spring cloud gateway使用redis限流并观察

引入redis的reactive依赖

    <dependency>
      <groupId>org.springframework.boot</groupId>
      <artifactId>spring-boot-starter-data-redis-reactive</artifactId>
      <version>2.6.2</version>
    </dependency>

定义一下限流的具体维度

@Configuration
public class DemoConfiguration {

    @Bean
    public KeyResolver pathKeyResolver() {
        return exchange  -> Mono.just(exchange.getRequest().getPath().toString());
    }

}

两种方式，一种是application.yml中配置

spring:
    redis:
        host: 127.0.0.1
        port: 6379
    cloud:
        gateway:
            routes:
                - id: routeB
                  uri: http://www.b.com
                  predicates:
                      - Path=/pathB
                  filters:
                      - name: RequestRateLimiter
                        args:
                            # 每秒处理多少个平均请求数
                            redis-rate-limiter.replenishRate: 2
                            # 令允许在一秒钟内完成的最大请求数
                            redis-rate-limiter.burstCapacity: 2
                            # 获取 Bean 对象，@Bean的标识，默认bean名称与方法名一样。
                            key-resolver: "#{@apiKeyResolver}"

另一种在RouteDefinitionRepository的实现中，即动态路由的实现中

        FilterDefinition filter3 = new FilterDefinition();
        filter3.setName("RequestRateLimiter");
        Map<String, String> map3 = new HashMap<>();
        map3.put("redis-rate-limiter.replenishRate", "3");
        map3.put("redis-rate-limiter.burstCapacity", "2");
        map3.put("key-resolver", "#{@pathKeyResolver}");
        filter3.setArgs(map3);

可以在本地redis中使用monitor命令观察所执行的内容

127.0.0.1:6379> monitor
OK

那么来看一下同一秒中连续执行两次请求的情况：

1643107233.014412 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"
1643107233.014451 [0 lua] "TIME"
1643107233.014462 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"
1643107233.014469 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"
1643107233.014484 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "1"
1643107233.014495 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107233"
1643107233.326166 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"
1643107233.326219 [0 lua] "TIME"
1643107233.326228 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"
1643107233.326235 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"
1643107233.326251 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "0"
1643107233.326262 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107233"

再看一下同一秒内连续三次的情况：

1643107474.188667 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"
1643107474.188704 [0 lua] "TIME"
1643107474.188712 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"
1643107474.188718 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"
1643107474.188733 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "1"
1643107474.188745 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107474"
1643107474.347245 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"
1643107474.347283 [0 lua] "TIME"
1643107474.347291 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"
1643107474.347298 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"
1643107474.347313 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "0"
1643107474.347324 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107474"
1643107474.494758 [0 127.0.0.1:52263] "EVALSHA" "76a566c51f92d8f643d16e0ef0101663d5380dba" "2" "request_rate_limiter.{/client1}.tokens" "request_rate_limiter.{/client1}.timestamp" "2" "2" "" "1"
1643107474.494793 [0 lua] "TIME"
1643107474.494801 [0 lua] "get" "request_rate_limiter.{/client1}.tokens"
1643107474.494808 [0 lua] "get" "request_rate_limiter.{/client1}.timestamp"
1643107474.494823 [0 lua] "setex" "request_rate_limiter.{/client1}.tokens" "2" "0"
1643107474.494834 [0 lua] "setex" "request_rate_limiter.{/client1}.timestamp" "2" "1643107474"

第三次的请求， 已经被限流了， 返回了http code 429
执行的lua脚本具体内容从源码中可以看到：

redis.replicate_commands()

local tokens_key = KEYS[1]
local timestamp_key = KEYS[2]

local rate = tonumber(ARGV[1])
local capacity = tonumber(ARGV[2])
local now = redis.call('TIME')[1]
local requested = tonumber(ARGV[4])

local fill_time = capacity/rate
local ttl = math.floor(fill_time*2)

local last_tokens = tonumber(redis.call("get", tokens_key))
if last_tokens == nil then
  last_tokens = capacity
end

local last_refreshed = tonumber(redis.call("get", timestamp_key))
if last_refreshed == nil then
  last_refreshed = 0
end

local delta = math.max(0, now-last_refreshed)
local filled_tokens = math.min(capacity, last_tokens+(delta*rate))
local allowed = filled_tokens >= requested
local new_tokens = filled_tokens
local allowed_num = 0
if allowed then
  new_tokens = filled_tokens - requested
  allowed_num = 1
end


if ttl > 0 then
  redis.call("setex", tokens_key, ttl, new_tokens)
  redis.call("setex", timestamp_key, ttl, now)
end

return { allowed_num, new_tokens }