Kafka Fundamentals for Java Developers

• An understanding of core Java programming
• Basic knowledge of distributed systems and messaging systems
• Familiarity with software development tools such as Maven or Gradle

Audience

• Java developers looking to integrate Kafka into their applications
• Software engineers working with event-driven architectures
• Developers interested in learning Kafka as a distributed messaging system

Kafka is a distributed event streaming platform used for high-performance data pipelines, real-time analytics, and event-driven architectures.

This instructor-led, live training (online or onsite) is aimed at intermediate-level Java developers who wish to integrate Apache Kafka into their applications for reliable, scalable, and high-throughput messaging.

By the end of this training, participants will be able to:

• Understand the architecture and core components of Kafka.
• Set up and configure a Kafka cluster.
• Produce and consume messages using Java.
• Implement Kafka Streams for real-time data processing.
• Ensure fault tolerance and scalability in Kafka applications.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Apache Kafka

• What is Kafka and why use it?
• Core components: Topics, Partitions, Producers, Consumers, Brokers
• Understanding Kafka’s publish-subscribe model
• Use cases of Kafka in real-world applications

Setting Up a Kafka Development Environment

• Installing and configuring Kafka and ZooKeeper
• Kafka CLI tools for topic management
• Configuring Kafka for high availability

Kafka Producers and Consumers

• Creating Kafka Producers in Java
• Producing messages with keys, partitions, and acknowledgments
• Creating Kafka Consumers in Java
• Consumer groups and offset management

Working with Kafka Streams

• Introduction to Kafka Streams API
• Processing real-time data streams
• Stateful vs. stateless processing
• Windowing, joins, and aggregations

Ensuring Reliability and Performance

• Kafka replication and fault tolerance
• Optimizing producer and consumer configurations
• Monitoring Kafka performance

Kafka Security and Authentication

• Enabling SSL/TLS encryption
• Configuring authentication with SASL
• Role-based access control with Kafka ACLs

Integrating Kafka with Other Systems

• Using Kafka Connect to integrate with databases
• Connecting Kafka with Elasticsearch, PostgreSQL, and other data sources
• Building event-driven microservices with Kafka

Summary and Next Steps