Apache Kafka – Stream data processing

Why take this course

If you want to master Apache Kafka and build real-time systems, this training is for you. You’ll gain a practical approach to stream processing, learn the platform’s key mechanisms, and understand the principles of building a streaming architecture.

What you'll learn

• A practical approach to stream processing.
• The key mechanisms of the Apache Kafka platform.
• How to understand the programming environment.
• The principles of building a streaming architecture.
• How to create applications using Apache Kafka.
• How to install and manage the Apache Kafka platform.
• How to process data using streams.

Certification & Exam

Upon completion the training, you will receive certificate of participation, confirming your skills in Apache Kafka stream data processing. There is no final exam—all you need is active participation in the classes.

Who is this course for

This course is designed for anyone involved in the software development process, members of project teams, as well as developers who understand the principles of object-oriented or functional programming in Java or Scala.

Topics covered

•  Apache Kafka platform – architecture
  • Platform construction
  • Details of platform operation
•  Installation
  • Preparation of the development environment
  • Installation and configuration of the Apache Kafka broker
  • Docker with Apache Kafka
  • Preparation of the production environment
  • Construction and configuration of the Apache Kafka cluster
• Administration and monitoring
  • Basic broker management
  • Partition management
  • Metrics and monitoring of brokers
•  Kafka Producers
  • Configuration
  • Synchronous and asynchronous sending of messages
  • Serializers and work with partitions
• Kafka Consumers
  • Configuration
  • Reading messages
  • Offset and Commit management
• Kafka Streams
  • The concept of stream processing
  • Project patterns
  • Architecture of Apache Kafka Streams
• Practical exercises – building a sample application.