Kafka Interview Questions and Answers for experienced

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100 Kafka Interview Questions and Answers

  1. What is Apache Kafka?

    • Answer: Apache Kafka is a distributed, fault-tolerant, high-throughput, low-latency streaming platform. It's used for building real-time data pipelines and streaming applications. It's essentially a highly scalable pub/sub messaging system built on a distributed commit log.

  2. Explain the core concepts of Kafka: brokers, topics, partitions, consumers, producers.

    • Answer: Brokers: Servers that store and manage data. Topics: Categorization of messages; a logical grouping of messages with a specific name. Partitions: Subdivisions of a topic to enable parallelism and scalability. Consumers: Applications that read messages from topics. Producers: Applications that write messages to topics.

  3. What are the benefits of using Kafka?

    • Answer: High throughput, low latency, fault tolerance, scalability, durability, real-time streaming capabilities, and ease of integration with other systems.

  4. Explain the different Kafka data storage mechanisms.

    • Answer: Kafka uses a distributed, replicated commit log. Data is persisted to disk for durability and is replicated across multiple brokers for fault tolerance. Each partition is sequentially appended, ensuring ordered delivery within a partition.

  5. How does Kafka achieve fault tolerance?

    • Answer: Through replication. Each partition is replicated across multiple brokers. If one broker fails, other replicas can take over, ensuring continuous operation and data availability.

  6. Describe the different consumer groups in Kafka.

    • Answer: Consumer groups allow parallel consumption of messages from a topic. Each consumer group subscribes to a topic, and messages are distributed among consumers within the group. Different consumer groups can consume the same topic concurrently.

  7. Explain Kafka's ZooKeeper integration.

    • Answer: ZooKeeper is used by Kafka for broker discovery, leader election, and configuration management. It maintains the cluster state and metadata, enabling dynamic scaling and fault tolerance.

  8. What are the different Kafka message formats?

    • Answer: Kafka supports various message formats, including Avro, JSON, and Protobuf. Avro is particularly popular due to its schema evolution capabilities.

  9. How does Kafka handle message ordering?

    • Answer: Kafka guarantees message ordering within a partition. However, across multiple partitions, ordering is not guaranteed.

  10. Explain the concept of Kafka's log compaction.

    • Answer: Log compaction reduces storage space by removing duplicate messages. It's particularly useful for storing state information where only the latest value is relevant.

  11. How do you monitor Kafka performance?

    • Answer: Using tools like Kafka Manager, Burrow, and Yahoo's Kafka monitoring tools. Key metrics to monitor include lag, throughput, consumer group offsets, and broker resource utilization.

  12. Describe different Kafka security mechanisms.

    • Answer: SASL/PLAIN, SSL/TLS encryption for secure communication, and access control lists (ACLs) for authorization.

  13. How to handle schema evolution in Kafka?

    • Answer: Using schema registries like Confluent Schema Registry, which allow for backward and forward compatibility of schemas.

  14. What are some common Kafka troubleshooting techniques?

    • Answer: Check logs, monitor metrics, use tools like `kafka-consumer-groups.sh` and `kafka-topics.sh`, and investigate consumer group lag.

  15. Explain the difference between Kafka and other message queues like RabbitMQ.

    • Answer: Kafka is designed for high-throughput streaming, while RabbitMQ is more suitable for general-purpose messaging. Kafka uses a distributed commit log, while RabbitMQ uses a more traditional message queue approach.

  16. How do you ensure exactly-once processing in Kafka?

    • Answer: Exactly-once processing is a complex problem. It generally involves idempotent consumers and transactions. True exactly-once is difficult to achieve, often settling for at-least-once with careful idempotency considerations.

  17. What are the different ways to deploy Kafka?

    • Answer: Standalone, ZooKeeper based cluster, and cloud-managed solutions like Confluent Cloud or Amazon MSK.

  18. Explain the concept of Kafka Streams.

    • Answer: Kafka Streams is a Java library for building stream processing applications using Kafka. It allows for stateful and stateless stream processing directly within the Kafka ecosystem.

  19. How do you handle dead-letter queues in Kafka?

    • Answer: By implementing custom error handling logic in consumers to redirect failed messages to a designated dead-letter queue topic for later investigation and retry.

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