Gain insights into Apache Kafka’s architecture, Client APIs, stream processing, and connectors. Discover hands-on techniques for building real-time data streaming and event-driven applications. Explore Kafka's core ecosystem.

build.tar.gz

producer-sync-example

producer-async-example

part1-dsl-api-stateful-ops

part2-dsl-api-stateful-ops

part3-dsl-api-stateful-ops

interactive-queries

testing-kafka-streams

spring-kafka

spring-kafka-consumer

consumer-api-example

queue-topic-example

consumer-api-config-example

kafka-connect-transformations-example

kafka-connect-sink-example

kafka-connect-source-example

kafka-schema-registry-example

Apache Kafka is a distributed streaming platform designed to handle real-time data streaming and processing in a distributed and fault-tolerant manner. This course can be taken by software developers and data engineers wanting to learn Kafka to build data-intensive applications. 

You will begin with an introduction to the Kafka architecture, client libraries, and its project ecosystem. Next, you will learn to use the Kafka Client APIs along with key configurations. Then, you will learn to develop stream processing applications using Kafka Streams. You will also explore the Kafka Connect Source and Sink connectors. You will finish by learning to make Kafka-related projects in addition to the core ecosystem. 

After completing this course, you will be comfortable with developing data-intensive applications. The course will prove helpful for anyone who wants to learn Kafka using a practical, hands-on approach for building real-time data streaming, event-driven architecture, microservices, and log aggregation.

Mastering Apache Kafka

**(True or False)** The `KafkaTemplate` abstraction is used to consume data from Kafka.

(True or False) The <code>KafkaTemplate</code> abstraction is used to consume data from Kafka.

The `MessageListenerContainer` interface and `@KafkaListener` annotation are used in Spring Kafka to consume messages.

The `MessageListenerContainer` interface is a high-level component.

Along with a `@KafkaListener` method, you also need to write a `MessageListenerContainer` implementation to receive data from Kafka.

There are two `MessageListenerContainer` implementations.

**(Select all that apply.)** Which is *true* about the `MessageListenerContainer` interface and `@KafkaListener` annotation? 

(Select all that apply.) Which is true about the <code>MessageListenerContainer</code> interface and <code>@KafkaListener</code> annotation?

**(True or False)** Confluent Schema Registry can only handle the Avro data type.

(True or False) Confluent Schema Registry can only handle the Avro data type.

Schema retrieval during the producer operation

Which Schema Registry feature allows different versions of the schema to be used by different producers and consumers?

Which Schema Registry feature allows different versions of the schema to be used by different producers and consumers?

**(True or False)** MirrorMaker 2.0 does not use the Kafka Connect framework.

(True or False) MirrorMaker 2.0 does not use the Kafka Connect framework.

Test your understanding of the Kafka ecosystem projects.

Introduction

Apache Kafka Producer API

Apache Kafka Consumer API

Kafka Streams

Kafka Connect

Exploring Projects in the Kafka Ecosystem

Wrap Up

Final Project

Quiz: Kafka Ecosystem