This tutorial explains how to build a lightweight log management module by defining a custom @SystemLog annotation, using Spring AOP to capture method execution details, and sending the log data through RabbitMQ via Spring Cloud Stream for asynchronous persistence in a database.
This guide walks through setting up Spring Cloud Stream with RabbitMQ, covering supported binders, core components, configuration, code examples for producers and consumers, consumer groups, and message partitioning to build scalable, event‑driven microservices.
This article explains how Spring Cloud Stream integrates with Apache Kafka, covering its programming model, configuration, code examples, topic provisioning, consumer groups, partitioning, monitoring, error handling, schema evolution, and Kafka Streams support for building robust streaming microservices.
This article explains how Spring Cloud Data Flow, together with Spring Cloud Skipper, enables developers to design, deploy, and manage event‑stream pipelines on Apache Kafka, covering ecosystem overview, pipeline components, Docker‑based local setup, stream creation, debugging, monitoring, and integration of Kafka Streams applications.
This article explains why RabbitMQ delayed messages stop working when the delay exceeds a specific limit, demonstrates the issue with practical curl tests, and provides the exact TTL boundary (4294967295 ms) you must respect to ensure reliable scheduling.
This article explains how Spring Cloud Stream leverages Spring Messaging and Spring Integration to create highly scalable, event‑driven microservices, covering core concepts, message channels, binders, code examples, and the underlying processing flow for both producers and consumers.
This tutorial explains how to handle tasks with uncertain start times by leveraging RabbitMQ's delayed‑message plugin together with Spring Cloud Stream, covering plugin installation, configuration, Java code examples, and verification through logs and the RabbitMQ management UI.
This curated list compiles essential Spring Cloud Stream articles covering quick start, core concepts, consumer groups and partitions, common FAQs, and four detailed failure‑handling strategies, providing developers with a handy reference to master message‑driven microservices.
Using Spring Cloud Stream’s @StreamListener condition attribute, this guide shows how to route messages by header values, providing a full example that includes a producer sending version‑tagged messages, a consumer with two conditional listeners, required configuration, and sample log output demonstrating the simplified processing flow.
This tutorial demonstrates how to use RabbitMQ's dead‑letter queue (DLQ) with Spring Cloud Stream to automatically capture failed messages, configure retry and DLQ settings, and later reprocess those messages through simple console operations, providing a complete error‑handling workflow for backend services.
This tutorial demonstrates how to create a custom error‑handling flow for Spring Cloud Stream by building a simple producer‑consumer example, configuring input/output bindings, using @StreamListener to simulate a failure, and routing the exception to a @ServiceActivator fallback method, while also discussing version‑specific limitations.
This guide explains how to configure message partitioning in Spring Cloud Stream by adjusting consumer and producer properties—such as group, destination, partitioned flag, instanceCount, instanceIndex, partitionKeyExpression, and partitionCount—to ensure that messages with the same characteristics are consistently processed by the same instance across multiple service instances.
This article explains how Spring Cloud Stream uses binders to isolate applications from messaging middleware, defines channels for input and output, demonstrates publish‑subscribe with RabbitMQ, shows how consumer groups prevent duplicate processing, and introduces message partitioning for ordered handling.
This tutorial walks through creating a Spring Boot microservice that uses Spring Cloud Stream to bind to RabbitMQ, covering project setup, required dependencies, a simple consumer implementation, application startup, log verification, core annotations, and a unit test for message production.
