10 most asked kafka

Certainly. Here are some common Apache Kafka interview questions:

1. What is Apache Kafka?

   • Apache Kafka is a distributed streaming platform designed for high-throughput, fault-tolerant, and scalable event streaming.

2. Explain the key components of Kafka architecture.

   • Kafka has four main components: Producers, Consumers, Brokers, and Zookeeper. Producers publish messages, Consumers subscribe to topics, Brokers manage the storage and distribution of messages, and Zookeeper is used for coordination.

3. What is a Kafka topic?

   • A topic in Kafka is a category or feed name to which records are published. It serves as a channel for organizing and categorizing the messages.

4. How does Kafka ensure fault tolerance?

   • Kafka ensures fault tolerance through replication. Each partition has multiple replicas distributed across different brokers, ensuring that if one broker fails, another can take over.

5. Explain the role of Zookeeper in Kafka.

   • Zookeeper is used for distributed coordination and synchronization in Kafka. It manages broker metadata, leader election, and maintains the overall health of the Kafka cluster.

6. What is the significance of partitions in Kafka?

   • Partitions allow Kafka to horizontally scale by distributing data across multiple brokers. Each partition can be replicated to provide fault tolerance and high availability.

7. Differentiate between Kafka and traditional message-oriented middleware (MOM).

   • Kafka is designed for high-throughput, durability, and horizontal scalability, whereas traditional MOM may have limitations in these aspects. Kafka uses a log-centric storage model, providing efficient data handling.

8. Explain the use of offset in Kafka.

   • An offset is a unique identifier assigned to each message within a partition. It helps track the position of consumers in a partition and enables reliable message processing.

9. What is the role of a consumer group in Kafka?

   • A consumer group is a set of consumers that work together to consume a topic. Kafka ensures that each partition is consumed by only one member of a consumer group at a time, enabling parallel processing.

10. How does Kafka handle message retention?

    • Kafka allows configuring retention policies for topics, specifying how long messages should be retained. Messages can be retained based on time or size, ensuring efficient resource utilization.

These questions cover fundamental aspects of Apache Kafka and its architecture, providing a basis for assessing a candidate's knowledge in a Kafka-related interview.

Certainly, here are examples of Apache Kafka code-based questions using the Node.js client library:

1. Producer Example:
   • Create a Kafka producer in Node.js to send messages to a topic.

   const { Kafka } = require('kafkajs');

   const kafka = new Kafka({
       clientId: 'example-producer',
       brokers: ['localhost:9092']
   });

   const producer = kafka.producer();

   const produceMessage = async () => {
       await producer.connect();
       await producer.send({
           topic: 'example_topic',
           messages: [
               { key: 'key', value: 'value' }
           ]
       });
       await producer.disconnect();
   };

   produceMessage();

1. Consumer Example:
   • Create a Kafka consumer in Node.js to subscribe to a topic and process messages.

   const { Kafka } = require('kafkajs');

   const kafka = new Kafka({
       clientId: 'example-consumer',
       brokers: ['localhost:9092']
   });

   const consumer = kafka.consumer({ groupId: 'example_group' });

   const consumeMessages = async () => {
       await consumer.connect();
       await consumer.subscribe({ topic: 'example_topic', fromBeginning: true });

       await consumer.run({
           eachMessage: async ({ topic, partition, message }) => {
               console.log(`Received message on partition ${partition}: ${message.value}`);
           }
       });
   };

   consumeMessages();

Ensure that you have the 'kafkajs' library installed in your Node.js project for these examples to work (npm install kafkajs). Adjust the broker addresses, topic names, and any other configurations according to your Kafka cluster setup and requirements.