Description
Kafka Streams API for Developers using Java/SpringBoot 3.X course. The Kafka Streams API is an extended API that is part of the Kafka ecosystem. With the Kafka Streams API we can:
- Apply data transformation,
- Data enrichment,
- Split data into multiple data streams
- Collect data or join data from multiple Kafka topics.
- Aggregate data in window trays and more.
The Kafka Streams API for Developers Using Java/SpringBoot program is designed to provide you with the theoretical and programming 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 completely 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. By the end of this course, you will have a comprehensive understanding of these concepts:
- Building Kafka Streams applications using the Streams API
- Building Kafka Streams applications using the SpringBoot and Streams API
- Write interactive queries to retrieve collected data from a state store and make it available via a RESTFUL API.
- Unit testing and integration of Kafka Stream applications with JUnit5
Getting started with Kafka Streams
- In this section, I will give you an introduction to Kafka Streams and the different terms involved in building a Kafka Streams application.
- An introduction to Kafka’s movements
- Kafka Streams Terminology – Topology and Processor
- Introduction to the KStreams API
Hello Kafka Streams application with KStreams API
In this section, we will create a simple Kafka Streams application and test it locally.
- Training on building the Greetings application topology
- Create a Kafka Streams launcher that we can use to start and stop the application.
Operators for Kafka streams with the KStream API
In this section, we will explore some of the operators available in the Kafka Streams API.
- Filter & FilterNot
- Card/Card Values
- FlatMapValues/FlatMap
- Look
- merge
Serialization and deserialization in Kafka streams
In this section we program and test serialization and deserialization in Kafka Streams.
- How does key/value serialization and deserialization work in Kafka Stream?
- Provide a default serializer/deserializer using application configuration
- Create custom serdes for extended welcome messages
General reusable serializer/deserializer (recommended approach)
In this section, I will show you the best way to create a generic serializer and serializer that can be used for any message type.
- Create a generic Serializer/Serializer
Kafka Streams Job Management Application – a Real-Time Use Case
In this section, we will create a Kafka Streams application by implementing an order management system for a retail company.
Topology, process and tasks – under the hood
In this section, we explore the internals of the Kafka Streams application.
- Internal topology, process and tasks
Error/Exception Handling in Kafka Streams
In this section we explore the different error handlers in Kafka Streams.
- Errors in Kafka streams
- Default behavior for deserialization errors
- Custom deserialization error handler
- Standard and custom processor error handlers
- Custom error handler for production
What you will learn in the course “Kafka Streams API for Developers with Java/SpringBoot 3.X”
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Build advanced Kafka Streams applications using the Streams API
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Create a Kafka Streams application with HighLevel DSL
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Exactly once processing transactions and powerless producer
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Build a real-time streaming application for retail using the Streams API
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Combine multiple events into cumulative events
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Combine multiple streams into one continuous stream
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Collect streams in the Events window group.
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Create a standard Kafka Streams Enterprise application with SpringBoot
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Testing Kafka Stream with TopologyTestDriver with JUnit5
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Testing Spring Kafka streams with EmbeddedKafka and JUnit5
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Create interactive queries to retrieve collected data via RESTFUL APIs
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Interactive queries with multiple instances of the Kafka Flow pattern (MicroServices pattern)
This course is suitable for people who
- Advanced Java developers
- Kafka developers curious about the Kafka Streams API
- Kafka developers interested in developing advanced streaming applications
- Developers who want to learn Kafka Streams application testing techniques with TopologyTestDriver.
Course specification Kafka Streams API for developers using Java/SpringBoot 3.X
- Editor: Udemy
- Teacher: Pragmatic Code School
- Training level: beginner to advanced
- Training duration: 11 hours and 20 minutes
- Number of courses: 109
Headlines of the course “Kafka Streams API for developers using Java/SpringBoot 3.X” on 11.11.2023
Kafka Streams API for developers using Java/SpringBoot 3.X course prerequisites
- Java knowledge is required
- Previous knowledge of developing Kafka applications
- Previous knowledge of working with IntelliJ or another IDEA
- Java 17 is required
- Gradle or Maven knowledge is required
Course pictures
Sample video of the course
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