Gateway Redis令牌桶請求限流過濾器
阿新 • • 發佈：2020-09-08
spring cloud gateway預設基於redis令牌桶演算法進行微服務的限流保護，採用RateLimter限流演算法來實現。
1.引入依賴包
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-gateway</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.cloud</
2、yml中配置redis
spring:
application:
name: mima-cloud-gateway
redis:
database: 1
host: localhost
port: 6379
password:
3、配置KeyResolver——RateLimiteConfig.java(介面限流/ip限流/使用者限流)
package com.mkevin.gateway.config;
import org.springframework.cloud.gateway.filter.ratelimit.KeyResolver;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Primary;
import reactor.core.publisher.Mono;
/**
* 限流配置KeyResolver——有三種寫法(介面限流/ip限流/使用者限流)
*/
@Configuration
public class RateLimiteConfig {
/**
* 介面限流：根據請求路徑限流
* @return
*/
/*
如果不使用@Primary註解，會報如下錯誤，需要注意
Description:
Parameter 1 of method requestRateLimiterGatewayFilterFactory in org.springframework.cloud.gateway.config.GatewayAutoConfiguration required a single bean, but 3 were found:
- pathKeyResolver: defined by method 'pathKeyResolver' in class path resource [com/mkevin/gateway/config/RateLimiteConfig.class]
- ipKeyResolver: defined by method 'ipKeyResolver' in class path resource [com/mkevin/gateway/config/RateLimiteConfig.class]
- userKeyResolver: defined by method 'userKeyResolver' in class path resource [com/mkevin/gateway/config/RateLimiteConfig.class]
Action:
Consider marking one of the beans as @Primary, updating the consumer to accept multiple beans, or using @Qualifier
to identify the bean that should be consumed
*/
@Bean
@Primary
public KeyResolver pathKeyResolver() {
//寫法1
return exchange -> Mono.just(
exchange.getRequest()
.getPath()
.toString()
);
/*
//寫法2
return new KeyResolver() {
@Override
public Mono<String> resolve(ServerWebExchange exchange) {
return Mono.just(exchange.getRequest()
.getPath()
.toString());
}
};
*/
}
/**
* 根據請求IP限流
* @return
*/
@Bean
public KeyResolver ipKeyResolver() {
return exchange -> Mono.just(
exchange.getRequest()
.getRemoteAddress()
.getHostName()
);
}
/**
* 根據請求引數中的userId進行限流
*
* 請求地址寫法：http://localhost:8801/rate/123?userId=lisi
*
* @return
*/
@Bean
public KeyResolver userKeyResolver() {
return exchange -> Mono.just(
exchange.getRequest()
.getQueryParams()
.getFirst("userId")
);
}
}
4、yml中配置spring.cloud.gateway.routes.filters
spring:
cloud:
gateway:
routes:
- id: rate-limit-demo
uri: lb://mima-cloud-producer
predicates:
#訪問路徑：http://localhost:8801/rate/123
- Path=/rate/**
filters:
- name: RequestRateLimiter
args:
# 令牌桶每秒填充平均速率, 允許使用者每秒處理多少個請求。
redis-rate-limiter.replenishRate: 1
# 令牌桶的容量，允許在1s內完成的最大請求數。
redis-rate-limiter.burstCapacity: 2
# 使用SpEL表示式從Spring容器中獲取Bean物件, 檢視RateLimiteConfig實現類中的方法名
key-resolver: "#{@pathKeyResolver}"
#key-resolver: "#{@ipKeyResolver}"
#key-resolver: "#{@userKeyResolver}"
5、訪問地址測試
http://localhost:8801/rate/123
當F5頻繁重新整理請求介面時，控制檯會報429錯誤狀態碼，提示我們請求過多，如下：
[開始]請求路徑:/rate/123
[應答]請求路徑:/rate/123耗時:2ms
2020-09-08 16:23:27.253 DEBUG 18512 --- [ioEventLoop-4-1] o.s.w.s.adapter.HttpWebHandlerAdapter : [62eb90e0] Completed 429 TOO_MANY_REQUESTS
2020-09-08 16:23:27.394 DEBUG 18512 --- [ctor-http-nio-2] o.s.w.s.adapter.HttpWebHandlerAdapter : [62eb90e0] HTTP GET "/rate/123"
corsFilter... run
[開始]請求路徑:/rate/123
[應答]請求路徑:/rate/123耗時:2ms
2020-09-08 16:23:27.397 DEBUG 18512 --- [ioEventLoop-4-1] o.s.w.s.adapter.HttpWebHandlerAdapter : [62eb90e0] Completed 429 TOO_MANY_REQUESTS
2020-09-08 16:23:27.536 DEBUG 18512 --- [ctor-http-nio-2] o.s.w.s.adapter.HttpWebHandlerAdapter : [62eb90e0] HTTP GET "/rate/123"
corsFilter... run
6、當發生限流時，會向redis中儲存兩個資料
127.0.0.1:1>keys *
1) "request_rate_limiter.{/rate/123}.timestamp"
2) "request_rate_limiter.{/rate/123}.tokens"
127.0.0.1:1>keys *
1) "request_rate_limiter.{0:0:0:0:0:0:0:1}.timestamp"
2) "request_rate_limiter.{0:0:0:0:0:0:0:1}.tokens"
127.0.0.1:1>keys *
1) "request_rate_limiter.{lisi}.timestamp"
2) "request_rate_limiter.{lisi}.tokens"
引數說明：
request_rate_limiter.{key}.timestamp：
儲存的是當前時間的秒數，也就是System.currentTimeMillis()/1000或者Instant.now().getEpochSecond()。
request_rate_limiter.{key}.tokens：
儲存的是當前這秒鐘對應的可用令牌數量
7、完整yml配置檔案
# 開啟resilience4j斷路器
# spring.cloud.circuitbreaker.resilience4j.enabled: true
# 設定hystrix斷路器超時時間
# hystrix.command.fallbackcmd.execution.isolation.thread.timeoutInMilliseconds: 2000
spring:
application:
name: mima-cloud-gateway
redis:
database: 1
host: localhost
port: 6379
password:
cloud:
gateway:
routes:
- id: rate-limit-demo
uri: lb://mima-cloud-producer
predicates:
#訪問路徑：http://localhost:8801/rate/123
- Path=/rate/**
filters:
- name: RequestRateLimiter
args:
# 令牌桶每秒填充平均速率, 允許使用者每秒處理多少個請求。
redis-rate-limiter.replenishRate: 1
# 令牌桶的容量，允許在1s內完成的最大請求數。
redis-rate-limiter.burstCapacity: 2
# 使用SpEL表示式從Spring容器中獲取Bean物件, 檢視RateLimiteConfig實現類中的同名方法
#key-resolver: "#{@pathKeyResolver}"
#key-resolver: "#{@ipKeyResolver}"
#請求地址寫法：http://localhost:8801/rate/123?userId=lisi
key-resolver: "#{@userKeyResolver}"
# The RequestRateLimiter GatewayFilter Factory
# The Redis RateLimiter
# Modify a Request Body GatewayFilter Factory 測試版本，未來可能改動
# Modify a Response Body GatewayFilter Factory 測試版本，未來可能改動
server:
port: 8801
eureka:
client:
serviceUrl:
#defaultZone: http://kevin:123456@localhost:8761/eureka/
defaultZone: http://localhost:8761/eureka/
instance:
prefer-ip-address: true
#instance-id: ${spring.application.name}:${spring.cloud.client.ip-address:}:${server.port}
instance-id: ${spring.application.name}:${server.port}
debug: true
management:
endpoints:
web:
exposure:
include: '*'
endpoint:
health:
show-details: always
shutdown: true