浅析Spring Boot单体应用熔断技术的使用

壹、入围方案

Sentinel

• github地址：https://sentinelguard.io/zh-cn/docs/introduction.html

• 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）

Hystrix

• github地址：https://github.com/Netflix/Hystrix/wiki

• 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

resilience4j

• github地址：https://resilience4j.readme.io/docs

• 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

贰、技术对比

叁、应用改造

3.1、sentinel

3.1.1、引入依赖

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<dependency>   <groupId>com.alibaba.cloudgroupId>   <artifactId>spring-cloud-starter-alibaba-sentinelartifactId>   <version>2.0.3.RELEASEversion> dependency>

3.1.2、改造接口或者service层

@SentinelResource(value = "allInfos",fallback = "errorReturn")

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@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   Classextends Throwable>[] exceptionsToTrace() default {Throwable.class};      //忽略异常   Classextends Throwable>[] exceptionsToIgnore() default {}; }

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@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");     }   }

3.1.3、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

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/**    * 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

3.1.4、接入dashboard

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spring:  cloud:   sentinel:    transport:     port: 8719     dashboard: localhost:8080

3.1.5、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

3.2、hystrix

3.2.1、引入依赖

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<dependency>   <groupId>org.springframework.bootgroupId>   <artifactId>spring-boot-starter-actuatorartifactId> dependency> <dependency>   <groupId>org.springframework.cloudgroupId>   <artifactId>spring-cloud-starter-netflix-hystrix-dashboardartifactId>   <version>2.0.4.RELEASEversion> dependency> <dependency>   <groupId>org.springframework.cloudgroupId>   <artifactId>spring-cloud-starter-netflix-hystrixartifactId>   <version>2.0.4.RELEASEversion> dependency>

3.2.2、改造接口

@HystrixCommand(fallbackMethod = "timeOutError")

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@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 {};      Classextends Throwable>[] ignoreExceptions() default {};      ObservableExecutionMode observableExecutionMode() default ObservableExecutionMode.EAGER;      HystrixException[] raiseHystrixExceptions() default {};      String defaultFallback() default ""; }

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@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");   } }

3.2.3、针对接口配置熔断方法

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/**  * 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"); }

3.2.4、配置默认策略

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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

3.2.5、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

3.3、resilience4j

3.3.1、引入依赖

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dependency>   <groupId>org.springframework.bootgroupId>   <artifactId>spring-boot-starter-webartifactId> dependency>    <dependency>   <groupId>org.springframework.bootgroupId>   <artifactId>spring-boot-starter-testartifactId>   <scope>testscope> dependency>    <dependency>   <groupId>io.github.resilience4jgroupId>   <artifactId>resilience4j-spring-boot2artifactId>   <version>1.6.1version> dependency>    <dependency>   <groupId>io.github.resilience4jgroupId>   <artifactId>resilience4j-bulkheadartifactId>   <version>1.6.1version> dependency>    <dependency>   <groupId>io.github.resilience4jgroupId>   <artifactId>resilience4j-ratelimiterartifactId>   <version>1.6.1version> dependency>    <dependency>   <groupId>io.github.resilience4jgroupId>   <artifactId>resilience4j-timelimiterartifactId>   <version>1.6.1version> dependency>

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

3.3.2、改造接口

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@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");   } }

3.3.3、针对接口配置熔断方法

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/**  * 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 ); }

3.3.4、配置规则

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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

3.3.5、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

【后面的话】

个人建议的话，比较推荐sentinel，它提供了很多接口便于开发者自己拓展，同时我觉得他的规则动态更新也比较方便。最后是相关示例代码:单体应用示例代码

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