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Kafka Streams Course Overview

Kafka Streams Course Overview

Our Kafka Streams course at Koenig Solutions provides an in-depth exploration of Apache Kafka Streams, perfect for those with a basic knowledge of Java and Apache Kafka. Over four intensive days, you'll delve into its architecture, core concepts, and practical applications. You will gain hands-on experience by developing, deploying, and managing real-time stream processing applications. Topics covered include Kafka Streams Basic Operations, Joins, Stateful Operations, and Exactly Once Semantics. By the end of the course, you'll be proficient in building efficient stream processing applications, ensuring you can handle real-time data with ease. Join us to master Kafka Streams and elevate your data processing skills!

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  • Live Training (Duration : 32 Hours)
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Course Prerequisites

Minimum Prerequisites for Kafka Streams Course:


  • Basic Knowledge of Java: Understanding of core Java concepts such as data types, loops, conditionals, exceptions, collections, and basic object-oriented programming principles.
  • Familiarity with Apache Kafka: Basic understanding of Apache Kafka, including topics, producers, and consumers, as well as a general overview of how Kafka works.

These prerequisites ensure that learners have a foundational understanding needed to grasp the concepts and participate in hands-on labs throughout the Kafka Streams course.


Target Audience for Kafka Streams

Kafka Streams course provides a comprehensive understanding of Apache Kafka Streams, from foundational concepts to advanced operations, for efficient stream processing and real-time data handling.


  • Java Developers
  • Software Engineers
  • Data Engineers
  • Big Data Developers
  • System Architects
  • IT and Data Analytics Managers
  • DevOps Professionals
  • Solution Architects
  • Technical Leads
  • Data Scientists
  • Enterprise Architects
  • Integration Specialists


Learning Objectives - What you will Learn in this Kafka Streams?

1. Brief Introduction:

The Kafka Streams course offers an in-depth understanding of Apache Kafka Streams, from foundational concepts to advanced operations, empowering you to develop, deploy, and manage efficient real-time stream processing applications.

2. Learning Objectives and Outcomes:

  • Understand the fundamental concepts of Apache Kafka Streams and its architecture.
  • Learn to differentiate Kafka Streams from other stream processing libraries like Spark Streaming, NiFi, and Flink.
  • Master core Kafka Streams operations including KTable, Joins, Serialization, and Windowing.
  • Develop your first Kafka Streams application from scratch and perform basic and advanced operations.
  • Explore stateful operations, state management, and interactive queries in Kafka Streams.
  • Implement exactly-once semantics in Kafka Streams to ensure data consistency.
  • Perform various KStream and KTable transformations and understand their duality.
  • Handle errors and implement fault tolerance for stateful stream processing applications.
  • Gain practical experience through hands-on labs, including setting up projects, debugging, and achieving graceful shutdowns.
  • Learn how to perform different types of joins, including Inner Join, Left Join, and Outer Join with Global KTables.

Target Audience for Kafka Streams

Kafka Streams course provides a comprehensive understanding of Apache Kafka Streams, from foundational concepts to advanced operations, for efficient stream processing and real-time data handling.


  • Java Developers
  • Software Engineers
  • Data Engineers
  • Big Data Developers
  • System Architects
  • IT and Data Analytics Managers
  • DevOps Professionals
  • Solution Architects
  • Technical Leads
  • Data Scientists
  • Enterprise Architects
  • Integration Specialists


Learning Objectives - What you will Learn in this Kafka Streams?

1. Brief Introduction:

The Kafka Streams course offers an in-depth understanding of Apache Kafka Streams, from foundational concepts to advanced operations, empowering you to develop, deploy, and manage efficient real-time stream processing applications.

2. Learning Objectives and Outcomes:

  • Understand the fundamental concepts of Apache Kafka Streams and its architecture.
  • Learn to differentiate Kafka Streams from other stream processing libraries like Spark Streaming, NiFi, and Flink.
  • Master core Kafka Streams operations including KTable, Joins, Serialization, and Windowing.
  • Develop your first Kafka Streams application from scratch and perform basic and advanced operations.
  • Explore stateful operations, state management, and interactive queries in Kafka Streams.
  • Implement exactly-once semantics in Kafka Streams to ensure data consistency.
  • Perform various KStream and KTable transformations and understand their duality.
  • Handle errors and implement fault tolerance for stateful stream processing applications.
  • Gain practical experience through hands-on labs, including setting up projects, debugging, and achieving graceful shutdowns.
  • Learn how to perform different types of joins, including Inner Join, Left Join, and Outer Join with Global KTables.