Developing Event-Driven Applications with Apache Kafka and Red Hat AMQ Streams with Exam Classroom Training in United States of America

• Application developers with microservice development experience.
• Experience with microservice application development and design, such as DO378 or equivalent experience.
• OpenShift experience is recommended, but not required.

Impact on the organization

Organizations are recognizing that traditional synchronous applications are not able to scale consistently and adjust to the massive amounts of data from customers while still meeting customers’ expectations of immediate results. With event-driven applications using Kafka and AMQ Streams, organizations can expect to be able to globally scale their applications, store and stream process data, and provide feedback to customers with extremely low latency.

Impact of this training

As a result of attending this course, students will understand the architecture of Kafka and AMQ Streams and will be able to identify proper use cases for event-driven applications. In addition to learning the fundamental principles and features of Kafka and AMQ Streams, Students will learn how to design, develop, and test event-driven applications.

Students should be able to demonstrate the following skills:

• Design, build, and use event-driven applications for relevant scenarios with standard patterns.
• Detect and react to data changes with Debezium to improve application performance.
• Troubleshoot common problems with event-driven applications.

Designing Event-Driven Applications

Describe the principles of event-driven applications.

Introducing Kafka and AMQ Streams Concepts

Build applications with basic read-and-write messaging capabilities.

Building Applications with the Streams API

Leverage the Streams API to create data streaming applications.

Creating Asynchronous Services with Event Collaboration

Create and migrate to asynchronous services using the event collaboration pattern.

Integrating Data Systems with Kafka Connect

Connect data systems and react to data changes using Kafka Connect and Debezium.

Troubleshooting AMQ Streams Applications

Handle common problems in Kafka and AMQ Streams applications.