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
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
以上就是浅析Spring Boot单体应用熔断技术的使用的详细内容,更多关于Spring Boot单体应用熔断技术的资料请关注易盾网络其它相关文章!