Asynchronous message communication under Spring Cloud microservices
With the rise of cloud computing and big data, microservice architecture is widely used in enterprise systems. As an important implementation tool for microservice architecture, Spring Cloud provides a variety of solutions for realizing communication under microservice architecture. This article will focus on the asynchronous message communication solution under Spring Cloud microservices, hoping to provide some ideas and reference for everyone to solve the message communication problems under the microservice architecture.
1. Background of microservice asynchronous message communication
Under the microservice architecture, the service is split into multiple microservices for independent development, independent deployment and independent maintenance. There must be interaction and communication. However, traditional RPC calls or HTTP requests will degrade system performance due to long response times in high concurrency and big data scenarios. Therefore, asynchronous message communication is widely used in microservices as an excellent solution and efficiently supports Communication between different microservices.
2. Asynchronous message communication solutions under Spring Cloud
In Spring Cloud, there are two commonly used asynchronous message communication solutions: Spring Cloud Stream and Spring Cloud Bus.
- Spring Cloud Stream
Spring Cloud Stream is a framework provided by Spring Cloud for building message-driven microservices. It is built on Spring Boot and Spring Integration and can easily connect various message broker services. Spring Cloud Stream implements asynchronous message communication based on the publish/subscribe model (Publish/Subscribe).
The Spring Cloud Stream workflow is as follows:
① The producer generates messages and publishes them to Spring Cloud Stream;
② Spring Cloud Stream sends the messages to the intermediate agent (Message Broker);
③ The consumer subscribes to the information from the intermediate agent and notifies Spring Cloud Stream when it receives the message. Spring Cloud Stream then delivers the message to the corresponding consumer.
Spring Cloud Stream uses message broker services such as Apache Kafka and RabbitMQ, which has the characteristics of high reliability, high concurrency and high scalability. Its use process is very simple. You only need to introduce the corresponding dependencies and configure the message agent it uses. The sample code to implement a message service is as follows:
// 引入Spring Cloud Stream依赖 <dependency> <groupId>org.springframework.cloud</groupId> <artifactId>spring-cloud-starter-stream-kafka</artifactId> </dependency> // 在应用程序属性文件中设置连接的kafka代理 spring.cloud.stream.kafka.binder.brokers=kafka.example.com:9092 spring.cloud.stream.kafka.binder.zkNodes=zookeeper.example.com spring.cloud.stream.kafka.binder.defaultBrokerPort=9092 spring.cloud.stream.kafka.binder.defaultZkPort=2181
- Spring Cloud Bus
Spring Cloud Bus is a mechanism for propagating state changes in a distributed system. It can Let messages pass between the various microservices that make up the system. Spring Cloud Bus uses a message broker to connect various microservices and uses a lightweight message type to complete the transmission of event status. Different from Spring Cloud Stream, Spring Cloud Bus is more used for messaging and state sharing within the system.
Spring Cloud Bus workflow is as follows:
① Trigger events that can affect the state on Spring Cloud Bus through HTTP/HTTPS requests (for example: POST method, PATCH method or DELETE method) ;
② Spring Cloud Bus receives the event request and stores the content of the event;
③ Broadcasts the event status in Spring Cloud Bus to the entire distributed system through the message agent;
④ Each microservice listens for messages Event status in the agent, and synchronously changes its own status in real time when the event status changes.
Spring Cloud Bus uses RabbitMQ or Kafka as the message proxy server, which has the characteristics of high scalability and high reliability. Spring Cloud Bus is very simple to use. You only need to add the corresponding configuration in the application properties file. The sample code to implement a message service is as follows:
// 添加依赖 <dependency> <groupId>org.springframework.cloud</groupId> <artifactId>spring-cloud-starter-bus-amqp</artifactId> </dependency> // 在应用程序属性文件中设置RabbitMQ地址 spring.rabbitmq.host=localhost spring.rabbitmq.virtual-host=/ spring.rabbitmq.port=5672 spring.rabbitmq.username=guest spring.rabbitmq.password=guest
3. Summary
Spring Cloud is one of the most popular implementation solutions in the current microservice architecture. Using Spring Cloud to implement asynchronous message communication has many an advantage. This article introduces the commonly used asynchronous message communication solutions under Spring Cloud: Spring Cloud Stream and Spring Cloud Bus, and introduces how to use them in applications through simple code examples. I hope this article can help everyone better apply the microservice architecture in practice and improve the performance and stability of the system.
The above is the detailed content of Asynchronous message communication under Spring Cloud microservices. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



Benefits of combining PHP framework with microservices: Scalability: Easily extend the application, add new features or handle more load. Flexibility: Microservices are deployed and maintained independently, making it easier to make changes and updates. High availability: The failure of one microservice does not affect other parts, ensuring higher availability. Practical case: Deploying microservices using Laravel and Kubernetes Steps: Create a Laravel project. Define microservice controllers. Create Dockerfile. Create a Kubernetes manifest. Deploy microservices. Test microservices.

The Java framework supports horizontal expansion of microservices. Specific methods include: Spring Cloud provides Ribbon and Feign for server-side and client-side load balancing. NetflixOSS provides Eureka and Zuul to implement service discovery, load balancing and failover. Kubernetes simplifies horizontal scaling with autoscaling, health checks, and automatic restarts.

Create a distributed system using the Golang microservices framework: Install Golang, choose a microservices framework (such as Gin), create a Gin microservice, add endpoints to deploy the microservice, build and run the application, create an order and inventory microservice, use the endpoint to process orders and inventory Use messaging systems such as Kafka to connect microservices Use the sarama library to produce and consume order information

SpringBoot plays a crucial role in simplifying development and deployment in microservice architecture: providing annotation-based automatic configuration and handling common configuration tasks, such as database connections. Support verification of API contracts through contract testing, reducing destructive changes between services. Has production-ready features such as metric collection, monitoring, and health checks to facilitate managing microservices in production environments.

Data consistency guarantee in microservice architecture faces the challenges of distributed transactions, eventual consistency and lost updates. Strategies include: 1. Distributed transaction management, coordinating cross-service transactions; 2. Eventual consistency, allowing independent updates and synchronization through message queues; 3. Data version control, using optimistic locking to check for concurrent updates.

Microservice architecture monitoring and alarming in the Java framework In the microservice architecture, monitoring and alarming are crucial to ensuring system health and reliable operation. This article will introduce how to use Java framework to implement monitoring and alarming of microservice architecture. Practical case: Use SpringBoot+Prometheus+Alertmanager1. Integrate Prometheus@ConfigurationpublicclassPrometheusConfig{@BeanpublicSpringBootMetricsCollectorspringBootMetric

Building a microservice architecture using a Java framework involves the following challenges: Inter-service communication: Choose an appropriate communication mechanism such as REST API, HTTP, gRPC or message queue. Distributed data management: Maintain data consistency and avoid distributed transactions. Service discovery and registration: Integrate mechanisms such as SpringCloudEureka or HashiCorpConsul. Configuration management: Use SpringCloudConfigServer or HashiCorpVault to centrally manage configurations. Monitoring and observability: Integrate Prometheus and Grafana for indicator monitoring, and use SpringBootActuator to provide operational indicators.

In PHP microservice architecture, data consistency and transaction management are crucial. The PHP framework provides mechanisms to implement these requirements: use transaction classes, such as DB::transaction in Laravel, to define transaction boundaries. Use an ORM framework, such as Doctrine, to provide atomic operations such as the lock() method to prevent concurrency errors. For distributed transactions, consider using a distributed transaction manager such as Saga or 2PC. For example, transactions are used in online store scenarios to ensure data consistency when adding to a shopping cart. Through these mechanisms, the PHP framework effectively manages transactions and data consistency, improving application robustness.
