1.简介
系统越来越大，我们所需要关联的组件也越来越多，为了更好的排查问题，我们需要对不同的指标进行监控，从而发现问题，Metrics作为一款监控指标的度量类库，提供了许多工具帮助开发者来完成自定义的监控工作。

2.环境
添加maven依赖

<dependency>
    <groupId>io.dropwizard.metrics</groupId>
    <artifactId>metrics-core</artifactId>
    <version>${metrics.version}</version>
</dependency>

3.使用
Metrics中MetricRegistry是中心容器，它是程序中所有度量的容器，所有新的度量工具都要注册到一个MetricRegistry实例中才可以使用，尽量在一个应用中保持让这个MetricRegistry实例保持单例。

Metrics提供了多个指标 Gauges、Counters、Histograms、Meters、Timers

3.1Timers
Timer用于统计QPS和耗时，这里用于统记DB查询所耗时间，由于try-catch-resources属性自动stop了，也可以显示调用Context stop方法

@RestController
@RequestMapping("/metric")
public class MetricCtrl {

    private static final MetricRegistry metricRegistry = new MetricRegistry();

    private Timer timer;

    private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metricRegistry).build();//使用控制台打印

    @Autowired
    private DailyTradeMarkingDao dailyTradeMarkingDao;//获取用户天维度的标记

    @PostConstruct
    public void setup() {
        timer = metricRegistry.timer("dbQuery");
        reporter.start(10, TimeUnit.SECONDS);//报告10秒输出一次
    }

    @PostMapping("/timer")
    public JsonResult testTimer() {
        List<DailyTradeMarking> markingList = null;
        try (Timer.Context context = timer.time()) {
            markingList = dailyTradeMarkingDao.getByAccountIdAndStockId(401422L, 14L);
        }
        return JsonResult.ok(markingList);
    }
}

显示结果：
-- Timers ----------------------------------------------------------------------
dbQuery
             count = 7
         mean rate = 0.12 calls/second
     1-minute rate = 0.08 calls/second
     5-minute rate = 0.02 calls/second
    15-minute rate = 0.01 calls/second
               min = 42.75 milliseconds
               max = 1228.59 milliseconds
              mean = 211.34 milliseconds
            stddev = 401.27 milliseconds
            median = 46.35 milliseconds
              75% <= 87.25 milliseconds
              95% <= 1228.59 milliseconds
              98% <= 1228.59 milliseconds
              99% <= 1228.59 milliseconds
            99.9% <= 1228.59 milliseconds

3.2Meters
Meter用于测试QPS ，这里统计/meter接口的QPS是多少

{
    meter = metricRegistry.meter("qps");
    @PostMapping("/meter")
    public JsonResult testMeter() {
        meter.mark();//根据不同的需求设置不同的n ,默认1
        return JsonResult.ok();
    }
}


显示结果：


-- Meters ----------------------------------------------------------------------
qps
             count = 6
         mean rate = 0.02 events/second
     1-minute rate = 0.09 events/second
     5-minute rate = 0.02 events/second
    15-minute rate = 0.01 events/second

3.3Histograms
Histogram 是一个统计图表，可以统计次数、最大、最小、平均值等, 这里记录reques长度的大小

{
    
    histogram = metricRegistry.histogram("request.size");
    @PostMapping("/histogram")
    public JsonResult testHistogram(HttpServletRequest request) {
        histogram.update(request.toString().length());
        return JsonResult.ok();
    }
}
显示结果：
-- Histograms ------------------------------------------------------------------
request.size
             count = 8
               min = 52
               max = 52
              mean = 52.00
            stddev = 0.00
            median = 52.00
              75% <= 52.00
              95% <= 52.00
              98% <= 52.00
              99% <= 52.00
            99.9% <= 52.00

3.4 Counters
counter用来统计次数，这里用来统计大于5的个数有多少个

{
    
    counter = metricRegistry.counter("count");
    counterFive = metricRegistry.counter("counterFive");

    @PostMapping("/counter")
    public JsonResult testCounter() {
        Random random = new Random();
        counter.inc();
        if (random.nextInt(10) > 5) {
            counterFive.inc();
        }
        return JsonResult.ok();
    }

}


显示结果：
-- Counters --------------------------------------------------------------------
counterFive
             count = 1
count
             count = 7

3.5Gauges
gauge可以实现自己的度量标准，这里用来检测缓存的大小

{
    private LoadingCache<Integer, Integer> cache = CacheBuilder.newBuilder()
        .maximumSize(1000)
        .refreshAfterWrite(10, TimeUnit.SECONDS).build(
        new CacheLoader<Integer, Integer>() {
            @Override
            public Integer load(Integer key) throws Exception {
                return 1;
            }
        }
    );
    gauge = metricRegistry.gauge("cache.size", new MetricRegistry.MetricSupplier<Gauge>() {
        @Override
        public Gauge newMetric() {
            return new Gauge<Long>() {
                @Override
                public Long getValue() {
                    return cache.size();
                }
            };
        }
    });
    
    @PostMapping("/gauge")  
    public JsonResult testGauge() throws ExecutionException {
        Random random = new Random();
        cache.get(random.nextInt(100));
        return JsonResult.ok(gauge.getValue());
    }
}




显示结果：
-- Gauges ----------------------------------------------------------------------
cache.size
             value = 10
-- Gauges ----------------------------------------------------------------------
cache.size
             value = 11

4.数据上报（显示）

ConsoleReporter reporter = ConsoleReporter.forRegistry(metricRegistry).build();//输出在控制台

也可以继承ScheduledReporter实现自己的聚合格式