Apache Kafka for Developers

In this course, you will gain a practical and in-depth understanding of Apache Kafka — the leading platform for real-time data streaming, messaging and event-driven architectures. You will learn how Kafka works under the hood, how to build scalable streaming applications, and how to integrate Kafka into modern data platforms and microservice ecosystems. Through hands-on labs, you will set up producers, consumers, connectors and stream processors, and learn how to design reliable, high-throughput pipelines.

What you learn

• The fundamentals of Apache Kafka and why it is ideal for real-time data streaming.

• Core concepts: producers, consumers, topics, partitions, offsets and consumer groups.

• Architectures for scalability, reliability and fault tolerance.

• Working with Kafka Connect for efficient data movement and database integrations.

• Real-time stream processing with the Kafka Streams API.

• Using Kafka in microservices and event-sourcing patterns.

• Advanced development concepts: exactly-once semantics, log compaction and Kafka Raft.

After this course you will be able to:

• Independently set up and operate Kafka clusters and clients.

• Build robust streaming applications using producers, consumers and Kafka Streams.

• Integrate Kafka into existing systems using best-practice architectures.

• Move data efficiently using Kafka Connect and schema management.

• Apply event-driven design patterns in microservice environments.

• Design scalable, production-ready real-time data pipelines.

For whom

• Data engineers and data architects implementing scalable streaming solutions.

• Software engineers working with microservices or event-driven architectures.

• Organizations adopting Kafka for real-time analytics, data integration or data movement.

• Anyone wanting to master real-time data processing with Apache Kafka.

Prerequisites

• Basic programming experience (e.g., Python, Java or similar).

• Familiarity with distributed systems or data processing is useful.

• No prior Kafka experience required.

Content (global program)

Part 1

• Introduction to Kafka and real-time data streaming.

• Core concepts: producers, consumers, topics and partitions.

Part 2

• Architecture & integration.

• Scalability, reliability, replication and fault tolerance.

Part 3

• Kafka Connect.

• Source & sink connectors, database integration, schema evolution.

Part 4

• Kafka Streams.

• Stateful processing, windows and real-time transformations.

Part 5

• Kafka in microservices.

• Event sourcing, messaging patterns and best practices.

Part 6

• Advanced concepts.

• Exactly-once semantics, log compaction, Kafka Raft.

Part 7

• Best practices & Q&A.