AD483 Developing Event-Driven Applications with Apache Kafka and Red Hat AMQ Streams with exam Course Overview

AD483 Developing Event-Driven Applications with Apache Kafka and Red Hat AMQ Streams with exam Course Overview

Learn to use Kafka and AMQ Streams to design, develop, and test event-driven applications. Event-driven microservices scale globally, store and stream process data, and provide low-latency feedback to customers.

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AD483 Developing Event-Driven Applications with Apache Kafka and Red Hat AMQ Streams with exam

Target Audience for AD483 Developing Event-Driven Applications with Apache Kafka and Red Hat AMQ Streams with exam

AD483 is a comprehensive course designed for application developers to master the creation and management of event-driven applications using Apache Kafka and Red Hat AMQ Streams.


  • Application Developers
  • Software Engineers
  • DevOps Engineers
  • Data Engineers
  • System Architects
  • Cloud Developers
  • Microservices Developers
  • Technical Leads
  • IT Professionals looking to specialize in event-driven architectures
  • Students in Computer Science or IT-related fields
  • Development Managers
  • Technical Trainers and Educators
  • Solutions Architects
  • Product Managers in tech firms
  • Data Analysts interested in streaming data solutions


Learning Objectives - What you will Learn in this AD483 Developing Event-Driven Applications with Apache Kafka and Red Hat AMQ Streams with exam?

Course Introduction:
The AD483 course focuses on developing event-driven microservice applications using Apache Kafka and Red Hat AMQ Streams. Participants will gain practical skills in designing, building, and troubleshooting scalable applications.

Learning Objectives and Outcomes:

  • Understand the principles of event-driven applications.
  • Gain foundational knowledge of Kafka and AMQ Streams concepts.
  • Build applications with basic read-and-write messaging capabilities.
  • Leverage the Streams API to create data streaming applications.
  • Develop asynchronous services using the event collaboration pattern.
  • Integrate data systems with Kafka Connect and react to data changes using Debezium.
  • Troubleshoot common issues in Kafka and AMQ Streams applications.
  • Design and implement event-driven microservices that scale globally.
  • Store and process data using streaming techniques.
  • Provide low-latency feedback to customers through efficient microservice architecture.

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