com.taotao.boot.prometheus.collector.PrometheusCollector Maven / Gradle / Ivy

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/*
 * Copyright (c) 2020-2030, Shuigedeng ([email protected] & https://blog.taotaocloud.top/).
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.taotao.boot.prometheus.collector;

import io.micrometer.core.instrument.Counter;
import io.micrometer.core.instrument.Gauge;
import io.micrometer.core.instrument.distribution.TimeWindowPercentileHistogram;
import io.micrometer.prometheusmetrics.PrometheusDistributionSummary;
import io.micrometer.prometheusmetrics.PrometheusMeterRegistry;
import org.springframework.beans.factory.InitializingBean;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Component;
@Component
public class PrometheusCollector implements InitializingBean {

    private final PrometheusMeterRegistry prometheusMeterRegistry;

    @Value("${spring.application.name}")
    private String applicationName;

    /**
     * requestCounter
     */
    public Counter requestCounter;
    /**
     * inprogressRequests
     */
    public Gauge inprogressRequests;
    /**
     * requestLatencyHistogram
     */
    public TimeWindowPercentileHistogram requestLatencyHistogram;
    /**
     * requestLatency
     */
    public PrometheusDistributionSummary requestLatency;

	public PrometheusCollector(PrometheusMeterRegistry prometheusMeterRegistry) {
		this.prometheusMeterRegistry = prometheusMeterRegistry;
	}

	/**
     * 服务启动时创建自定义指标
     */
    private void init() {
        /**
         * 用于统计请求总数 计数器可以用于记录只会增加不会减少的指标类型，比如记录应用请求的总量(http_requests_total)，
         * cpu使用时间(process_cpu_seconds_total)等。 一般而言，Counter类型的metrics指标在命名中 我们使用_total结束。
         */
        this.requestCounter = Counter.builder(getName() + "_requests_total")
                .description("请求总数数据")
                .tags("service", "method", "code", "dd")
                .register(prometheusMeterRegistry);

        /**
         * 使用Gauge可以反映应用的当前状态,例如在监控主机时，主机当前空闲的内容大小(node_memory_MemFree)， 37 *
         * 可用内存大小(node_memory_MemAvailable)。或者容器当前的CPU使用率,内存使用率。这里我们使用 Gauge记录当前应用正在处理的Http请求数量。
         */
        this.inprogressRequests = Gauge.builder(getName() + "_http_inprogress_requests", ()-> 0.0)
                .tags("path", "method")
                .description("进行中的请求状态数据")
                .register(prometheusMeterRegistry);

        /**
         * 主要用于在指定分布范围内(Buckets)记录大小(如http request bytes)或者事件发生的次数。
         * 以请求响应时间requests_latency_seconds为例
         */
		//todo: 需要修改
//        this.requestLatencyHistogram = Histogram.build()
//                .name(getName() + "_http_requests_latency_seconds_histogram")
//                .labelNames("path", "method", "code")
//                .help("以秒为单位的请求延迟直方图数据")
//                .register(prometheusMeterRegistry.getPrometheusRegistry());

        /**
         * 和Histogram类似，不同在于Histogram可以通过histogram_quantile函数在服务器端计算分位数，而
         * Sumamry的分位数则是直接在客户端进行定义。因此对于分位数的计算。 Summary在通过PromQL进行查询时
         * 有更好的性能表现，而Histogram则会消耗更多的资源。相对的对于客户端而言Histogram消耗的资源更少 用于统计TP50，TP90
         */
		//todo: 需要修改
//        this.requestLatency = Summary.build()
//                .name(getName() + "_request_latency")
//                .quantile(0.5, 0.05)
//                .quantile(0.9, 0.01)
//                .labelNames("path", "method", "code")
//                .help("以秒为单位的请求延迟分数数据")
//                .register(prometheusMeterRegistry.getPrometheusRegistry());
    }

    private String getName() {
        return applicationName.replaceAll("-", "_");
    }

    @Override
    public void afterPropertiesSet() throws Exception {
        init();
    }
}