Description
Kafka Streams API For Developers using Java/SpringBoot 3.X course. The Kafka Streams API is an advanced API that is part of the Kafka ecosystem. Using the Kafka Streams API, we can:
- apply data conversion,
- data enrichment,
- Split data into multiple data streams
- Collect data or join data from multiple Kafka topics.
- Aggregate data into window bins and more.
The Kafka Streams API For Developers using Java/SpringBoot program is designed to provide you with the theoretical and coding experience of developing Kafka Streams applications using the Streams API, as well as techniques for using standard Enterprise Kafka Streams applications using SpringBoot and Streams. Covers the API. This is a fully hands-on course where you will learn concepts through code. By the end of this course, you will have built a real-time Kafka Streams application. At the end of this course, you will have a complete understanding of these concepts:
- Building Kafka Streams applications using the Streams API
- Building Kafka Streams applications using SpringBoot & Streams API
- Write interactive queries to retrieve collected data from a state store and expose it via a RESTFUL API.
- Unit testing and integration of Kafka Stream applications using JUnit5
Getting Started with Kafka Streams
- In this section, I will give you all an introduction to Kafka Streams and the various terms involved in building a Kafka Streams application.
- An introduction to Kafka’s currents
- Kafka Streams Terminology – Topology and Processor
- Introduction to KStreams API
Hi Kafka Streams application using KStreams API
In this section, we will build a simple Kafka Streams application and test it locally.
- Training on the construction of the topology of the Greetings application
- Create a Kafka Streams startup program that we can use to start and stop the application.
Operators on Kafka Streams using the KStream API
In this section, we will explore some of the operators available in the Kafka Streams API.
- Filter & FilterNot
- Map/MapValues
- FlatMapValues/FlatMap
- peep
- merge
Serialization and deserialization in Kafka streams
In this section, we code and review serialization and deserialization in Kafka Streams.
- How does key/value serialization and deserialization work in Kafka Stream?
- Provide default serializer/deserializer using application configuration
- Create a custom serdes for advanced greeting messages
Generic reusable serializer/deserializer (recommended approach)
In this section, I’ll show you the best way to make a generic serializer and serializer that can be used for any message type.
- Create a generic serializer/serializer
Kafka Streams order management application – a real-time use case
In this section, we will build a Kafka Streams application by implementing an order management system for a retail company.
Topology, flow and tasks – under the hood
In this section, we will examine the internals of the Kafka Streams application.
- Internal topology, flow and tasks
Error/Exception Handling in Kafka Streams
In this section, we examine the various error handlers in Kafka Streams.
- Failure in Kafka Streams
- Default Deserialization error behavior
- Custom Deserialization error handler
- Default and custom processor error handlers
- Custom production error handler
What you will learn in the Kafka Streams API For Developers using Java/SpringBoot 3.X course
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Build advanced Kafka Streams applications using the Streams API
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Build a Kafka Streams application using the HighLevel DSL
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Exactly once processing- transactions and powerless producer
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Build a Realtime Retail Streaming application using the Streams API
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Aggregate multiple events into cumulative events
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Join multiple streams into one continuous stream
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Collect streams in the Events window group
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Build a standard Kafka Streams Enterprise application using SpringBoot
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Testing Kafka Stream using TopologyTestDriver using JUnit5
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Testing Spring Kafka streams using EmbeddedKafka and JUnit5
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Build interactive queries to retrieve collected data via RESTFUL APIs
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Interactive queries with multiple instances of the Kafka stream instance (MicroServices pattern)
This course is suitable for people who
- Advanced Java Developers
- Kafka developers who are curious to learn the Kafka Streams API
- Kafka developers interested in building advanced streaming applications
- Developers who want to learn Kafka Streams application testing techniques using TopologyTestDriver.
Course specification Kafka Streams API For Developers using Java/SpringBoot 3.X
- Publisher: Udemy
- teacher: Pragmatic Code School
- Training level: beginner to advanced
- Training duration: 11 hours and 20 minutes
- Number of courses: 109
Headlines of the Kafka Streams API For Developers using Java/SpringBoot 3.X course on 11/2023
Kafka Streams API For Developers using Java/SpringBoot 3.X course prerequisites
- Java knowledge is required
- Prior experience building Kafka Applications
- Prior experience working with IntelliJ or any other IDEA
- Java 17 is required
- Gradle or Maven knowledge is needed
Course images
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Installation guide
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