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

<dependency>
  <groupId>com.alibaba.cloud</groupId>
  <artifactId>spring-cloud-starter-alibaba-sentinel</artifactId>
  <version>2.0.3.RELEASE</version>
</dependency>

3.1.2、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");
    }
  }

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

/**
   * 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

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

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
  <groupId>org.springframework.cloud</groupId>
  <artifactId>spring-cloud-starter-netflix-hystrix-dashboard</artifactId>
  <version>2.0.4.RELEASE</version>
</dependency>
<dependency>
  <groupId>org.springframework.cloud</groupId>
  <artifactId>spring-cloud-starter-netflix-hystrix</artifactId>
  <version>2.0.4.RELEASE</version>
</dependency>

3.2.2、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");
  }
}

3.2.3、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");
}

3.2.4、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

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

dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-web</artifactId>
</dependency>

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-test</artifactId>
  <scope>test</scope>
</dependency>

<dependency>
  <groupId>io.github.resilience4j</groupId>
  <artifactId>resilience4j-spring-boot2</artifactId>
  <version>1.6.1</version>
</dependency>

<dependency>
  <groupId>io.github.resilience4j</groupId>
  <artifactId>resilience4j-bulkhead</artifactId>
  <version>1.6.1</version>
</dependency>

<dependency>
  <groupId>io.github.resilience4j</groupId>
  <artifactId>resilience4j-ratelimiter</artifactId>
  <version>1.6.1</version>
</dependency>

<dependency>
  <groupId>io.github.resilience4j</groupId>
  <artifactId>resilience4j-timelimiter</artifactId>
  <version>1.6.1</version>
</dependency>

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

3.3.2、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");
  }
}

3.3.3、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 );
}

3.3.4、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

3.3.5、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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