This course teaches learners how to work with Kafka Streams using Spring Cloud, focusing on real-time stream processing. By the end of the course, students will be able to install and run Kafka on different operating systems, create Kafka Streams projects, produce JSON and AVRO messages, implement stream processing requirements, handle errors and exceptions, work with KTables, compute streaming aggregates, perform joins in Kafka Streams, and implement complex aggregations. The course uses a combination of theoretical explanations, practical examples, and hands-on exercises. It is designed for Spring Boot developers interested in leveraging Apache Kafka for stream processing applications.
Overview
Syllabus
Kafka Streams using Spring Cloud | Learn Apache Kafka for Spring Boot Developers.
Kafka Streams using Spring Cloud Streams | Who should learn take course | Course Prerequisite.
Installing and Running Spring Kafka | Spring Kafka Development Environment.
Kafka Spring Boot Starter Project | Initializing Spring Kafka Project | Kafka Project in Gradle.
Installing Confluent Kafka on Windows | Setup Kafka cluster in WSL2 | Windows sub system for Linux.
Kafka Streams Project | Creating and Running Kafka Streams using Spring Cloud on windows machine.
Installing Kafka on Mac | Confluent Kafka on Mac | Setup your Kafka Development Environment on Mac.
Creating Kafka Streams project on Mac | Kafka Streams using Spring Cloud Streams on Mac machine.
Kafka Support in Spring | Spring Boot Vs Spring Cloud Vs Spring Cloud Stream Vs Spring Kafka Streams.
Spring Cloud Architecture | Introduction to Spring Cloud Streams for real-time stream processing.
How Kafka Streams work in Spring Cloud | What is Kafka Streams | Kafka Streams Vs Spring Cloud.
Simple RESTful Kafka Producer.
Creating Retail POS Simulator.
Producing JSON Messages.
Producing AVRO Messages.
Real time Stream Processing Requirement.
Implementing POS Fanout JSON to Avro.
Real life Serialization Scenarios.
Processing AVRO message Stream.
Understanding Record Serialization.
Overview of KStream Methods.
Kafka Streams Exactly Once Implementation.
Implementing Exactly Once.
Let's Practice - A Complex Problem Statement.
Working with XML Inputs.
Handling Errors and Exceptions.
Mixed Branching of a KStream.
Handling Poison Pills.
Introducing KTable.
Deep Dive into KTable.
Computing Streaming Aggregates.
Aggregation Concepts.
Reducing A Kafka Stream.
Aggregating a Kafka Stream.
Aggregation Challenges.
KTable Aggregation.
Kafka Time Semantics.
Windowing Aggregates.
Tumbling Window Vs Hopping Time Window.
Session Window and Grace Period.
Joins in Kafka Stream.
KStream to KStream Joins.
KTable to KTable Join.
KStream to KTable Join.
Implementing Complex Aggregation.
Super Simple Stream Listener.
Unit Testing Stream Listeners.
Converting Stream Listener to Functional Style.
Epilog.
Taught by
Learning Journal
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