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HomeJavajavaTutorialSpring Cloud's elegant microservice practice

Spring Cloud's elegant microservice practice

Jun 22, 2023 pm 12:31 PM
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With the development of the Internet, microservice architecture is becoming more and more popular among Internet companies. Spring Cloud provides a complete microservice solution based on Spring Boot. This article will introduce how to use the Spring Cloud framework to practice microservices.

1. Overview of microservice architecture

The so-called microservice architecture is to split the application into some smaller, autonomous service units, and use lightweight communication mechanisms between services. To work together, individual services can be built, deployed, tested, and scaled independently. The advantage of microservice architecture is that it can improve the productivity of the team and the elasticity and scalability of the system.

2. Spring Cloud Microservice Framework

Spring Cloud is the microservice solution of the Spring family. It provides a complete and rich toolkit based on Spring Boot. Spring Cloud uses multiple components (such as Eureka, Zuul, Hystrix, etc.) to build a complete microservice environment. The following are the main components of Spring Cloud:

1. Eureka: implements service registration and discovery, and provides a service registration center;
2. Feign: implements communication between services, simplifying RESTful calls;
3. Hystrix: Implement functions such as circuit breakers and downgrades to improve the robustness of the system;
4. Zuul: Provide API gateway services to achieve unified access and load balancing;
5. Config: Implement configuration Management provides a distributed configuration center.

3. Spring Cloud Microservice Practice

The following is a simple example to demonstrate how to use the Spring Cloud framework to build microservices. This example contains two services: a user service and an order service. The user service provides CRUD operations for user information, and the order service needs to call the user service to obtain user information.

1. Create a service registration center

First, we create a service registration center for registering and discovering services. Create a Spring Boot project to implement service registration and discovery through Spring Cloud's Eureka component.

Add dependencies:

<dependency>
  <groupId>org.springframework.cloud</groupId>
  <artifactId>spring-cloud-starter-eureka-server</artifactId>
</dependency>

Add the @EnableEurekaServer annotation on the startup class.

@SpringBootApplication
@EnableEurekaServer
public class EurekaServerApplication {

  public static void main(String[] args) {
    SpringApplication.run(EurekaServerApplication.class, args);
  }
}

In the application.properties configuration file, configure the relevant information of Eureka Server.

2. Create a user service

Create a user service to provide CRUD operations for user information. Create a Spring Boot project to implement communication between services through Spring Cloud's Feign component.

Add dependencies:

<dependency>
  <groupId>org.springframework.cloud</groupId>
  <artifactId>spring-cloud-starter-openfeign</artifactId>
</dependency>

Add the @EnableFeignClients annotation on the startup class.

@SpringBootApplication
@EnableFeignClients
public class UserServiceApplication {

  public static void main(String[] args) {
    SpringApplication.run(UserServiceApplication.class, args);
  }
}

Create the UserService interface and define CRUD operations for user information. Use the @FeignClient annotation to specify the service to be called. In this interface, a call to OrderService is defined.

@FeignClient(name = "order-service", fallback = OrderServiceFallback.class)
public interface OrderService {
  
  @GetMapping("/user/{userId}")
  UserDTO getUserById(@PathVariable("userId") Long userId);
  
  @PostMapping("/user")
  UserDTO createUser(@RequestBody UserDTO user);
  
  @PutMapping("/user")
  UserDTO updateUser(@RequestBody UserDTO user);
  
  @DeleteMapping("/user/{userId}")
  void deleteUser(@PathVariable("userId") Long userId);
}

In the application.properties configuration file, configure Eureka related information and Feign's timeout.

3. Create an order service

Create an order service for processing order information. Create a Spring Boot project and use Spring Cloud's Ribbon and Feign components to call user services and achieve load balancing between services.

Add dependencies:


  org.springframework.cloud
  spring-cloud-starter-ribbon


<dependency>
  <groupId>org.springframework.cloud</groupId>
  <artifactId>spring-cloud-starter-openfeign</artifactId>
</dependency>

Add @EnableFeignClients and @EnableDiscoveryClient annotations on the startup class.

@SpringBootApplication
@EnableFeignClients
@EnableDiscoveryClient
public class OrderServiceApplication {

  public static void main(String[] args) {
    SpringApplication.run(OrderServiceApplication.class, args);
  }
}

Create the OrderService interface and define CRUD operations for order information. In this interface, a call to UserService is defined.

public interface OrderService {

  @GetMapping("/order/{orderId}")
  OrderDTO getOrderById(@PathVariable("orderId") Long orderId);

  @PostMapping("/order")
  OrderDTO createOrder(@RequestBody OrderDTO order);

  @PutMapping("/order")
  OrderDTO updateOrder(@RequestBody OrderDTO order);

  @DeleteMapping("/order/{orderId}")
  void deleteOrder(@PathVariable("orderId") Long orderId);
}

In the implementation class, use @Autowired to inject the UserService interface.

@Service
public class OrderServiceImpl implements OrderService {

  @Autowired
  private UserService userService;

  // ...
}

In the application.properties configuration file, configure Eureka-related information and Ribbon's load balancing method.

4. Summary

This article introduces how to build an environment based on microservice architecture through the Spring Cloud framework, and uses a simple example to demonstrate how to implement service registration and discovery, service Inter-communication, load balancing and other functions. Of course, this is just a simple starting point, and more scenarios and issues need to be considered in practical applications. Only through deeper learning and practice can the reliability and scalability of the system be better improved.

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