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Spring Cloud Stream With Kafka

Introduction

Spring Cloud Stream, is a mechanism by which you can decouple the implementation of your producers and consumers from the type of messaging infrastructure you want to use. This allows us to keep our consumers and producers to be broker agnostic and we can easily switch to a different kind of broker by changing the binder implementation. 

There are quite many binder implementations like e.g Kafka, RabbitMQ, AWS SNS, AWS SQS, etc. You can find a list of available binder implementations here.

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Spring Cloud Stream Channel Interceptor

Introduction

A Channel Interceptor is a means to capture a message before being sent or received in order to view it or modify it. The channel interceptor allows having a structured code when we want to add extra message processing or embed additional data that are basically related to a technical aspect without affecting the business code.

The Message Interceptor is used in frameworks like Spring Cloud Sleuth and Spring Security to propagate tracing and security context through message queue by adding headers to message in the producer part, then reading them and restoring the context in the consumer part.

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Spring Cloud Stream: A Brief Guide

This article will teach you how to create a Spring Cloud Stream app that works with a messaging service (like Apache Kafka, RabbitMQ, etc.), You’ll be using functional, reactive code—leveraging Spring’s WebFlux—and Spring Cloud Stream’s functional building model,

Today, you are going to make an app that has a publisher, a processor, and a consumer. It will leverage two topics to publish a stream of integers, process the integers to calculate a running total, and consume the processed data. In the beginning, these messages will be simple (strings/integers)—but later you’ll see how Spring Cloud Stream makes mapping POJOs (Plain Old Java Objects) to messages using JSON mapping simple!

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Spring Cloud Stream + RabbitMQ

In this example, we'll use Spring Cloud Stream and RabbitMQ. Integrating Spring Boot Applications with Messaging Systems like Apache Kafka and RabbitMQ.

If you look at these examples these required a lot of configuration code which was Broker specific. For example, in the case of RabbitMQ integration with Spring Boot, we had to write code to create AmqpTemplate Template and Bindings. So if tomorrow the Messaging System changes we will also need to make application code changes.

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How to Create a Spring Cloud Stream Binder From Scratch

Learn how to develop a custom Spring Cloud Stream binder from scratch.

Spring Cloud Stream is a framework built on top of Spring Boot and Spring Integration that is designed to build event-driven microservices communicating via one or more shared messaging systems.

The core Spring Cloud Stream component is called “Binder,” a crucial abstraction that’s already been implemented for the most common messaging systems (e.g. Apache Kafka, Kafka Streams, Google PubSub, RabbitMQ, Azure EventHub, and Azure ServiceBus).

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Spring Cloud Streams ETL

Spring clouds. Get it?

Spring Cloud Data Flow is a cloud-native toolkit for building real-time data pipelines and batch processes. Spring Cloud Data Flow is ready to be used for a range of data processing use cases like simple import/export, ETL processing, event streaming, and predictive analytics.

We can categorize SCDF applications as Streams and Tasks. Generally, Streams are long-running applications and continue processing data as long as desired; on the other hand, Tasks are short-lived applications which are created, executed and terminated within a relatively short span of time. Our focus in this article is the former.

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A Bootiful Podcast: Oleg Zhurakousky

Hi, Spring fans! In this installment, we talk to Oleg Zhurakousky, the lead of the Spring Cloud Stream project, about application integration, messaging wonk, and a prolific contributor to Spring Integration. Oleg also has the dubious honor of being one of my oldest friends on the Spring team — poor guy!

Twitter: @z_oleg
Twitter: @SpringCloud