Metrics是一个给JAVA服务的各项指标提供度量工具的包，在JAVA代码中嵌入Metrics代码，可以方便的对业务代码的各个指标进行监控，同时，Metrics能够很好的跟Ganlia、Graphite结合，方便的提供图形化接口。基本使用方式直接将core包（目前稳定版本3.0.1）导入pom文件即可，配置如下：
<dependency>
<groupId>com.codahale.metrics</groupId>
<artifactId>metrics-core</artifactId>
<version>3.0.1</version>
</dependency>提供的监控工具：
Gauges：用于某一个值的测量。
Counters：计数器是一个AtomicLong的实例，可以增加或减少其值。
Histograms: 统计数值的分布，例如最大值、最小值和平均值等。
Meters：测量一段时间内的事件发生率，例如TPS。
Timers：测量一段代码被调用的速率和持续时间的分布。
Health Checks：检测服务健康的状况。
提供的多种渠道输出：
ConsoleReporter：控制台
CsvReporter：CSV文件
Slf4jReporter：Logback、Log4j等日志输出
JmxReporter：基于JMX的输出
GangliaReporter：监控工具Ganglia
GraphiteReporter：监控工具Graphite
使用方式总结
1. 启动项目类
package demo.metrics;
import com.codahale.metrics.ConsoleReporter;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.ApplicationContext;
import java.util.concurrent.TimeUnit;
@SpringBootApplication
public class DemoApplication {
public static void main(String[] args) {
ApplicationContext ctx = SpringApplication.run(DemoApplication.class, args);
// 启动Reporter
ConsoleReporter reporter = ctx.getBean(ConsoleReporter.class);
reporter.start(1, TimeUnit.SECONDS);
}
}
2. 接受请求的类
package demo.metrics.action;
import com.codahale.metrics.Counter;
import com.codahale.metrics.Histogram;
import com.codahale.metrics.Meter;
import com.codahale.metrics.Timer;
import demo.metrics.config.ListManager;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.ResponseBody;
import java.util.Random;
@Controller
@RequestMapping("/")
public class MainController {
@Autowired
private Meter requestMeter;
@Autowired
private Histogram responseSizes;
@Autowired
private Counter pendingJobs;
@Autowired
private Timer responses;
@Autowired
private ListManager listManager;
@RequestMapping("/hello")
@ResponseBody
public String helloWorld() {
requestMeter.mark();
pendingJobs.inc();
responseSizes.update(new Random().nextInt(10));
listManager.getList().add(1);
final Timer.Context context = responses.time();
try {
return "Hello World";
} finally {
context.stop();
}
}
}3. 配置类
package demo.metrics.config;
import com.codahale.metrics.*;
import org.slf4j.LoggerFactory;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import java.util.concurrent.TimeUnit;
@Configuration
public class MetricConfig {
@Bean
public MetricRegistry metrics() {
return new MetricRegistry();
}
/**
* Reporter 数据的展现位置
*
* @param metrics
* @return
*/
@Bean
public ConsoleReporter consoleReporter(MetricRegistry metrics) {
return ConsoleReporter.forRegistry(metrics)
.convertRatesTo(TimeUnit.SECONDS)
.convertDurationsTo(TimeUnit.MILLISECONDS)
.build();
}
@Bean
public Slf4jReporter slf4jReporter(MetricRegistry metrics) {
return Slf4jReporter.forRegistry(metrics)
.outputTo(LoggerFactory.getLogger("demo.metrics"))
.convertRatesTo(TimeUnit.SECONDS)
.convertDurationsTo(TimeUnit.MILLISECONDS)
.build();
}
@Bean
public JmxReporter jmxReporter(MetricRegistry metrics) {
return JmxReporter.forRegistry(metrics).build();
}
/**
* 自定义单位
*
* @param metrics
* @return
*/
@Bean
public ListManager listManager(MetricRegistry metrics) {
return new ListManager(metrics);
}
/**
* TPS 计算器
*
* @param metrics
* @return
*/
@Bean
public Meter requestMeter(MetricRegistry metrics) {
return metrics.meter("request");
}
/**
* 直方图
*
* @param metrics
* @return
*/
@Bean
public Histogram responseSizes(MetricRegistry metrics) {
return metrics.histogram("response-sizes");
}
/**
* 计数器
*
* @param metrics
* @return
*/
@Bean
public Counter pendingJobs(MetricRegistry metrics) {
return metrics.counter("requestCount");
}
/**
* 计时器
*
* @param metrics
* @return
*/
@Bean
public Timer responses(MetricRegistry metrics) {
return metrics.timer("executeTime");
}
}五种Metrics类型示例：
1. Gauges
Gauges是一个最简单的计量，一般用来统计瞬时状态的数据信息，比如系统中处于pending状态的job。测试代码
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.Gauge;
import com.codahale.metrics.JmxReporter;
import com.codahale.metrics.MetricRegistry;
import java.util.Queue;
import java.util.concurrent.LinkedBlockingDeque;
import java.util.concurrent.TimeUnit;
/**
* User: hzwangxx
* Date: 14-2-17
* Time: 14:47
* 测试Gauges，实时统计pending状态的job个数
*/
public class TestGauges {
/**
* 实例化一个registry，最核心的一个模块，相当于一个应用程序的metrics系统的容器，维护一个Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
private static Queue<String> queue = new LinkedBlockingDeque<String>();
/**
* 在控制台上打印输出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
public static void main(String[] args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
//实例化一个Gauge
Gauge<Integer> gauge = new Gauge<Integer>() {
@Override
public Integer getValue() {
return queue.size();
}
};
//注册到容器中
metrics.register(MetricRegistry.name(TestGauges.class, "pending-job", "size"), gauge);
//测试JMX
JmxReporter jmxReporter = JmxReporter.forRegistry(metrics).build();
jmxReporter.start();
//模拟数据
for (int i=0; i<20; i++){
queue.add("a");
Thread.sleep(1000);
}
}
}
/*
console output:
14-2-17 15:29:35 ===============================================================
-- Gauges ----------------------------------------------------------------------
com.netease.test.metrics.TestGauges.pending-job.size
value = 4
14-2-17 15:29:38 ===============================================================
-- Gauges ----------------------------------------------------------------------
com.netease.test.metrics.TestGauges.pending-job.size
value = 6
14-2-17 15:29:41 ===============================================================
-- Gauges ----------------------------------------------------------------------
com.netease.test.metrics.TestGauges.pending-job.size
value = 9
*/通过以上步骤将会向MetricsRegistry容器中注册一个名字为com.netease.test.metrics .TestGauges.pending-job.size的metrics，实时获取队列长度的指标。另外，Core包种还扩展了几种特定的Gauge：
- JMX Gauges—提供给第三方库只通过JMX将指标暴露出来。
- Ratio Gauges—简单地通过创建一个gauge计算两个数的比值。
- Cached Gauges—对某些计量指标提供缓存
Derivative Gauges—提供Gauge的值是基于其他Gauge值的接口。
2. Counter
Counter是Gauge的一个特例，维护一个计数器，可以通过inc()和dec()方法对计数器做修改。使用步骤与Gauge基本类似，在MetricRegistry中提供了静态方法可以直接实例化一个Counter。
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.Counter;
import com.codahale.metrics.MetricRegistry;
import java.util.LinkedList;
import java.util.Queue;
import java.util.concurrent.TimeUnit;
import static com.codahale.metrics.MetricRegistry.*;
/**
* User: hzwangxx
* Date: 14-2-14
* Time: 14:02
* 测试Counter
*/
public class TestCounter {
/**
* 实例化一个registry，最核心的一个模块，相当于一个应用程序的metrics系统的容器，维护一个Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
/**
* 在控制台上打印输出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
/**
* 实例化一个counter,同样可以通过如下方式进行实例化再注册进去
* pendingJobs = new Counter();
* metrics.register(MetricRegistry.name(TestCounter.class, "pending-jobs"), pendingJobs);
*/
private static Counter pendingJobs = metrics.counter(name(TestCounter.class, "pedding-jobs"));
// private static Counter pendingJobs = metrics.counter(MetricRegistry.name(TestCounter.class, "pedding-jobs"));
private static Queue<String> queue = new LinkedList<String>();
public static void add(String str) {
pendingJobs.inc();
queue.offer(str);
}
public String take() {
pendingJobs.dec();
return queue.poll();
}
public static void main(String[]args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
while(true){
add("1");
Thread.sleep(1000);
}
}
}
/*
console output：
14-2-17 17:52:34 ===============================================================
-- Counters --------------------------------------------------------------------
com.netease.test.metrics.TestCounter.pedding-jobs
count = 4
14-2-17 17:52:37 ===============================================================
-- Counters --------------------------------------------------------------------
com.netease.test.metrics.TestCounter.pedding-jobs
count = 6
14-2-17 17:52:40 ===============================================================
-- Counters --------------------------------------------------------------------
com.netease.test.metrics.TestCounter.pedding-jobs
count = 9
*/3. Meters
Meters用来度量某个时间段的平均处理次数（request per second），每1、5、15分钟的TPS。比如一个service的请求数，通过metrics.meter()实例化一个Meter之后，然后通过meter.mark()方法就能将本次请求记录下来。统计结果有总的请求数，平均每秒的请求数，以及最近的1、5、15分钟的平均TPS。
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.Meter;
import com.codahale.metrics.MetricRegistry;
import java.util.concurrent.TimeUnit;
import static com.codahale.metrics.MetricRegistry.*;
/**
* User: hzwangxx
* Date: 14-2-17
* Time: 18:34
* 测试Meters
*/
public class TestMeters {
/**
* 实例化一个registry，最核心的一个模块，相当于一个应用程序的metrics系统的容器，维护一个Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
/**
* 在控制台上打印输出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
/**
* 实例化一个Meter
*/
private static final Meter requests = metrics.meter(name(TestMeters.class, "request"));
public static void handleRequest() {
requests.mark();
}
public static void main(String[] args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
while(true){
handleRequest();
Thread.sleep(100);
}
}
}
/*
14-2-17 18:43:08 ===============================================================
-- Meters ----------------------------------------------------------------------
com.netease.test.metrics.TestMeters.request
count = 30
mean rate = 9.95 events/second
1-minute rate = 0.00 events/second
5-minute rate = 0.00 events/second
15-minute rate = 0.00 events/second
14-2-17 18:43:11 ===============================================================
-- Meters ----------------------------------------------------------------------
com.netease.test.metrics.TestMeters.request
count = 60
mean rate = 9.99 events/second
1-minute rate = 10.00 events/second
5-minute rate = 10.00 events/second
15-minute rate = 10.00 events/second
14-2-17 18:43:14 ===============================================================
-- Meters ----------------------------------------------------------------------
com.netease.test.metrics.TestMeters.request
count = 90
mean rate = 9.99 events/second
1-minute rate = 10.00 events/second
5-minute rate = 10.00 events/second
15-minute rate = 10.00 events/second
*/4. Histograms
Histograms主要使用来统计数据的分布情况，最大值、最小值、平均值、中位数，百分比（75%、90%、95%、98%、99%和99.9%）。例如，需要统计某个页面的请求响应时间分布情况，可以使用该种类型的Metrics进行统计。具体的样例代码如下：
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.Histogram;
import com.codahale.metrics.MetricRegistry;
import java.util.Random;
import java.util.concurrent.TimeUnit;
import static com.codahale.metrics.MetricRegistry.name;
/**
* User: hzwangxx
* Date: 14-2-17
* Time: 18:34
* 测试Histograms
*/
public class TestHistograms {
/**
* 实例化一个registry，最核心的一个模块，相当于一个应用程序的metrics系统的容器，维护一个Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
/**
* 在控制台上打印输出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
/**
* 实例化一个Histograms
*/
private static final Histogram randomNums = metrics.histogram(name(TestHistograms.class, "random"));
public static void handleRequest(double random) {
randomNums.update((int) (random*100));
}
public static void main(String[] args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
Random rand = new Random();
while(true){
handleRequest(rand.nextDouble());
Thread.sleep(100);
}
}
}
/*
14-2-17 19:39:11 ===============================================================
-- Histograms ------------------------------------------------------------------
com.netease.test.metrics.TestHistograms.random
count = 30
min = 1
max = 97
mean = 45.93
stddev = 29.12
median = 39.50
75% <= 71.00
95% <= 95.90
98% <= 97.00
99% <= 97.00
99.9% <= 97.00
14-2-17 19:39:14 ===============================================================
-- Histograms ------------------------------------------------------------------
com.netease.test.metrics.TestHistograms.random
count = 60
min = 0
max = 97
mean = 41.17
stddev = 28.60
median = 34.50
75% <= 69.75
95% <= 92.90
98% <= 96.56
99% <= 97.00
99.9% <= 97.00
14-2-17 19:39:17 ===============================================================
-- Histograms ------------------------------------------------------------------
com.netease.test.metrics.TestHistograms.random
count = 90
min = 0
max = 97
mean = 44.67
stddev = 28.47
median = 43.00
75% <= 71.00
95% <= 91.90
98% <= 96.18
99% <= 97.00
99.9% <= 97.00
*/5. Timers
Timers主要是用来统计某一块代码段的执行时间以及其分布情况，具体是基于Histograms和Meters来实现的。样例代码如下：
package com.netease.test.metrics;
import com.codahale.metrics.ConsoleReporter;
import com.codahale.metrics.MetricRegistry;
import com.codahale.metrics.Timer;
import java.util.Random;
import java.util.concurrent.TimeUnit;
import static com.codahale.metrics.MetricRegistry.name;
/**
* User: hzwangxx
* Date: 14-2-17
* Time: 18:34
* 测试Timers
*/
public class TestTimers {
/**
* 实例化一个registry，最核心的一个模块，相当于一个应用程序的metrics系统的容器，维护一个Map
*/
private static final MetricRegistry metrics = new MetricRegistry();
/**
* 在控制台上打印输出
*/
private static ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
/**
* 实例化一个Meter
*/
// private static final Timer requests = metrics.timer(name(TestTimers.class, "request"));
private static final Timer requests = metrics.timer(name(TestTimers.class, "request"));
public static void handleRequest(int sleep) {
Timer.Context context = requests.time();
try {
//some operator
Thread.sleep(sleep);
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
context.stop();
}
}
public static void main(String[] args) throws InterruptedException {
reporter.start(3, TimeUnit.SECONDS);
Random random = new Random();
while(true){
handleRequest(random.nextInt(1000));
}
}
}
/*
14-2-18 9:31:54 ================================================================
-- Timers ----------------------------------------------------------------------
com.netease.test.metrics.TestTimers.request
count = 4
mean rate = 1.33 calls/second
1-minute rate = 0.00 calls/second
5-minute rate = 0.00 calls/second
15-minute rate = 0.00 calls/second
min = 483.07 milliseconds
max = 901.92 milliseconds
mean = 612.64 milliseconds
stddev = 196.32 milliseconds
median = 532.79 milliseconds
75% <= 818.31 milliseconds
95% <= 901.92 milliseconds
98% <= 901.92 milliseconds
99% <= 901.92 milliseconds
99.9% <= 901.92 milliseconds
14-2-18 9:31:57 ================================================================
-- Timers ----------------------------------------------------------------------
com.netease.test.metrics.TestTimers.request
count = 8
mean rate = 1.33 calls/second
1-minute rate = 1.40 calls/second
5-minute rate = 1.40 calls/second
15-minute rate = 1.40 calls/second
min = 41.07 milliseconds
max = 968.19 milliseconds
mean = 639.50 milliseconds
stddev = 306.12 milliseconds
median = 692.77 milliseconds
75% <= 885.96 milliseconds
95% <= 968.19 milliseconds
98% <= 968.19 milliseconds
99% <= 968.19 milliseconds
99.9% <= 968.19 milliseconds
14-2-18 9:32:00 ================================================================
-- Timers ----------------------------------------------------------------------
com.netease.test.metrics.TestTimers.request
count = 15
mean rate = 1.67 calls/second
1-minute rate = 1.40 calls/second
5-minute rate = 1.40 calls/second
15-minute rate = 1.40 calls/second
min = 41.07 milliseconds
max = 968.19 milliseconds
mean = 591.35 milliseconds
stddev = 302.96 milliseconds
median = 650.56 milliseconds
75% <= 838.07 milliseconds
95% <= 968.19 milliseconds
98% <= 968.19 milliseconds
99% <= 968.19 milliseconds
99.9% <= 968.19 milliseconds
*/Health Checks
Metrics提供了一个独立的模块：Health Checks，用于对Application、其子模块或者关联模块的运行是否正常做检测。该模块是独立metrics-core模块的，使用时则导入metrics-healthchecks包。使用起来和与上述几种类型的Metrics有点类似，但是需要重新实例化一个Metrics容器HealthCheckRegistry，待检测模块继承抽象类HealthCheck并实现check()方法即可，然后将该模块注册到HealthCheckRegistry中，判断的时候通过isHealthy()接口即可。如下示例代码：
package com.netease.test.metrics;
import com.codahale.metrics.health.HealthCheck;
import com.codahale.metrics.health.HealthCheckRegistry;
import java.util.Map;
import java.util.Random;
/**
* User: hzwangxx
* Date: 14-2-18
* Time: 9:57
*/
public class DatabaseHealthCheck extends HealthCheck{
private final Database database;
public DatabaseHealthCheck(Database database) {
this.database = database;
}
@Override
protected Result check() throws Exception {
if (database.ping()) {
return Result.healthy();
}
return Result.unhealthy("Can't ping database.");
}
/**
* 模拟Database对象
*/
static class Database {
/**
* 模拟database的ping方法
* @return 随机返回boolean值
*/
public boolean ping() {
Random random = new Random();
return random.nextBoolean();
}
}
public static void main(String[] args) {
// MetricRegistry metrics = new MetricRegistry();
// ConsoleReporter reporter = ConsoleReporter.forRegistry(metrics).build();
HealthCheckRegistry registry = new HealthCheckRegistry();
registry.register("database1", new DatabaseHealthCheck(new Database()));
registry.register("database2", new DatabaseHealthCheck(new Database()));
while (true) {
for (Map.Entry<String, Result> entry : registry.runHealthChecks().entrySet()) {
if (entry.getValue().isHealthy()) {
System.out.println(entry.getKey() + ": OK");
} else {
System.err.println(entry.getKey() + ": FAIL, error message: " + entry.getValue().getMessage());
final Throwable e = entry.getValue().getError();
if (e != null) {
e.printStackTrace();
}
}
}
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
}
}
}
}
/*
console output:
database1: OK
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: OK
database1: OK
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: OK
database1: FAIL, error message: Can't ping database.
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: FAIL, error message: Can't ping database.
database1: OK
database2: OK
database1: OK
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: OK
database1: OK
database2: OK
database1: FAIL, error message: Can't ping database.
database2: OK
database1: OK
database2: OK
database1: OK
database2: OK
database1: OK
database2: FAIL, error message: Can't ping database.
database1: FAIL, error message: Can't ping database.
database2: FAIL, error message: Can't ping database.
*/本文内容转载自： http://www.cnblogs.com/nexiyi/p/metrics_sample_2.html,