Integrate a Spring Cloud Data Flow app with a MongoDB service running on Kubernetes.
Integrate Kafka with MongoDB to create scalable, fault-tolerant messaging on Kubernetes
Leverage Spring Cloud Stream, a framework for building highly scalable, event-driven microservices for your enterprise needs.
Leverage Apache Kafka, a distributed streaming platform built for storing and processing streams of records, while focusing on performance.
Leverage RabbitMQ, an open source message broker that is lightweight and easy to deploy on premises and in the cloud.
A simple demonstration of how to implement your Java application with Kafka (Spring Cloud Stream) with the least amount of code in your Spring Boot application.
Simulate a scenario to get a better sense of what we have previously discussed on Spring Cloud Stream Part 1. Asynchronous communication between applications and using Apache Kafka as broker.
Creating & Deploying Spring Cloud Stream Apps with Spring Cloud Data Flow
Creating a http-log stream with Spring Cloud Data Flow
Getting Started With The Spring Cloud Data Flow CLI Tool
Installing Spring Cloud Data Flow Locally On Kubernetes With Helm
Spring Cloud Stream Processors And Scripted Deployments With Spring Cloud Data Flow
Spring Live: Developing fault-tolerant stream processing application with Kafka Streams and Kubernetes
Spring Live: Processing CloudEvents with Spring and Knative
Building Microservice Data Streams With Spring Cloud Data Flow
Simple Event Driven Microservices with Spring Cloud Stream
Which is better RabbitMQ or Kafka? This article will outline the functionality offered by both messaging systems and help you make an informed decision when choosing a platform.