Summary of Spring Cloud interview questions

Correspondence between Spring Cloud and each sub-project version

Spring Cloud is a development toolkit for building distributed systems. It provides a set of modules and functions based on Spring Boot for building distributed applications in a microservice architecture. Different sub-projects of Spring Cloud have their own versions. Here are some common Spring Cloud sub-projects and their correspondence with Spring Boot versions:

Spring Cloud Netflix：
- Spring Cloud Netflix includes multiple modules integrated with Netflix OSS, such as Eureka (service registration and discovery), Ribbon (load balancing), Hystrix (circuit breaker), Feign (declarative REST client), etc.
- The version of Spring Cloud Netflix is usually consistent with the version of Spring Boot. For example, Spring Cloud Netflix 2.2.x needs to be used in conjunction with Spring Boot 2.2.x.
Spring Cloud Config：
- Spring Cloud Config is used to centrally manage application configuration information.
- The version of Spring Cloud Config is usually consistent with the version of Spring Boot, but a specific version of Spring Cloud Config can also be specified in the configuration of Spring Cloud Config Server.
Spring Cloud Gateway：
- Spring Cloud Gateway is an API gateway service built on Spring Framework 5 and Spring Boot 2, used to build routing and filtering in microservice architecture.
- The version of Spring Cloud Gateway is usually consistent with the version of Spring Boot. For example, Spring Cloud Gateway 2.2.x needs to be used in conjunction with Spring Boot 2.2.x.
Spring Cloud Sleuth：
- Spring Cloud Sleuth is used for distributed tracing and logging.
- The version of Spring Cloud Sleuth is usually consistent with the version of Spring Boot, but it is also possible to specify a specific version of Spring Cloud Sleuth in the Spring Cloud Sleuth configuration.
Spring Cloud OpenFeign：
- Spring Cloud OpenFeign is a declarative HTTP client for communicating with RESTful services.
- The version of Spring Cloud OpenFeign is usually consistent with the version of Spring Boot. For example, Spring Cloud OpenFeign 2.2.x needs to be used in conjunction with Spring Boot 2.2.x.
Spring Cloud Bus：
- Spring Cloud Bus is used to broadcast configuration change events in distributed systems.
- The version of Spring Cloud Bus is usually consistent with the version of Spring Boot, but you can also specify a specific version of Spring Cloud Bus in the configuration of Spring Cloud Bus.

Please note that the above are some common Spring Cloud sub-projects, and the Spring Cloud ecosystem contains many more sub-projects and modules, each of which may have its specific version. To ensure compatibility and stability, it is generally recommended to keep the versions of Spring Boot and Spring Cloud consistent and use the same version of subprojects in the project. You can find details and release notes about specific subproject versions in the official Spring Cloud documentation or GitHub pages.

Spring Cloud OpenFeign

Spring Cloud OpenFeign is part of the Spring Cloud microservices framework and is used to simplify communication between REST-based services. It is built on Netflix's Feign and provides a declarative way to write HTTP client code, making calling remote services as simple as calling local methods.

The following are the main features and uses of Spring Cloud OpenFeign:

Declarative REST client : OpenFeign allows you to use annotations to define interfaces and describe calls to remote services through these interfaces. This declarative approach makes the code clearer and easier to maintain.
Automated load balancing : OpenFeign integrates Spring Cloud Ribbon to automatically handle load balancing. You can call a remote service by its service name without hardcoding the URL of the target service.
Integrated Spring Cloud service discovery : OpenFeign can be integrated with Spring Cloud Eureka or other service discovery components, so that services registered in the service registry can be dynamically discovered and invoked.
Customization of requests and responses : You can customize request headers, request parameters, request bodies, and response processing through annotations to meet different needs.
Support for circuit breakers : OpenFeign can integrate Spring Cloud Circuit Breaker (usually using Hystrix) to increase fault tolerance against service failures.
Integrate other Spring Cloud components : OpenFeign can be integrated with other Spring Cloud components such as Spring Cloud Config and Spring Cloud Sleuth to provide functions such as configuration management and distributed tracing.
Logging and debugging : OpenFeign can generate detailed request and response logs to help you diagnose and debug problems.

Here is a simple example showing how to use Spring Cloud OpenFeign to call a remote service in a Spring Boot application:

import org.springframework.cloud.openfeign.FeignClient;
import org.springframework.web.bind.annotation.GetMapping;

@FeignClient(name = "remote-service")
public interface RemoteServiceClient {
    
    

    @GetMapping("/api/resource")
    String getResource();
}

In the above example, the interface declares a remote service client RemoteServiceClientusing the annotation, where the attribute specifies the name of the service to be called. You can then use the interface to call the remote service just like calling a local method.@FeignClientnameRemoteServiceClient

To use Spring Cloud OpenFeign, you need to add the relevant dependencies and specify the service name, port, and other configuration in the application's configuration. You can then use the injected Feign client to call the remote service.

In summary, Spring Cloud OpenFeign is a powerful tool that can be used to simplify service invocation and communication in microservice architecture, making it easier for developers to build distributed systems.

Springcloud core components and their functions, as well as springcloud working principle

Spring Cloud is a development toolbox for building distributed systems that provides a core set of components and patterns to simplify the development and deployment of distributed systems. The following is the core components of Spring Cloud and their roles, as well as an overview of how Spring Cloud works:

Spring Cloud core components and their functions:

Eureka (service registration and discovery) :
- Role: Eureka is a service registration and discovery component used to build service registries in distributed systems. The service provider registers itself on the Eureka server, and the service consumer can obtain the list of available services from the Eureka server to achieve communication between services.
Ribbon (client load balancing) :
- Function: Ribbon is a load balancer that distributes client requests to multiple service provider instances to achieve load balancing and fault tolerance.
Feign (declarative REST client) :
- Function: Feign provides a declarative way to write REST client code, treating calls to remote services as local method calls, thus simplifying calls to remote services.
Hystrix (fault tolerance and circuit breakers) :
- Role: Hystrix is used to increase fault tolerance and elasticity of services in distributed systems. It provides a circuit breaker mode to prevent cascading failures in the event of service failure, and also provides a degradation mechanism.
Zuul (API gateway) :
- Role: Zuul is an API gateway used to route, filter, verify and monitor microservice requests. It centralizes request processing and provides load balancing, security, and logging capabilities.
Config (distributed configuration management) :
- Function: Config is used to centrally manage and distribute configurations so that microservices can dynamically obtain configuration information without redeployment.
Bus (message bus) :
- Function: Bus uses message queues (such as RabbitMQ or Kafka) to propagate configuration change events so that microservices can update configurations in real time.

Overview of how Spring Cloud works:

The core principle of Spring Cloud is to simplify the development and management of distributed systems through various components. Here's how Spring Cloud works in general:

Service registration and discovery : The service provider registers itself to the service registration center (such as Eureka) at startup, and the service consumer obtains the list of available services from the registration center. Ribbon is responsible for distributing requests to these service providers.
Load balancing : Ribbon provides load balancing function and distributes requests to different service instances through polling, random or other strategies to achieve load balancing.
Declarative REST client : Feign allows developers to define remote service calls through interfaces and annotations, and uses Ribbon at the bottom to achieve load balancing and fault tolerance.
Fault tolerance and circuit breaker : Hystrix provides a circuit breaker mode that can monitor service calls. When a service fails or times out, Hystrix can downgrade or provide backup responses to prevent cascading failures.
API gateway : Zuul acts as a gateway to receive external requests, can route, filter, verify and monitor them, and forward the requests to the corresponding microservices.
Distributed configuration management : Config allows centralized management of application configurations. When configuration changes are made, each microservice can be notified in real time through the message bus (Bus).
Message bus : Bus allows microservices to propagate configuration change events through message queues to achieve dynamic configuration updates.

In short, Spring Cloud provides a set of tools and patterns to help developers build and manage distributed systems, making tasks such as communication, load balancing, fault tolerance, and configuration management between microservices easier and more reliable. These components can be combined and used according to specific needs to build distributed applications that meet the needs of specific scenarios.

Interface current limiting method?

Interface throttling is a method used to control the frequency of interface requests to prevent malicious or excessively frequent requests from placing unnecessary burden on the server. The following are some common interface current limiting methods:

Based on Token Bucket algorithm :
- The token bucket algorithm is a commonly used current limiting algorithm. It maintains a fixed-capacity token bucket. Tokens are put into the bucket at a fixed rate. Each request needs to obtain a token before it can be executed. If there are not enough tokens in the bucket, the request is throttled.
- Advantages: Smoothly control the request rate, suitable for burst requests.
- Disadvantages: Difficult to handle sudden large number of requests.
Based on Leaky Bucket algorithm :
- The leaky bucket algorithm maintains a fixed-capacity leaky bucket, and requests are added to the leaky bucket at a fixed rate. The requests need to wait until there is enough space in the leaky bucket before they can be processed. If the request arrival speed exceeds the processing speed of the leaky bucket, the request is limited.
- Advantages: Smoothly control the request rate, suitable for stable traffic.
- Disadvantages: Not suitable for burst requests.
Counter based :
- A simple current limiting method is to maintain a counter to record the number of requests within a certain period of time. If the number of requests exceeds the limit, the request is limited.
- Advantages: Simple and easy to implement.
- Disadvantages: It is not suitable for smoothly controlling the request rate and is easily affected by burst requests.
Based on distributed current limiter :
- In a distributed system, a distributed current limiter (such as Redis or ZooKeeper) can be used to implement interface current limiting. Each service node shares a distributed rate limiter that coordinates throttling requests.
- Advantages: Suitable for distributed systems and can coordinate current limiting of multiple nodes.
- Disadvantages: Requires additional distributed storage and coordination mechanisms.
Based on third-party services :
- Use a third-party rate limiting service, such as Google's Rate Limiting or the cloud service provider's API gateway rate limiting function. These services usually provide powerful current limiting and quota management functions.
- Advantages: easy to use, good scalability.
- Disadvantages: Additional fees may apply.

Choosing the right throttling method for your application needs depends on several factors, including request characteristics, system architecture, and performance requirements. Generally, token bucket and leaky bucket algorithms are common choices, but in specific cases, other methods may be more suitable. Best practice is to test and tune based on your specific needs to find the throttling strategy that works best for you.

Spring Cloud Task

Spring Cloud Task is a project in the Spring Cloud ecosystem that supports the development and execution of short-lived, one-time tasks. It is designed to simplify the creation, scheduling and execution of tasks, as well as the management of task status. Spring Cloud Task is usually used to process batch tasks, ETL (extract, transform, load) tasks, data import and other one-time task scenarios.

Here are some key features and uses of Spring Cloud Task:

Task creation and configuration : Spring Cloud Task allows developers to create and configure tasks, defining the input, output and other properties of the task through simple annotations and property settings.
Task scheduling : You can use Spring Cloud Task to schedule the execution of tasks. You can trigger tasks manually or execute tasks according to a plan.
Task execution : Spring Cloud Task provides a task execution environment that can be used to run tasks. It can run within a single application or execute in a distributed environment.
Task status management : Spring Cloud Task allows you to manage the status of tasks, including task start, stop, failure, etc. You can view the execution history and results of tasks.
Task listener : Spring Cloud Task provides task listeners, which you can use to monitor the execution of tasks and perform custom operations during the task life cycle.
Task failure and recovery : Spring Cloud Task allows you to define failure handling strategies for tasks, such as retries, rollbacks, or notifications.
Task tracking and monitoring : Spring Cloud Task can integrate Spring Cloud Stream and Spring Cloud Data Flow to implement task tracking, monitoring and management.
Distributed tasks : Although Spring Cloud Task is mainly used for short-lived one-time tasks, distributed tasks can also be implemented with the help of tools such as Spring Cloud Data Flow.

Spring Cloud Task is often used in conjunction with Spring Batch to handle large-scale batch processing tasks. Spring Cloud Data Flow can be used to create and manage Spring Cloud Tasks, deploy them to different execution environments, and provide task monitoring and management.

Overall, Spring Cloud Task is a framework that helps simplify the creation and management of one-time tasks, especially for scenarios where batch processing, ETL, or data import tasks need to be performed. It provides task life cycle management, status management and task scheduling functions, making task execution more reliable and controllable.

What is Oauth?

OAuth (Open Authorization) is an open-standard authorization protocol used to authorize a user or application to access another application's resources without sharing user credentials (for example, username and password). OAuth is designed to allow users to grant third-party applications limited access to their protected resources without revealing their passwords.

The basic concepts of the OAuth protocol involve the following main roles and concepts:

Resource Owner : The resource owner is the user who owns the protected resource. This can be a person or an application.
Client : The client is an application that requests access to resources. It may be a web application, mobile application, desktop application or back-end service.
Authorization Server : The authorization server is the server responsible for verifying the identity of the resource owner and issuing access tokens to the client. Typically, the authorization server is also the authentication server.
Resource Server : The resource server is a server that stores protected resources. The resource server verifies the client's token and provides protected resources.
Access Token : An access token is a credential used by the client to access protected resources on the resource server. Access tokens are usually valid for a shorter period for added security.
Authorization Code : In some OAuth processes, the client will first redirect to the authorization server. After the resource owner authorizes the authorization, the authorization server will return an authorization code to the client, and then the client will exchange the authorization code. access token.

OAuth defines different authorization processes (or authorization methods) to meet different application and security requirements. The most common one, OAuth 2.0, is a modern version of OAuth that is widely used for authorization of Internet applications and APIs.

The core benefit of OAuth is that it allows users to grant limited, scope-specific access without sharing their credentials. This is important to protect user privacy and security, and allows users to have more control over managing their data. OAuth is widely used in many Internet services, social media platforms, and APIs to enable secure third-party access authorization.

What is DRY in microservice architecture?

DRY is the abbreviation of "Don't Repeat Yourself", which is an important principle in software development. In the microservice architecture, the DRY principle also applies. The core idea is to avoid duplication and redundant code and functions in the system.

In microservice architecture, the DRY principle has the following meaning and importance:

Avoid code redundancy : The DRY principle encourages developers to avoid writing the same code repeatedly in different microservices or service components. Not only does this reduce the amount of code, it also reduces maintenance costs because when changes or fixes need to be made, they only have to be done in one place.
Consistency and maintainability : The DRY principle helps maintain system consistency as the same logic only needs to be implemented once. This improves the maintainability of the system because developers only need to worry about the issues of a single implementation and do not have to worry about the consistency of multiple copies.
Bug reduction and troubleshooting : Since the logic only exists in one place, when an issue or bug occurs, developers can more easily locate and fix the issue without having to check multiple places.
Performance and resource utilization : Avoiding duplication of code and functionality improves system performance because the same operations no longer need to be performed multiple times. In addition, the waste of resources can also be reduced because multiple resources will not be allocated for the same function.
Scalability and Flexibility : The DRY principle helps in the scalability of the system as new microservices or features can reuse existing logic instead of having to write it from scratch. This increases the flexibility of the system as it can more easily adapt to new needs and changes.

In summary, the DRY principle is of great significance in microservice architecture, as it helps ensure code consistency, maintainability, and scalability. Developers should strive to avoid copying and pasting the same code in different microservices and instead enable code reuse through modularity, libraries, shared code, or communication between microservices. This helps build more efficient, stable, and maintainable microservice applications.

What are the best practices for designing microservices?

Best practices for designing microservices cover many aspects, including microservice decomposition, communication, maintainability, security, monitoring, and more. Here are some best practices when designing microservices:

Domain Driven Design (DDD) :
- Understand the business domain and divide microservices into logical boundaries. Each microservice focuses on a specific business subdomain. This helps ensure that microservice responsibilities are clear and cohesive.
Single Responsibility Principle (SRP) :
- Each microservice should have a single responsibility for a well-defined function. This helps simplify the design and maintenance of microservices.
Loose Coupling :
- Minimize dependencies between microservices by using appropriate communication mechanisms such as HTTP REST or message queues. Avoid hard-coded dependencies and instead use mechanisms like service discovery and registration to find other microservices.
API design :
- Design clear, stable and easy-to-understand APIs so that other microservices can easily call them. Use version control to manage API evolution.
Independent deployment and scalability :
- Each microservice should be able to deploy and scale independently, which helps achieve high availability and system resiliency. Use containerization technologies such as Docker and Kubernetes to manage the deployment of microservices.
Circuit breaker mode :
- Implement the circuit breaker pattern (like Hystrix) to handle failures and delays between microservices to prevent cascading failures.
Logging and monitoring :
- Implement logging and monitoring within microservices to be able to track and analyze microservice behavior and performance. Use a distributed tracing tool (such as Zipkin) to track the flow of requests.
Security :
- Implement appropriate security measures for microservices, including authentication, authorization, API tokens, etc. Ensure sensitive data is protected during transmission and storage.
Continuous integration and continuous delivery :
- Automate build, test, and deployment processes so you can deliver new releases frequently. Use CI/CD tools to support automated processes.
Documentation and API documentation :
- Write appropriate documentation to describe each microservice's functionality, API, usage, and dependencies. Well-maintained documentation facilitates team collaboration and rapid development.
Fault tolerance and failure handling :
- Consider the fault tolerance of microservices, handle failure situations and provide appropriate fallback mechanisms to ensure that the system can continue to operate when problems occur.
Team organization :
- Organize teams into microservices, with each team responsible for maintaining and developing one or more microservices. Ensure teams have sufficient autonomy to respond quickly to changes in requirements.

Best practices may vary from organization to organization and project to project, but the above principles generally apply to most microservices architecture designs. The design and implementation of microservices requires balancing multiple factors, including performance, maintainability, security, and scalability, so careful consideration is required during the design phase and continuous adjustments and improvements are made based on feedback and needs.

What does load balancing mean?

Load Balancing is an important technology in computer network and system design. Its main purpose is to evenly distribute network traffic or workload to multiple servers or resources to improve performance, availability, stability and scalability. sex. The following are the main meanings and functions of load balancing:

Improve performance :
- Load balancing distributes traffic across multiple servers, reducing the load on each server. This improves overall system performance, improves response times, and reduces latency.
Improve usability :
- When a server goes down or undergoes maintenance, a load balancer can automatically redirect traffic to other functioning servers. This increases system availability and reduces the risk of service interruption.
Increase stability :
- Load balancing prevents a server from becoming overloaded, causing performance degradation or crashes. By evenly distributing the load, the stability of the system can be improved and the possibility of failure reduced.
To achieve horizontal expansion :
- Load balancing allows adding more servers when needed to handle increased traffic. This horizontal scaling approach increases the scalability of the system, allowing it to handle more requests.
Resource utilization :
- Load balancing ensures that each server can make full use of its resources, thereby improving the utilization of hardware resources. This helps reduce server costs as there is no need to over-invest in high-end hardware.
Failure detection and automatic recovery :
- Load balancers usually have a failure detection mechanism that can detect the failure of a server and automatically route traffic to a functioning server. This helps restore service quickly.
Optimize user experience :
- Users get a better user experience through faster response times and higher availability, thus increasing user satisfaction.
Distributed system support :
- In a distributed system, load balancing can coordinate workloads between different nodes to ensure reasonable task distribution and improve system efficiency.

In short, load balancing plays a key role in modern computing environments. It not only improves system performance, availability, and stability, but also supports many important applications such as cloud computing, distributed systems, and high-availability applications. By evenly distributing load, load balancing helps ensure efficient utilization of computing resources and provides a seamless user experience.

The role of service gateway

Service Gateway is an important component in the microservice architecture. It acts as the entry point between the client and the backend microservices and has multiple important functions:

Routing request :
- The service gateway can route the request to the appropriate backend microservice based on the requested URL, HTTP method, header information and other conditions. This allows clients to access multiple microservices through a single entry point.
Load balancing :
- The service gateway can distribute requests evenly among multiple identical microservice instances to ensure that each instance evenly shares the load and improves the performance and scalability of the system.
Security :
- The service gateway can act as a security boundary and perform security functions such as authentication, authorization, and access control. It protects backend microservices from malicious requests and security threats.
Request conversion :
- Service gateways can transform requests and responses to accommodate the needs of different clients and backend microservices. This includes protocol conversion of requests and responses, data format conversion, etc.
Cache :
- Service gateways can cache responses to reduce load on backend microservices and improve response times. This is helpful for scenarios where the same resource is requested frequently.
Logging and monitoring :
- A service gateway is typically responsible for logging requests and responses, as well as performing monitoring and analysis functions. This helps track system performance and troubleshoot problems.
Current limiting and fusing :
- The service gateway can implement request current limiting and circuit breaker mechanisms to prevent excessive requests from affecting the performance and availability of back-end services.
Static resource service :
- The service gateway can provide services for static resources (such as images, CSS, and JavaScript files), reducing the burden on back-end services and improving page loading speed.
API version management :
- Service gateways can handle different versions of APIs, providing clients with API versions that suit their needs without directly affecting the APIs of backend microservices.
Service discovery and registration :
- The service gateway can be integrated with the service discovery mechanism to dynamically discover instances of back-end microservices and automatically update routing information.

In short, the service gateway plays an important role in the microservice architecture, providing a series of key functions, including request routing, load balancing, security, caching, monitoring, etc., to help build scalable, high-performance and secure microservices app. It provides a single entry point that simplifies client interaction with multiple microservices while providing some necessary infrastructure support.

What is the function of spring cloud circuit breaker?

Spring Cloud Circuit Breaker is an important component used to build fault tolerance and fault handling mechanisms in distributed systems. The main role of a circuit breaker is to provide fault-tolerant protection in the communication between services to ensure that the system continues to be available in the face of failure or high load conditions.

The following are the main functions of Spring Cloud circuit breakers:

Fault handling : Circuit breakers are able to detect failures or delays in remote services and take action when a failure is detected, rather than continuing to request services that may fail. This helps prevent failures from spreading throughout the system.
Avoid overload : When the backend service is unavailable or the response time is too long, continuous requests may cause the service to be overloaded. Circuit breakers reduce the load on backend services by stopping requests at appropriate times.
Fail fast : The circuit breaker responds quickly to faults rather than waiting for a timeout. This helps reduce client wait time and makes the system more responsive.
Self-recovery : Circuit breakers usually have a self-recovery mechanism. They will periodically try to request the backend service to check whether the service has returned to normal. Once service is up, the circuit breaker will allow requests to pass through.
Status monitoring : Spring Cloud circuit breakers usually provide monitoring and measurement functions, which can track the status, failure rate, timeout rate and other indicators of the circuit breaker in real time. This helps the operations team understand the health of the system.
Degrade strategy : A circuit breaker can define a degradation strategy. When a service is degraded, it can return predefined backup data or execute backup logic to ensure that the basic functions of the system continue to be available.
Adaptability : Circuit breakers can dynamically adjust their behavior based on the status and performance of backend services. This enables the system to adapt to varying loads and failures.

Spring Cloud circuit breakers are often integrated with other Spring Cloud components (such as Eureka, Ribbon, Feign, etc.) to provide comprehensive fault tolerance and load balancing solutions. Hystrix is a commonly used circuit breaker implementation in Spring Cloud. It provides a wealth of functions and configuration options that can be configured and used according to specific needs. Circuit breakers are one of the key components in building reliable and robust distributed systems, especially in microservice architectures where failures between multiple services are difficult to avoid.

Spring Cloud Security

When using Spring Cloud Security with Spring Cloud Gateway and authenticating using user information in the database, the following steps are required:

Add dependencies : Add the dependencies of Spring Cloud Gateway and Spring Cloud Security to the
project file:pom.xml

<dependencies>
    <!-- Spring Cloud Gateway -->
    <dependency>
        <groupId>org.springframework.cloud</groupId>
        <artifactId>spring-cloud-starter-gateway</artifactId>
    </dependency>

    <!-- Spring Cloud Security -->
    <dependency>
        <groupId>org.springframework.cloud</groupId>
        <artifactId>spring-cloud-starter-security</artifactId>
    </dependency>
</dependencies>

Create a custom UserDetailsService :
Create a UserDetailsServicecustom service that implements the interface and retrieves user information from the database and returns UserDetailsobjects. Make sure the service can query the database for user information based on username.

@Service
public class CustomUserDetailsService implements UserDetailsService {
      
      
    // 注入 UserRepository 或相应的数据访问层

    @Override
    public UserDetails loadUserByUsername(String username) throws UsernameNotFoundException {
      
      
        // 查询数据库中的用户信息并构建 UserDetails 对象
        // ...
    }
}

Configure Spring Security :
Create a Spring Security configuration class, register UserDetailsServiceand password encoders, and configure security rules. Make sure to configure appropriate roles and access rights.

@Configuration
@EnableWebSecurity
public class SecurityConfig extends WebSecurityConfigurerAdapter {
      
      
    @Autowired
    private UserDetailsService userDetailsService;

    @Bean
    public PasswordEncoder passwordEncoder() {
      
      
        return new BCryptPasswordEncoder();
    }

    @Override
    protected void configure(HttpSecurity http) throws Exception {
      
      
        http
            .authorizeRequests()
                .antMatchers("/secure/**").authenticated()
                .anyRequest().permitAll()
                .and()
            .httpBasic();
    }
}

Test security :
Make sure your database contains user information, including usernames and encrypted passwords. Test with a suitable username and password.

This way, when your Spring Cloud Gateway application starts, it will authenticate using the user information in the database. If the username and password match and the user has the required roles and access rights, the request will be allowed through, otherwise an authentication error will be returned. This approach enables you to ensure that only authorized users can access your microservices. Please note that the above example is a basic configuration and you can extend and customize the security configuration according to your actual needs.

What is a Hystrix circuit breaker? Do we need it?

Hystrix is an open source circuit breaker library originally created and open sourced by Netflix. Its main goal is to help build fault tolerance in distributed systems, specifically to provide a reliable solution when faced with problems such as communication failures, timeouts, delays, or insufficient resources between services. The function of the circuit breaker is to prevent the spread of faults and improve the availability and stability of the system.

Here are some of the key features and functions of Hystrix circuit breakers:

Failsafe : Hystrix can monitor calls to dependent services and take action when a failure occurs, rather than continuing to issue failed requests. This helps prevent failures from spreading throughout the system.
Fail fast : Hystrix responds to failures quickly instead of waiting for a timeout. This reduces the time the client waits and makes the system more responsive.
Self-recovery : Hystrix has the capability of self-recovery. It will periodically try to request dependent services to check whether the service has returned to normal. Once service is up, the circuit breaker will allow requests to pass through.
Throttling : Hystrix can set a concurrency limit for requests to ensure that too many requests do not flood the system, thereby protecting backend services from overload.
Metrics and Monitoring : Hystrix collects metrics data about the performance and status of circuit breakers, which can be used for monitoring and analysis. It can also be integrated with monitoring tools (such as Hystrix Dashboard, Turbine, etc.) to view the status of circuit breakers in real time.
Downgrade strategy : When a dependent service fails, Hystrix can implement a downgrade strategy, such as returning standby data or executing standby logic, to ensure that the basic functions of the system continue to be available.

Whether you need to use a Hystrix circuit breaker depends on the nature and architecture of your application. Here are some situations where you may want to consider using a Hystrix circuit breaker:

Microservices Architecture : In a microservices architecture, multiple services depend on each other and failures may propagate throughout the system. This situation can be effectively controlled and managed using Hystrix to prevent failure from spreading.
External dependencies : If your application depends on external services or resources (such as HTTP calls, database connections, message queues, etc.), these dependencies may malfunction or be unavailable. Hystrix can help you failsafe these external dependencies.
Fault tolerance : If your application has high requirements on availability and fault tolerance, using Hystrix can help you achieve these goals.
Resource isolation : Hystrix uses thread pools or semaphores to isolate calls to dependent services, thus preventing one failed service from affecting other services.

It should be noted that Hystrix has entered maintenance mode in recent years, and Netflix announced that it will stop the development of the Hystrix project. Therefore, if you are considering using Circuit Breaker in a new project, you might consider using other alternatives such as Resilience4j or Sentinel, which offer similar functionality and are maintained on an ongoing basis. Choosing the right circuit breaker library should be based on your specific needs and technology stack.

How does springcloud implement service registration?

It is a common practice to use Consul as a configuration center. Consul can not only be used as a service discovery and registration center, but also can store and distribute application configuration information. Here are the general steps for using Consul as a configuration center:

Add dependencies : First, you need to add the relevant dependencies of Spring Cloud Consul configuration to the
project file:pom.xml

<dependencies>
    <!-- Spring Cloud Consul Config -->
    <dependency>
        <groupId>org.springframework.cloud</groupId>
        <artifactId>spring-cloud-starter-consul-config</artifactId>
    </dependency>
</dependencies>

Configure Consul connection information :
In the configuration file of the Spring Boot application, configure the information to connect to Consul, including the address and port of the Consul server.
```
spring:
  cloud:
    consul:
      host: consul-server-host
      port: consul-server-port
```
Replace consul-server-hostand consul-server-portwith the host and port of your Consul server.
Create a configuration file :
Create a configuration file (usually in YAML or Properties format) and store the application's configuration information in it. You can create multiple configuration files as needed, such as application.yml, , application-dev.yml, application-prod.ymletc., to distinguish the configurations of different environments.
```
# application.yml
message: Hello from Consul Config
```

Enable the configuration center :
Add annotations to the startup class of the Spring Boot application @EnableAutoConfigurationand enable the Consul configuration center.

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.cloud.client.discovery.EnableDiscoveryClient;
import org.springframework.cloud.context.config.annotation.RefreshScope;

@SpringBootApplication
@EnableDiscoveryClient
@RefreshScope
public class YourApplication {
      
      
    public static void main(String[] args) {
      
      
        SpringApplication.run(YourApplication.class, args);
    }
}

@RefreshScopeAnnotations are used to implement dynamic refresh of configuration information to automatically update the application when the configuration changes.

Access configuration information :
In your application, you can access configuration information through Spring @Valueannotations or objects.Environment

import org.springframework.beans.factory.annotation.Value;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;

@RestController
public class ConfigController {
      
      
    @Value("${message}")
    private String message;

    @GetMapping("/message")
    public String getMessage() {
      
      
        return message;
    }
}

Start the application :
Start your Spring Boot application, it will automatically connect to the Consul configuration center and use the configuration information in the configuration center.
Modify configuration information :
When you need to change the configuration information, you can modify it directly in Consul's key-value store. The application automatically detects configuration changes and reloads.
Monitoring configuration changes :
If you wish to monitor configuration changes, you can use Spring Cloud Bus and a message broker (such as RabbitMQ or Kafka) to notify all application instances to update the configuration.

The above steps are based on the integration of Spring Cloud and Consul, allowing your application to dynamically obtain configuration information from the Consul configuration center. This approach makes configuration management more flexible, allowing configurations to be easily updated without redeploying the application.

Spring Cloud Sleuth

Spring Cloud Sleuth is an open source framework for distributed tracing that is part of the Spring Cloud ecosystem. It helps developers trace requests in distributed systems to identify problems and analyze performance bottlenecks. The main features of Spring Cloud Sleuth include:

Distributed tracing : Spring Cloud Sleuth has the ability to create unique tracing identifiers for requests in distributed applications, typically using traceId and spanId. These identifiers can span different services and components, allowing you to track the entire life cycle of a request.
Integration : Spring Cloud Sleuth can be easily integrated into Spring Cloud applications, including Spring Boot. It also supports integration with other distributed tracing systems such as Zipkin, Jaeger, etc.
Automated identification : Sleuth can automatically generate unique identifications for requests, so you don't need to manually write code to manage these identifications. This makes it easier to track requests in a distributed system.
Trace data collection : Spring Cloud Sleuth can send trace data to a centralized tracing server (such as Zipkin) in order to analyze the flow and performance of requests. This data includes the duration of the request, processing time for each service, etc.
Trace data visualization : By integrating with a trace server (such as Zipkin), you can visually view trace data, analyze the flow of requests, and identify potential performance bottlenecks.
Error and exception tracking : Spring Cloud Sleuth can also track errors and exceptions in requests, helping you quickly locate and solve problems.
Custom tracking : Although Sleuth provides an automated tracking mechanism, you can also customize tracking information as needed to monitor application behavior more granularly.

Using Spring Cloud Sleuth can improve the observability of distributed systems, helping developers identify and resolve performance issues, failures and delays. It is one of the useful tools for building microservice architecture, especially in large and complex microservice systems, and can provide key distributed tracing and performance analysis functions. Used together with other Spring Cloud components, highly observable microservice applications can be built.

What are the commonly used methods of ZuulFilter?

When using Zuul as an API gateway in Spring Cloud, you can create custom Zuul filters to perform logic at different stages of the request and response. Here are some commonly used Zuul filter methods:

pre Filters :
- shouldFilter(): This method determines whether to enable the current filter. Return truemeans enabled, return falsemeans disabled.
- run(): This is the main method for the actual filter logic. Executed before the request is routed. For example, logic such as authentication, certification, request logging, etc. can be added here.
route Filters :
- shouldFilter(): Similar to the pre-filter, determines whether to enable the current filter.
- run(): Executed when the request is routed. Here you can modify the request, such as modifying the request header, request path, etc.
post Filters :
- shouldFilter(): Similar to prefix and routing filters, determines whether to enable the current filter.
- run(): Executed before the response is sent back to the client. Usually here you can modify the response, add response headers, record response logs, etc.
error Filters :
- shouldFilter(): Determines whether to enable the current filter.
- run(): Executed when an error occurs during request processing. For example, you can log error information, handle exceptions, etc. here.

These methods are common methods for Zuul filters. You can create custom filters according to your needs and write logic in these methods to implement different functions. Filters are executed in a specific order in Zuul's request processing pipeline, and you can control the order in which they are executed by setting the order of filters.

When creating a custom Zuul filter, you need to extend ZuulFilterthe class and implement the appropriate methods from the above. Then, register the filter into Zuul so that it can perform the corresponding logic in request and response processing. By using Zuul filters, you can implement many useful functions, such as authentication, authorization, request forwarding, response processing, etc.

Spring Cloud Gateway

Spring Cloud Gateway is an API gateway tool built on Spring Framework 5, Project Reactor and Spring Boot 2. It allows you to build and deploy API gateways in a reactive programming manner for a series of common tasks in microservice architectures such as routing, filtering, load balancing, circuit breakers, and current limiting. The following are the main features and functions of Spring Cloud Gateway:

Dynamic routing : Gateway allows you to dynamically route requests to different backend services based on the request path, query parameters, request headers and other information.
Filters : Gateway supports custom filters. You can perform various operations before, after, and during error handling, such as authentication, modification of requests and responses, logging, etc.
Load balancing : It integrates a load balancing function that can evenly distribute requests to multiple backend service instances.
Circuit breaker : Gateway supports circuit breaker mode, which can avoid cascading request failures and improve system stability when the back-end service is unavailable.
Current limiting : You can use Gateway to implement request current limiting to prevent performance problems caused by excessive requests for a service.
Route matching : Supports flexible route matching rules, which can route requests to different backend services based on different URL paths and request conditions.
Reactive programming : Gateway is built based on the principles of reactive programming and uses Project Reactor to handle high-concurrency requests.
Integrated Spring ecosystem : Gateway is seamlessly integrated with the Spring ecosystem and can be used with components such as Spring Boot, Spring Cloud Config, and Spring Cloud Discovery.
Dynamic refresh : Supports dynamic refresh of routing configuration, allowing you to modify routing rules without restarting the application.
Highly scalable : Gateway's architecture allows you to easily add custom features and extend its functionality.

Spring Cloud Gateway is one of the key tools for building microservice architecture. It provides a flexible, high-performance and scalable way to manage API requests and responses. By using Gateway, you can better control request traffic, improve system availability, and implement common functions in various microservice architectures. However, it also requires a certain learning curve, especially for the concepts and usage of reactive programming.

Spring Cloud OpenFeign

Spring Cloud OpenFeign is a component of the Spring Cloud ecosystem that provides developers with a simple and powerful way to define and use declarative REST clients. With OpenFeign, you can call remote services just like calling local methods without having to manually write HTTP requests and handle HTTP responses.

The following are the main features and capabilities of Spring Cloud OpenFeign:

Declarative REST client : OpenFeign allows you to use annotations to define a REST client interface whose methods correspond to the HTTP endpoints of the remote service. This makes the code for remote calls more concise and easier to understand.
Automated HTTP requests : When calling methods of the declarative client interface, OpenFeign automatically generates and sends HTTP requests, so you don't need to manually construct HTTP requests.
Integrated Ribbon load balancing : OpenFeign integrates Ribbon, so it can automatically distribute requests to multiple service instances to achieve client load balancing.
Integrated Hystrix circuit breakers : OpenFeign also integrates Hystrix, allowing you to set circuit breakers for remote calls to handle situations where the remote service is unavailable or delayed.
Support Spring Cloud Contract : OpenFeign can be used with Spring Cloud Contract to define and test API contracts to ensure contract consistency between the client and server.
Customizability : Although OpenFeign provides many default configurations, you can still customize the configuration to meet specific needs, such as adding request interceptors, changing encoding methods, etc.

Using Spring Cloud OpenFeign, you can greatly simplify communication between microservices, reducing the workload of manually writing HTTP requests and processing HTTP responses. This allows developers to focus more on business logic while maintaining code clarity and maintainability. It is particularly suitable for building client applications in microservice architecture, such as microservice gateways, web applications, etc.

Both Eureka and ZooKeeper can provide service registration and discovery functions. Please tell us the difference between the two.

Both Eureka and ZooKeeper can be used as tools for service registration and discovery, but they have some differences in design, features and applicable scenarios:

Eureka:

Design concept :
- Eureka is Netflix's open source tool, specially designed for building cloud-based microservice architecture.
- Eureka adopts a "service registry" design pattern, where service providers register themselves to the Eureka server and send heartbeats regularly to keep registration information up-to-date.
CAP theorem :
- Eureka pursues high availability and partition fault tolerance (AP model), that is, in the case of network partitions, it pays more attention to availability rather than consistency. This means that in the case of network partitions, Eureka can continue to provide service registration and discovery functions, but it may cause eventual consistency issues with the data.
Purpose :
- Eureka is suitable for building cloud-native applications and microservices-based architectures, especially in AWS environments.

ZooKeeper:

Design concept :
- ZooKeeper is a distributed coordination service originally designed to build coordination and management functions for distributed systems.
- ZooKeeper provides a distributed file system and node-based data storage, which can be used to implement shared configuration, distributed locks, leader election and other functions of various distributed systems. Service registration and discovery are only one of them.
CAP theorem :
- ZooKeeper pursues strong consistency (CP model), that is, in the case of network partitions, it pays more attention to data consistency rather than availability. This means that in the case of network partitions, ZooKeeper may cause some services to be unavailable, but data consistency is guaranteed.
Purpose :
- ZooKeeper has a wider range of applications, not only for service registration and discovery, but also for distributed coordination tasks such as distributed configuration management, distributed locks, and leader election.

Summarize:

If the system you build is mainly based on microservice architecture and has high requirements for high availability, Eureka may be a more suitable choice.
If you need a general distributed coordination service, including service registration and discovery and other distributed tasks, and can tolerate sacrificing some availability to ensure data consistency in the case of network partitions, then ZooKeeper may be more suitable for you.
In addition, now in Spring Cloud, Eureka has been officially announced to stop maintenance, and it is recommended to use other service discovery tools, such as Consul or ZooKeeper. Therefore, Eureka may no longer be the first choice in new projects.

What is Hystrix? How does it achieve fault tolerance?

Hystrix is a fault-tolerant and delay-tolerant library open sourced by Netflix, used to build elastic services in distributed systems. Its goal is to prevent failures and latency problems in distributed systems from affecting the entire system, providing a series of mechanisms to handle failures and reduce the impact of services.

The following are the main features and fault-tolerant implementation of Hystrix:

Isolate service calls : Hystrix isolates service calls and places each service call in an independent thread pool. This means that problems with one service will not propagate to other services, preventing the spread of failures. If a service call fails or times out, it will only affect the thread pool of the service, but will not affect the stability of the entire system.
Circuit breaker mode : Hystrix implements the circuit breaker mode, which monitors the failure rate and response time of service calls. If the service call failure rate exceeds a certain threshold or the response time exceeds the specified time, Hystrix will open the fuse and stop making requests to the service. This avoids unnecessary calls to unavailable services and attempts to close circuit breakers after a period of time to restore the service.
Downgrade mechanism : Hystrix allows you to define a downgrade strategy. When a service call fails, you can perform alternate operations or return to default values to ensure the normal operation of the system. For example, cached data or a friendly error message can be returned.
Timeout control : Hystrix allows you to set the timeout for service calls. If the service call is not completed within the specified time, Hystrix will consider it to have timed out and implement a downgrade strategy.
Fallback strategy : Hystrix supports defining fallback strategies, which can specify backup logic to be executed when service calls fail to ensure system availability.
Metrics and Monitoring : Hystrix provides rich metrics and monitoring capabilities to collect and report performance and status information about service calls. This information can help operation and maintenance personnel understand the health status of the service and take timely measures to deal with failures.
Automatic recovery : Hystrix has an automatic recovery function. Once the service calls return to normal, it will automatically close the circuit breaker and resume requests for the service.

In short, Hystrix is a library used to build resilience and fault tolerance. Through mechanisms such as isolation, circuit breaker, degradation, timeout control, rollback strategy, etc., it makes distributed systems more stable and reliable in the face of faults and delays. It is widely used in large distributed systems such as Netflix and plays an important role in microservice architecture. However, it should be noted that Hystrix is no longer active under the maintenance of Netflix. It is recommended to use alternatives such as Spring Cloud Circuit Breaker.

Can SpringCloud Config achieve real-time refresh?

Yes, Spring Cloud Config can implement the function of refreshing configuration in real time. With Spring Cloud Config, you can centrally store configuration information in an external configuration server and let the application obtain the configuration from the server. When the configuration on the configuration server changes, Spring Cloud Config can notify the application that has obtained the configuration to achieve the effect of refreshing the configuration in real time.

Here are the general steps to implement real-time refresh of configurations:

Set up the configuration server : First, you need to set up a configuration server, which can be achieved using Spring Cloud Config Server. On the configuration server, you need to store the application's configuration files, for example, use Git, SVN, a local file system, etc. to manage these configuration files.
Integrate the Spring Cloud Config client in your application : In your application, introduce the Spring Cloud Config client dependency and specify the location of the configuration server and the name of the application in the configuration file. For example, configure in a bootstrap.propertiesor file:bootstrap.yml
```
spring:
  cloud:
    config:
      uri: http://config-server:8888  # 配置服务器的地址
    name: your-application-name  # 应用程序的名称
```
Configuring real-time refresh : To achieve real-time refresh configuration, you can use Spring Cloud Bus, usually combined with a message broker such as RabbitMQ or Kafka. After configuring Spring Cloud Bus, you can use /actuator/refreshthe endpoint to trigger a real-time refresh of the configuration.
Using configuration in your application : In your application, use Spring's @Valueannotations or @ConfigurationPropertiesto inject configuration properties. These properties will be obtained from the configuration server and refreshed in real time when the configuration changes.
Trigger configuration refresh : When the configuration needs to be refreshed, send a POST request to /actuator/refreshthe endpoint. This will notify the application to reload the configuration.

Through the above steps, you can implement the real-time refresh configuration function of Spring Cloud Config to update the application configuration at runtime without restarting the application. This is useful for dynamic configuration and failure recovery.

What is Spring Boot Executor

The Spring Boot Actuator is an important part of the Spring Boot framework. It provides a set of functions and endpoints for monitoring and managing Spring Boot applications. Actuator allows you to view your application's internal state, performance metrics, application environment, and other information at runtime and take management actions when needed, such as reloading configurations or shutting down the application. The main goal of Spring Boot Actuator is to provide support for runtime management and monitoring of applications to better understand and maintain applications.

Spring Boot Actuator includes multiple built-in endpoints, each of which provides different management and monitoring functions. Here are some commonly used Actuator endpoints:

/actuator/health : Provides health status information of the application and can be used for health checks.
/actuator/info : Allows applications to provide customized information, such as version numbers or other metadata.
/actuator/metrics : Provides a wealth of metrics, such as memory usage, thread pool status, number of HTTP requests, etc.
/actuator/env : Provides the application's environment properties and configuration information.
/actuator/loggers : used to view and modify logging levels.
/actuator/auditevents : Provides information about security audit events.
/actuator/httptrace : Record tracing information of HTTP requests and responses.
/actuator/threaddump : used to obtain thread dump information, which helps analyze the thread status of the application.
/actuator/mappings : Displays the mapping information of Spring MVC controller, including URL path and processing method.
/actuator/beans : Provides information about all Spring Beans in the application.

Spring Boot Actuator also supports custom endpoints that you can create to expose application-specific information or perform specific management operations.

The function of Actuator is very useful for monitoring and managing Spring Boot applications. It can help you quickly diagnose problems, monitor performance, and can be integrated with various monitoring systems (such as Prometheus, Grafana, Elasticsearch, etc.) to achieve more complex monitoring and Alert policy. To use Actuator, just add the corresponding dependencies to your Spring Boot project and enable the required endpoints in the configuration. However, be aware that since Actuator provides powerful management and monitoring capabilities, appropriate security configuration is required to avoid unauthorized access.