The Kafka APIs are a collection of interfaces that allow you to interact with Kafka in various ways—producing messages, consuming messages, real-time data processing, and administrative tasks. Here, we’ll cover four main APIs: Producer, Consumer, Streams, and Admin.

Overview of Kafka APIs

Kafka APIs provide a way to interact programmatically with the Kafka ecosystem. Understanding these APIs is crucial for any developer working with Kafka.

Producer API: Sending Data to Kafka

The Producer API allows you to publish records to Kafka topics. Key methods include send() for asynchronous sends and flush() for ensuring all sent records have been transmitted.

  • Key Methods:

    • send(): Sends a record to a topic.
    • flush(): Waits for buffered records to be sent.
  • Configurations:

    • bootstrap.servers: List of brokers.
    • key.serializer: Serializes the key.
    • value.serializer: Serializes the value.

Consumer API: Reading Data from Kafka

The Consumer API lets you subscribe to topics and consume records. It’s capable of subscribing to multiple topics and consuming data in a distributed manner.

  • Key Methods:

    • poll(): Polls for new data.
    • subscribe(): Subscribes to one or more topics.
  • Configurations:

    • bootstrap.servers: List of brokers.
    • key.deserializer: Deserializes the key.
    • value.deserializer: Deserializes the value.

Streams API: Real-Time Data Processing

Kafka Streams API allows for real-time data transformation and processing. It’s a client library that processes Kafka messages.

  • Key Points:

    • Processes data in real-time.
    • Stateless and stateful operations.
    • Easily scalable and distributed.
  • Key Concepts:

    • KStream: Represents a stream of records.
    • KTable: Represents a changelog stream.
  • Operations:

    • map(), filter(), join(), etc.

Admin API: Managing Kafka Resources

The Admin API enables programmatic management of Kafka resources like topics, brokers, and configurations.

  • Key Points:

    • Create, delete, and list topics.
    • Fetch metadata and configurations.
    • Control ACLs (Access Control Lists).
  • Key Methods:

    • createTopics(): Creates one or more new topics.
    • describeTopics(): Describes the specified topics.


  1. What is the purpose of Kafka Producer API’s flush() method?
  2. What does the poll() method do in the Kafka Consumer API?
  3. Can a Kafka consumer subscribe to multiple topics?
  4. How can you force all sent messages to be transmitted in Kafka Producer API?
  5. What is the primary function of Kafka Streams API?
  6. What kind of operations can you perform using Kafka Admin API?
  7. Name the method used for sending messages asynchronously in Kafka.
  8. What is the difference between stateless and stateful operations in Kafka Streams?
  9. What configuration in Kafka Consumer API is used for committing offsets automatically?
  10. Can Kafka Admin API control ACLs? If yes, how?
  11. How does a Kafka Producer know which partition to send a message to?
  12. Can you name a configuration setting that can be adjusted for a Kafka Producer for better throughput?
  13. What happens if a Kafka Consumer fails? How does Kafka handle it?
  14. Is it possible to consume messages from a specific partition using Kafka Consumer API?
  15. How do you handle errors or exceptions in Kafka Streams API?
  16. How would you change the replication factor of a topic using Kafka Admin API?
  17. What method in the Producer API is used to send messages synchronously?
  18. Can Kafka Streams API perform windowed operations? If yes, name one.
  19. How do you describe the durability settings of a Kafka Producer?
  20. In Kafka Streams API, what is the significance of the KStream and KTable abstractions?
  21. What are some common use-cases where Kafka Admin API would be helpful?
  22. What is the default partitioning strategy in Kafka Producer API?
  23. What is the role of the Deserializer class in Kafka Consumer API?
  24. Can you dynamically change the configurations of a Kafka broker using Admin API?
  25. How can Kafka Streams API be scaled horizontally?


  1. The flush() method ensures that all sent messages have been transmitted to the broker.
  2. The poll() method fetches records from the broker.
  3. Yes, a Kafka consumer can subscribe to multiple topics.
  4. By using the flush() method.
  5. The primary function is real-time data processing.
  6. You can create, delete, and list topics, among other things.
  7. send() method.
  8. Stateless operations are those that don’t depend on the state, while stateful operations keep track of state.
  9. auto.commit.enable.
  10. Yes, it can control ACLs by setting and fetching access control rules.
  11. It uses a partitioning strategy, which can be round-robin, hash-based, or custom.
  12. can be adjusted for better throughput.
  13. If a consumer in a consumer group fails, Kafka reassigns the partitions to other consumers in the same group.
  14. Yes, using the assign method, you can consume messages from a specific partition.
  15. Using try-catch blocks or configuring a DeserializationExceptionHandler.
  16. You can use the alterTopics method in the Admin API.
  17. By calling send() and then get() methods together.
  18. Yes, it can perform windowed operations like windowedBy(TimeWindows.of()).
  19. Durability can be controlled by setting the acks configuration.
  20. KStream is for stream-based processing, and KTable is for table-based (stateful) operations.
  21. Creating or deleting topics, altering configurations, and setting ACLs.
  22. The default is round-robin.
  23. Deserializer class is used to deserialize the byte array data back into objects.
  24. Yes, using the alterConfigs method.
  25. By adding more instances of the application, as each instance will take over some of the partitions.