浅析Spring Boot单体应用熔断技术的使用

网友投稿 396 2022-11-05


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

com.alibaba.cloud

spring-cloud-starter-alibaba-sentinel

2.0.3.RELEASE

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 JfScUDUsonResult 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

org.springframework.boot

spring-boot-starter-actuator

org.springframework.cloud

spring-cloud-starter-netflix-hystrix-dashboard

2.0.4.RELEASE

org.springframework.cloud

spring-cloud-starter-netflix-hystrix

2.0.4.RELEASE

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>

org.springframework.boot

spring-boot-starter-web

org.springframework.boot

spring-boot-starter-test

test

io.github.resilience4j

resilience4j-spring-boot2

1.6.1

io.github.resilience4j

resilience4j-bulkhead

1.6.1

io.github.resilience4j

resilience4j-ratelimiter

1.6.1

io.github.resilience4j

resilience4j-timelimiter

1.6.1

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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