Top 50 FAQs for Kafka

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1. What is Apache Kafka?

Apache Kafka is an open-source distributed event streaming platform used for building real-time data pipelines and streaming applications.

2. What are the key components of Kafka?

The main components include Producers, Brokers (Kafka servers), Topics, Partitions, Consumers, and Zookeeper for coordination.

3. How does Kafka ensure fault tolerance?

Kafka achieves fault tolerance through replication. Each partition has multiple replicas distributed across different brokers.

4. What is a Kafka Topic?

A Kafka topic is a category or feed name to which messages are published by producers and from which consumers consume messages.

5. What is a Kafka Partition?

A partition is a unit of parallelism and scalability in Kafka. Each partition is a sequence of records, and a topic can have multiple partitions.

6. What is a Kafka Broker?

A Kafka broker is a Kafka server that stores data, receives and serves requests from producers and consumers, and participates in replication.

7. How does Kafka handle message ordering?

Kafka guarantees order at the partition level. Messages within a partition are strictly ordered, but across partitions, there is no guaranteed order.

8. What is a Kafka Consumer Group?

A consumer group is a set of consumers that jointly consume a topic. Each partition is consumed by only one consumer within a group.

9. What is Zookeeper’s role in Kafka?

Zookeeper is used for distributed coordination and maintains metadata about Kafka brokers, topics, and partitions.

10. How does Kafka ensure high throughput?

Kafka achieves high throughput by utilizing a distributed and partitioned architecture, allowing parallel processing of messages across multiple partitions.

11. What is Kafka Producer API?

Kafka Producer API is a set of APIs that allows producers to send messages to Kafka topics.

12. What is Kafka Consumer API?

Kafka Consumer API is a set of APIs that allows consumers to subscribe to Kafka topics and process messages.

13. What is the purpose of Kafka Connect?

Kafka Connect is a framework for building and running connectors, which are used to import/export data between Kafka and other data systems.

14. What is the role of Schema Registry in Kafka?

Schema Registry is used for storing and managing Avro schemas, ensuring compatibility and consistency in message formats.

15. How does Kafka handle message retention?

Kafka allows configurable retention periods for messages in topics. Messages older than the specified retention period are deleted.

16. What is the role of Kafka Streams?

Kafka Streams is a library for building stream processing applications on top of Kafka, allowing real-time data processing.

17. How does Kafka handle message durability?

Kafka ensures durability by replicating messages across multiple brokers. Replicas can take over if a broker fails.

18. What is the significance of the offset in Kafka?

The offset is a unique identifier assigned to each message in a partition. It is used to track the progress of consumers in a topic.

19. How to achieve exactly-once semantics in Kafka?

Kafka provides exactly-once semantics through idempotent producers and transactional capabilities.

20. What is the role of the Kafka Controller?

The Kafka Controller is responsible for managing leadership election and coordinating activities among brokers.

21. How does Kafka handle data serialization?

Kafka supports different serializers for key and value in messages. Common formats include Avro, JSON, and Protobuf.

22. What is the Kafka log compaction feature?

Log compaction is a feature that retains the latest record for each key in a Kafka topic, ensuring that the log doesn’t grow indefinitely.

23. How to handle message processing failures in Kafka?

Kafka provides mechanisms for handling failures, including retries, dead-letter queues, and monitoring for consumer lag.

24. What is the role of the Kafka MirrorMaker tool?

Kafka MirrorMaker is used for replicating data between Kafka clusters, either within the same data center or across different data centers.

25. How does Kafka handle data partitioning?

Kafka uses a hash-based partitioning mechanism to distribute data evenly across partitions within a topic.

26. What is the purpose of Kafka Headers?

Kafka Headers allow producers and consumers to attach key-value pairs of metadata to messages.

27. How to monitor Kafka performance?

Kafka can be monitored using tools like Kafka Manager, Burrow, and JMX metrics exposed by Kafka brokers.

28. How to configure Kafka for optimal performance?

Configurations like message size, replication factor, and number of partitions should be optimized based on use cases and requirements.

29. What is the role of Kafka ACLs (Access Control Lists)?

Kafka ACLs are used to control access to Kafka resources, such as topics, by defining user-specific permissions.

30. How to secure Kafka communication?

Kafka supports SSL/TLS encryption for securing communication between clients and brokers.

31. What is the Kafka Streams State Store?

Kafka Streams State Store is a local storage mechanism for maintaining state during stream processing applications.

32. How to scale Kafka consumers horizontally?

Consumers can be scaled horizontally by adding more instances and ensuring each instance subscribes to a subset of partitions.

33. How to handle schema evolution in Kafka with Avro?

Avro supports schema evolution, and Kafka consumers can handle different versions of Avro schemas using the Schema Registry.

34. What is the role of the Kafka Firehose connector?

The Kafka Firehose connector is used to stream data from Kafka topics to Amazon S3 for data archival.

35. How does Kafka handle backpressure?

Kafka handles backpressure by allowing consumers to process messages at their own pace and by leveraging the Kafka topic retention period.

36. What is the purpose of the Kafka REST Proxy?

Kafka REST Proxy provides a RESTful interface to produce and consume messages from Kafka topics, making integration with non-Java applications easier.

37. How to perform rolling restarts in a Kafka cluster?

Rolling restarts can be achieved by restarting Kafka brokers one at a time to ensure continuous availability.

38. What is the role of Kafka Liveness Probes?

Liveness probes are used to check the health of Kafka brokers in a Kubernetes environment and restart them if necessary.

39. How to handle data schema changes in Kafka?

Schema evolution or using a flexible schema format like Avro can help handle data schema changes in Kafka.

40. How to configure Kafka to store data on disk?

Kafka’s log segments are stored on disk, and you can configure parameters like log directory and retention policies.

41. What is Kafka’s At-Least-Once delivery semantics?

At-Least-Once delivery semantics in Kafka ensures that messages are guaranteed to be delivered but may result in duplicates.

42. How to handle Kafka rebalancing?

Kafka rebalancing occurs when the number of consumers in a consumer group changes, and it is automatically handled by Kafka.

43. What is the role of the Kafka Producer Acknowledgment?

Producer Acknowledgment settings define the level of acknowledgment required from brokers for successful message publishing.

44. How to perform rolling upgrades in a Kafka cluster?

Rolling upgrades can be done by upgrading Kafka brokers one at a time, ensuring compatibility between versions.

45. What is Kafka’s Exactly-Once delivery semantics?

Kafka’s Exactly-Once delivery semantics is achieved using transactional producers and consumer offsets stored in Kafka.

46. How does Kafka handle message durability?

Kafka ensures durability by replicating messages across multiple brokers. Replicas can take over if a broker fails.

47. What is the role of Kafka Streams KTables?

Kafka Streams KTables represent the latest value for each key in a stream.

48. How to handle Kafka Zookeeper dependency?

Kafka 2.8.0 and later versions no longer have a strict dependency on Zookeeper for basic operations.

49. What is the purpose of the Kafka Lag Exporter?

Kafka Lag Exporter is used to monitor consumer lag in Kafka consumer groups.

50. How to configure Kafka for high availability?

High availability can be achieved by configuring multiple Kafka brokers with replication, ensuring no single point of failure.

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