.

15. What is Zookeeper?

Zookeeper is a distributed system that performs three primary functions in Kafka: electing a controller, cluster membership, and topic configuration.

16. What is durability in Kafka, and why is it important?

Durability in Kafka means that data written to Kafka is persisted to disk and replicated for fault tolerance. This ensures that data is not lost even if there are failures in the system.

Durability is essential because it guarantees data persistence and fault tolerance, making Kafka a reliable and trustworthy messaging system.

17. What is Kafka Streams?

Kafka Streams is a stream processing platform introduced in Kafka 0.10, which allows users to process data in multiple stages and transform raw input data into new topics for further consumption.

18. What is a message in Kafka, and how is it directed to a partition using a message key?

A message in Kafka is a record consisting of a key of value at a time stamp directed to a partition using a message key.

The message key is generated by a partitioner, which maps it to a partition, ensuring that messages with the same key are always written in the same partition.

19. What are the different types of Kafka clusters?

There are different types of Kafka clusters, such as single-load single-broker clusters, single-load multi-broker clusters, and multi-node multi-broker clusters.

20. What is a Kafka topic?

A Kafka topic is a schema that describes a topic’s messages, retention period, and compaction properties.

21. How is Kafka used for operational monitoring data?

Kafka is used for operational monitoring data by abstracting logs and data streams, allowing for lower latency processing and more accessible support for multiple data sources.

22. What is a Kafka cluster?

A Kafka cluster is a distributed system comprising brokers that manage the cluster.

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23. What is a partition in Kafka, and how does it work?

A partition is a log with strict ordering, meaning that when a producer writes a new message to a partition, it puts the message at the end of the partition.

This ensures that the events in the partition are strictly ordered.

24. How do producers determine the partition number for messages without a key?

Producers use a round-robin method to determine the partition number for messages without a key.

25. How do consumers determine their offset into each partition?

Consumers store their offset in a particular topic called consumer offsets, helping them remember their location.

26. What is a topic in Kafka?

A topic is a collection of related messages or events, considered a log or sequence of events. There is no theoretical limit on the number of issues or partitions, but there is a practical limit on the number of partitions.

27. What is the difference between a Kafka producer and a consumer?

A Kafka producer writes data into the cluster, while a Kafka consumer reads data from the cluster.

Producers and consumers are decoupled from one another, meaning consumers don’t know about the producers producing the data they’re reading.

28. What is the Confluent Replicator?

The Confluent Replicator is a tool that allows for operating clusters between data centres or cloud regions.

29. What is Kafka Mirror Maker, and how does it work?

Kafka Mirror Maker is a tool that allows you to replicate data between Kafka clusters. It can be used to create a copy of a Kafka cluster in another data centre or cloud provider, allowing you to maintain high availability and disaster recovery options.

30. What is Kafka Connect, and how does it work?

Kafka Connect is a tool that allows you to build real-time data pipelines between Apache Kafka and other systems like HDFS, S3, Elasticsearch, and MySQL.

It can be used to ingest and transform data from other systems into Kafka or to export data from Kafka to other systems.

31. What is a Kafka producer?

A Kafka producer is an application within the cluster that takes rights and manages its partitions.

32. What is a Kafka consumer?

A Kafka consumer is a program that reads from topics and pulls messages from them.

33. What is Kafka String Processing, and how does it work?

Kafka String Processing is a client library for building mission-critical real-time applications and microservices using Apache Kafka.

It provides a set of high-level APIs for processing and transforming data in real time, making it easy to build complex streaming applications.

34. What is the difference between a Kafka partition and a Kafka topic?

A Kafka partition is a log with strict ordering, while a Kafka topic is a collection of related messages or events.

35. What is the difference between a Kafka command line tool and a Kafka producer?

A Kafka command line tool is used for quick visibility and scripting, while a Kafka producer is an application within the cluster that takes rights and manages its partitions.

36. What is the difference between a Kafka consumer and a non-Java language support?

A Kafka consumer is a program that reads from topics and pulls messages from them. At the same time, non-Java language support is a rest proxy that allows communication with the Kafka cluster.

37. What is at least once processing in Kafka?

At least once, processing ensures that all events get through, even if some messages might get lost or duplicated.

38. What is the role of the zookeeper in the Kafka cluster?

Zookeeper is a distributed system that stores authorisation information and access control lists. When a broker fails, it manages the replication of a topic, which is then replicated in other parts of the cluster.

39. What is the atomic broadcast problem in distributed messaging?

The atomic broadcast problem proves that delivery in a distributed messaging system is impossible exactly once.

40. What is the purpose of partition reallocation in Kafka when the composition of the group changes?

To automatically re-allocate partitions for each consumer in a Kafka cluster.

41. Why is state management critical in Kafka?

State management is essential for maintaining elasticity and fault tolerance in the consumer.

42. What is the purpose of encrypting data in Kafka?

Data is encrypted from client to broker and broker to Zookeeper in Kafka to ensure security.

43. What is the role of the schema registry in Kafka?

The schema registry connects processes outside the cluster, allowing producers and consumers to serialise and de-serialize messages with new schemas.

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44. What is the role of the Confluent REST proxy in Kafka?

The Confluent REST proxy is a REST wrapper around the producer and consumer, allowing for an HTTP interface and exposing administrative capabilities over the same interface.

45. What is schema evolution in Kafka?

Schema evolution refers to changes in the schema of messages in a Kafka topic.

46. How can schema evolution be managed in Kafka?

Schema evolution can be managed using the schema registry, which allows for independent versioning of producers and consumers and compatibility with old data in old versions.

47. What are the three types of Kafka streams?

The three types of Kafka streams are producer and consumer, assembly languages, and Kafka streams, which are more opinionated and accessible to deploy.

48. What is the Kubernetes operator?

The Kubernetes operator is a tool that allows for running the Confluent Platform natively in Kubernetes.

50. What is Confluent CLI?

Confluent CLI is a command line tool that allows users to manage their Confluent Platform or Confluent Cloud deployment, including role-based access control.

51. What is the Complement Operator in the Confluent Platform?

The Complement Operator is an outstanding Kafka operator that supports all other elements of the Confluent Platform, including managing persistent volumes, security integration, automatic rolling upgrades, configuration updates, and elastic scaling of Kafka.

52. What is Confluent Platform?

Confluent Platform is a comprehensive solution for organisations adopting events streaming, managing data, and deploying Kafka across various industries.

53. What are the benefits of using Confluent Platform?

The benefits of using the Confluent Platform include a broader connector ecosystem, support for various data sources, and a smooth transition to the cloud.

54. What industries are using Kafka?

Kafka is increasingly used in various industries, including banking, healthcare, online gaming, government, and financial services.

55. What are some benefits of using Kafka in various industries?

The benefits of using Kafka in various industries include improved efficiency, reduced engineering effort, and faster, more efficient customer experiences.

Our extensive blog of top MCQ questions will help you confidently answer any interview question!

1. What system was Kafka developed?

a) Netflix

b)

c) Google

d) Facebook

2. How are data pipelines advantageous in real-time scenarios?

a) Eliminates the need for messaging systems

b) Stores data statically

c) Slows down data transfer

d)

3. What feature of messaging systems allows them to send data across platforms and languages?

a) Data visualisation capabilities

b) Distributed computing

c) Real-time analytics

d)

4. Which method does Kafka NOT follow?

a) Polling

b)

c) Multiplexing

d) Pub-sub

5. What does Kafka do with the data to ensure no data loss?

a) Storage data across decentralised databases

b) Collects data on an individual topic basis

c) Encrypts all data at rest

d)

6. What critical function does Kafka’s stream processor perform?

a) Encrypts streams for data security

b)

c) Translates data between different formats

d) Compresses stream data to save space

7. How does Kafka treat partitions in logs?

a) Uses them as backup storage

b)

c) Deletes them after consumption

d) As mutable sequences

8. Which component of Kafka maintains leadership for each partition?

a) Controller

b) Broker

c) Consumer

d)

9. What does Kafka allow for when creating a topic?

a) Setting a maximum message size

b)

c) Customizing consumer subscriptions

d) Choosing a unique encryption algorithm

10. What does the term ‘Kafka Streams’ refer to?

a)

b) Kafka’s messaging protocol

c) A type of Kafka broker

d) A stream of authentication data

11. What is required to install Kafka?

a) Python and Apache Hadoop

b) PHP and MySQL

c) C++ and Microsoft SQL Server

d)

This blog provided you with both fundamental knowledge of Kafka as well as advanced topics so you could grasp and confidently address any Interview Questions on Apache Kafka.

Practice these interview questions to expand your knowledge and improve your odds for Kafka interviews.

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