JAVA微服务Spring Cloud熔断器熔断降级常见三种方案

JAVA微服务Spring Cloud熔断器熔断降级常见三种方案

码农世界 2024-05-31 后端 76 次浏览 0个评论

目录

一、熔断方案

1、Sentinel

2、Hystrix

3、resilience4j

二、技术对比

三、应用改造

1、sentinel

1.1、引入依赖

1.2、改造接口或者service层

1.3、针对接口配置熔断方法或者限流方法

1.4、接入dashboard

1.5、规则持久化和动态更新

2、hystrix

2.1、引入依赖

2.2、改造接口

2.3、针对接口配置熔断方法

2.4、配置默认策略

2.5、接入监控

3、resilience4j

3.1、引入依赖

3.2、改造接口

3.3、针对接口配置熔断方法

3.4、配置规则

3.5、配置监控

一、熔断方案

1、Sentinel

阿里出品，Spring Cloud Alibaba限流组件，目前持续更新中

自带Dashboard，可以查看接口Qps等，并且可以动态修改各种规则

流量控制，直接限流、冷启动、排队

熔断降级，限制并发限制数和相应时间

系统负载保护，提供系统级别防护，限制总体CPU等

主要核心：资源，规则(流量控制规则、熔断降级规则、系统保护规则、来源访问控制规则 和 热点参数规则。)，和指标

文档非常清晰和详细，中文

支持动态规则(推模式和拉模式)

2、Hystrix

Netflix出品，Spring Cloud Netflix限流组件，已经停止新特性开发，只进行bug修复，最近更新为2018年，功能稳定

有简单的dashboard页面

以隔离和熔断为主的容错机制，超时或被熔断的调用将会快速失败，并可以提供 fallback 机制的初代熔断框架，异常统计基于滑动窗口

3、resilience4j

是一款轻量、简单，并且文档非常清晰、丰富的熔断工具。是Hystrix替代品，实现思路和Hystrix一致，目前持续更新中

需要自己对micrometer、prometheus以及Dropwizard metrics进行整合

CircuitBreaker 熔断

Bulkhead 隔离

RateLimiter QPS限制

Retry 重试

TimeLimiter 超时限制

Cache 缓存

自己实现(基于Guava)

基于Guava的令牌桶，可以轻松实现对QPS进行限流

二、技术对比

JAVA微服务Spring Cloud熔断器熔断降级常见三种方案

三、应用改造

1、sentinel

1.1、引入依赖


    com.alibaba.cloud
    spring-cloud-starter-alibaba-sentinel

1.2、改造接口或者service层

@SentinelResource(value = "allInfos",fallback = "errorReturn")
@Target({ElementType.METHOD, ElementType.TYPE})
@Retention(RetentionPolicy.RUNTIME)
@Inherited
public @interface SentinelResource {
    //资源名称
    String value() default "";
    //流量方向
    EntryType entryType() default EntryType.OUT;
    //资源类型
    int resourceType() default 0;
    //异常处理方法
    String blockHandler() default "";
    //异常处理类
    Class>[] blockHandlerClass() default {};
    //熔断方法
    String fallback() default "";
    //默认熔断方法
    String defaultFallback() default "";
    //熔断类
    Class>[] fallbackClass() default {};
    //统计异常
    Class extends Throwable>[] exceptionsToTrace() default {Throwable.class};
    //忽略异常
    Class extends Throwable>[] exceptionsToIgnore() default {};
}
@RequestMapping("/get")
@ResponseBody
@SentinelResource(value = "allInfos",fallback = "errorReturn")
public JsonResult allInfos(HttpServletRequest request, HttpServletResponse response, @RequestParam Integer num){
    try {
        if (num % 2 == 0) {
            log.info("num % 2 == 0");
            throw new BaseException("something bad with 2", 400);
        }
        return JsonResult.ok();
    } catch (ProgramException e) {
        log.info("error");
        return JsonResult.error("error");
    }
}

1.3、针对接口配置熔断方法或者限流方法

默认过滤拦截所有Controller接口

/**
* 限流，参数需要和方法保持一致
* @param request
* @param response
* @param num
* @return
* @throws BlockException
*/
public JsonResult errorReturn(HttpServletRequest request, HttpServletResponse response, @RequestParam Integer num) throws BlockException {
    return JsonResult.error("error 限流" + num );
}
/**
* 熔断，参数需要和方法保持一直，并且需要添加BlockException异常
* @param request
* @param response
* @param num
* @param b
* @return
* @throws BlockException
*/
public JsonResult errorReturn(HttpServletRequest request, HttpServletResponse response, @RequestParam Integer num,BlockException b) throws BlockException {
    return JsonResult.error("error 熔断" + num );
}

注意也可以不配置限流或者熔断方法。通过全局异常去捕获UndeclaredThrowableException或者BlockException避免大量的开发量

1.4、接入dashboard

spring:

        cloud:

                sentinel:

                        transport:

                                port: 8719

                                dashboard: localhost:8080

JAVA微服务Spring Cloud熔断器熔断降级常见三种方案

1.5、规则持久化和动态更新

接入配置中心如：zookeeper等等，并对规则采用推模式

2、hystrix

2.1、引入依赖


    org.springframework.boot
    spring-boot-starter-actuator


    org.springframework.cloud
    spring-cloud-starter-netflix-hystrix-dashboard


    org.springframework.cloud
    spring-cloud-starter-netflix-hystrix

2.2、改造接口

@HystrixCommand(fallbackMethod = "timeOutError")
@Target({ElementType.METHOD})
@Retention(RetentionPolicy.RUNTIME)
@Inherited
@Documented
public @interface HystrixCommand {
    String groupKey() default "";
    String commandKey() default "";
    String threadPoolKey() default "";
    String fallbackMethod() default "";
    HystrixProperty[] commandProperties() default {};
    HystrixProperty[] threadPoolProperties() default {};
    Class extends Throwable>[] ignoreExceptions() default {};
    ObservableExecutionMode observableExecutionMode() default ObservableExecutionMode.EAGER;
    HystrixException[] raiseHystrixExceptions() default {};
    String defaultFallback() default "";
}
@RequestMapping("/get")
@ResponseBody
@HystrixCommand(fallbackMethod = "fallbackMethod")
public JsonResult allInfos(HttpServletRequest request, HttpServletResponse response, @RequestParam Integer num){
    try {
        if (num % 3 == 0) {
            log.info("num % 3 == 0");
            throw new BaseException("something bad whitch 3", 400);
        }
        return JsonResult.ok();
    } catch (ProgramException | InterruptedException exception) {
        log.info("error");
        return JsonResult.error("error");
    }
}

2.3、针对接口配置熔断方法

/**
* 该方法是熔断回调方法，参数需要和接口保持一致
* @param request
* @param response
* @param num
* @return
*/
public JsonResult fallbackMethod(HttpServletRequest request, HttpServletResponse response, @RequestParam Integer num) {
    response.setStatus(500);
    log.info("发生了熔断！！");
    return JsonResult.error("熔断");
}

2.4、配置默认策略

hystrix:

        command:

                default:

                        execution:

                                isolation:

                                        strategy: THREAD

                                thread:

                                        # 线程超时15秒,调用Fallback方法

                                        timeoutInMilliseconds: 15000

                                metrics:

                                        rollingStats:

                                                timeInMilliseconds: 15000

                                        circuitBreaker:

                                        # 10秒内出现3个以上请求(已临近阀值),并且出错率在50%以上,开启断路器.断开服务,调用Fallback方法

                                                requestVolumeThreshold: 3

                                                sleepWindowInMilliseconds: 10000

2.5、接入监控

曲线：用来记录2分钟内流量的相对变化，我们可以通过它来观察到流量的上升和下降趋势。

集群监控需要用到注册中心

3、resilience4j

3.1、引入依赖

        
            io.github.resilience4j
            resilience4j-spring-boot2
        
        
            io.github.resilience4j
            resilience4j-bulkhead
        
        
            io.github.resilience4j
            resilience4j-ratelimiter
        
        
            io.github.resilience4j
            resilience4j-timelimiter

可以按需要引入：bulkhead，ratelimiter，timelimiter等

3.2、改造接口

@RequestMapping("/get")
@ResponseBody
//@TimeLimiter(name = "BulkheadA",fallbackMethod = "fallbackMethod")
@CircuitBreaker(name = "BulkheadA",fallbackMethod = "fallbackMethod")
@Bulkhead(name = "BulkheadA",fallbackMethod = "fallbackMethod")
public JsonResult allInfos(HttpServletRequest request, HttpServletResponse response, @RequestParam Integer num){
    log.info("param----->" + num);
    try {
        //Thread.sleep(num);
        if (num % 2 == 0) {
            log.info("num % 2 == 0");
            throw new BaseException("something bad with 2", 400);
        }
        if (num % 3 == 0) {
            log.info("num % 3 == 0");
            throw new BaseException("something bad whitch 3", 400);
        }
        if (num % 5 == 0) {
            log.info("num % 5 == 0");
            throw new ProgramException("something bad whitch 5", 400);
        }
        if (num % 7 == 0) {
            log.info("num % 7 == 0");
            int res = 1 / 0;
        }
        return JsonResult.ok();
    } catch (BufferUnderflowException e) {
        log.info("error");
        return JsonResult.error("error");
    }
}

3.3、针对接口配置熔断方法

/**
* 需要参数一致，并且加上相应异常
* @param request
* @param response
* @param num
* @param exception
* @return
*/
public JsonResult fallbackMethod(HttpServletRequest request, HttpServletResponse response, @RequestParam Integer num, BulkheadFullException exception) {
    return JsonResult.error("error 熔断" + num );
}

3.4、配置规则

resilience4j.circuitbreaker:

instances:

backendA:

registerHealthIndicator: true

slidingWindowSize: 100

backendB:

registerHealthIndicator: true

slidingWindowSize: 10

permittedNumberOfCallsInHalfOpenState: 3

slidingWindowType: TIME_BASED

minimumNumberOfCalls: 20

waitDurationInOpenState: 50s

failureRateThreshold: 50

eventConsumerBufferSize: 10

recordFailurePredicate: io.github.robwin.exception.RecordFailurePredicate

resilience4j.retry:

instances:

backendA:

maxRetryAttempts: 3

waitDuration: 10s

enableExponentialBackoff: true

exponentialBackoffMultiplier: 2

retryExceptions:

- org.springframework.web.client.HttpServerErrorException

- java.io.IOException

ignoreExceptions:

- io.github.robwin.exception.BusinessException

backendB:

maxRetryAttempts: 3

waitDuration: 10s

retryExceptions:

- org.springframework.web.client.HttpServerErrorException

- java.io.IOException

ignoreExceptions:

- io.github.robwin.exception.BusinessException

resilience4j.bulkhead:

instances:

backendA:

maxConcurrentCalls: 10

backendB:

maxWaitDuration: 10ms

maxConcurrentCalls: 20

resilience4j.thread-pool-bulkhead:

instances:

backendC:

maxThreadPoolSize: 1

coreThreadPoolSize: 1

queueCapacity: 1

resilience4j.ratelimiter:

instances:

backendA:

limitForPeriod: 10

limitRefreshPeriod: 1s

timeoutDuration: 0

registerHealthIndicator: true

eventConsumerBufferSize: 100

backendB:

limitForPeriod: 6

limitRefreshPeriod: 500ms

timeoutDuration: 3s

resilience4j.timelimiter:

instances:

backendA:

timeoutDuration: 2s

cancelRunningFuture: true

backendB:

timeoutDuration: 1s

cancelRunningFuture: false

配置的规则可以被代码覆盖

3.5、配置监控

如grafana等

肆、关注点

是否需要过滤部分异常

是否需要全局默认规则

可能需要引入其他中间件

k8s流量控制

规则存储和动态修改

接入改造代价

转载请注明来自码农世界，本文标题：《JAVA微服务Spring Cloud熔断器熔断降级常见三种方案》

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