What you'll learn:
- Setup a basic Kafka development environment
- Learn & implement Apache Kafka concepts : topic, partition, publish / consume
- Kafka Stream : Real-time data transformation
- Basic error handling in Kafka
- Learn & implement Java programs to handle asynchronous data integration among multiple systems using Apache Kafka
- How Kafka fit on microservice architecture
Major Update:
The whole course was re-recorded using better audio quality and natural English.
Now uses Spring Boot 3
Learn how to use AIAssistant (Github Copilot)to develop Spring application and Kafka
Additional course lectures
New Update 2 :
Learn everything about Kafka in a single course:
Rewrite all lectures for better audio quality
Update the Spring version to 2.6.x
Update Kafka version to 3.x
Newer alternative for deprecated syntax on Spring Kafka
Learn about Kafka Connect. How can it fit into system architecture, and how easy is it to ingest data from/to Kafka using Kafka Connect? With real-world sample hands-on
Learn about KsqlDB. How it can help speed up kafka usage, even for a team that does not know the Java programming language
The whole sections are integrated. Learn how to integrate Kafka Connect +Kafka Schema Registry +Kafka Stream +KsqlDB
New Update :
Learn how to use avro with spring Kafka and manage avro schema with confluent schema registry.
Write producer &consumer without coding using Kafka RESTProxy
Find out how Kafka fits into microservice architecture.
How to use Kafka along with RESTAPI&Database transaction
Kafka Stream:
real-time data transformation within Apache Kafka
joining stream
joining table
joining stream-table
global table
Exactly-Once Semantic
Messaging System
Nowadays, we work with multiple systems and data that run among them. It's common for one system to trigger another system(s) process, or data needs to be transferred among systems. Whether your systems are built on monolith or microservice, whatever database you use, you need data moving from one point to another. And you need those movements FAST to be processed immediately (otherwise, your life will be ruined).
That kind of demand is so common, and fortunately, today's technology has an answer for it. Say hello to messaging systems, where you can send messages easily from one system to another system(s) asynchronously, in an almost real-time interval. There are some popular messaging systems in the market, and in this course, we will be talking about one of the most popular:Apache Kafka.
Apache Kafka
Apache Kafkais like a central hub where you place all data from the source system(s), and the other corresponding systems take the data and process it. It is open-source, reliable, and able to work on clusters. It has a small learning curve to start, yet it is powerful enough for system integrations.
This course includes everything you need to know about basic Apache Kafka, and implementation using Java (Spring Framework). After finishing this course, you should be able to install, configure, and use Apache Kafka from the Java Program. In this course, we will walk through detailed step-by-step from concept to hands-on Java coding. Given such a way, you will learn to understand its logic and experience how things are done using Apache Kafka and Java source codes.
Java and Spring Boot
Java has been a popular language for years. It is recognized as the world's most used programming language by several programming language indexes. Due to its popularity and long history, Java has many open source projects or frameworks to help developers work more efficiently.
One popular Java framework is the Spring Framework. Over the years, It has grown substantially among the Java community. Almost all software components required by a Java application are available within the Spring Framework. However, configuring Spring requires some effort. This involves setting up library dependencies and configuring the required Java Spring beans using XMLor annotations in Java code. Spring developers soon realized that it is possible to automate much of this work.
So, in 2014, Spring Boot 1.0 was released for the Java community. Spring Boot gives Java programmers many automatic helpers and led to the quick large-scale adoption of the project by Java developers.
Spring provides good support for Kafka and the abstraction layers to work with over the native Kafka Java clients. With Spring, developing applications to interact with Apache Kafka is becoming easier.
Github Copilot as AIAssistant
GitHub Copilot can streamline Java development with Spring Boot and Apache Kafka by suggesting code snippets, generating boilerplate code, and offering best practices. It helps set up Kafka producers and consumers, configure Spring Boot applications, and integrate Kafka for real-time data processing. Copilot’s contextual suggestions improve productivity and reduce errors by providing relevant code examples and automated completions, enhancing development speed and code quality in your Java projects.
What You Will Get
After finishing the course, you will learn:
Installation of Apache Kafka and Java for development environment
How to use AIAssistant(Github Copilot)to boost your coding productivity
Apache Kafka key concepts
Create publisher and consumer using Java (Spring Boot)
Basic error handler if there is a failure during processing of Apache Kafka message
Basic understanding of how Kafka fit into Microservice Architecture
The course explains not only the theory of Apache Kafka but also a lot of hands-on coding to get your hands dirty and your brain working. Whether you are a hobbyist, beginner, or experienced developer, this course will surely add value to you!
Road to Microservices
Message broker is an important pillar of microservice architecture. In microservices, we use asynchronous messaging for inter-service communication. Services communicate by exchanging messages over messaging channels like Apache Kafka.
In this course, you will learn the theory and hand-code of messaging with Apache Kafka, a microservice architecture communication pillar.
Later on, you can learn more about Microservice Architecture & Patterns, with Kafka as an important component.
