Pengantar Metrik Dropwizard

1. Perkenalan

Metrics adalah pustaka Java yang menyediakan alat ukur untuk aplikasi Java.

Ini memiliki beberapa modul, dan dalam artikel ini, kami akan menguraikan modul metrics-core, modul metrics-healthchecks, modul metrics-servlet, dan modul metrics-servlet, dan membuat sketsa sisanya, untuk referensi Anda.

2. Modul metrik-inti

2.1. Dependensi Maven

Untuk menggunakan modul metrics-core , hanya ada satu dependensi yang diperlukan yang perlu ditambahkan ke file pom.xml :

 io.dropwizard.metrics metrics-core 3.1.2  

Dan Anda dapat menemukan versi terbarunya di sini.

2.2. MetricRegistry

Sederhananya, kita akan menggunakan kelas MetricRegistry untuk mendaftarkan satu atau beberapa metrik.

Kami dapat menggunakan satu registri metrik untuk semua metrik kami, tetapi jika kami ingin menggunakan metode pelaporan yang berbeda untuk metrik yang berbeda, kami juga dapat membagi metrik kami menjadi beberapa grup dan menggunakan registri metrik yang berbeda untuk setiap grup.

Mari buat MetricRegistry sekarang:

MetricRegistry metricRegistry = new MetricRegistry();

Dan kemudian kita dapat mendaftarkan beberapa metrik dengan MetricRegistry ini :

Meter meter1 = new Meter(); metricRegistry.register("meter1", meter1); Meter meter2 = metricRegistry.meter("meter2"); 

Ada dua cara dasar untuk membuat metrik baru: membuat instance sendiri atau mendapatkannya dari registry metrik. Seperti yang Anda lihat, kami menggunakan keduanya pada contoh di atas, kami membuat instance objek Meter "meter1" dan kami mendapatkan objek Meter "meter2" lainnya yang dibuat oleh metricRegistry .

Dalam registri metrik, setiap metrik memiliki nama unik, seperti yang kami gunakan "meter1" dan "meter2" sebagai nama metrik di atas. MetricRegistry juga menyediakan sekumpulan metode pembantu statis untuk membantu kami membuat nama metrik yang tepat:

String name1 = MetricRegistry.name(Filter.class, "request", "count"); String name2 = MetricRegistry.name("CustomFilter", "response", "count"); 

Jika kita perlu mengelola sekumpulan registri metrik, kita dapat menggunakan kelas SharedMetricRegistries , yang merupakan singleton dan thread-safe. Kita dapat menambahkan daftar metrik ke dalamnya, mengambil daftar metrik ini darinya, dan menghapusnya:

SharedMetricRegistries.add("default", metricRegistry); MetricRegistry retrievedMetricRegistry = SharedMetricRegistries.getOrCreate("default"); SharedMetricRegistries.remove("default"); 

3. Konsep Metrik

Modul metrik-inti menyediakan beberapa jenis metrik yang umum digunakan: Meter , Gauge , Penghitung , Histogram dan Timer , dan Reporter untuk mengeluarkan nilai metrik .

3.1. Meter

Sebuah Meteran mengukur jumlah dan kecepatan kejadian kejadian:

Meter meter = new Meter(); long initCount = meter.getCount(); assertThat(initCount, equalTo(0L)); meter.mark(); assertThat(meter.getCount(), equalTo(1L)); meter.mark(20); assertThat(meter.getCount(), equalTo(21L)); double meanRate = meter.getMeanRate(); double oneMinRate = meter.getOneMinuteRate(); double fiveMinRate = meter.getFiveMinuteRate(); double fifteenMinRate = meter.getFifteenMinuteRate(); 

Metode getCount () mengembalikan jumlah kejadian kejadian, dan metode mark () menambahkan 1 atau n ke jumlah kejadian kejadian. The meter objek menyediakan empat tingkat yang mewakili tingkat rata-rata untuk seluruh meter seumur hidup, untuk terakhir satu menit, untuk terakhir lima menit dan untuk kuartal terakhir, masing-masing.

3.2. Mengukur

Gauge adalah antarmuka yang hanya digunakan untuk mengembalikan nilai tertentu. Modul metrics-core menyediakan beberapa implementasinya: RatioGauge , CachedGauge , DerivativeGauge dan JmxAttributeGauge .

RatioGauge adalah kelas abstrak dan mengukur rasio satu nilai ke nilai lainnya.

Mari kita lihat bagaimana cara menggunakannya. Pertama, kami menerapkan kelas AttendanceRatioGauge :

public class AttendanceRatioGauge extends RatioGauge { private int attendanceCount; private int courseCount; @Override protected Ratio getRatio() { return Ratio.of(attendanceCount, courseCount); } // standard constructors } 

Dan kemudian kami mengujinya:

RatioGauge ratioGauge = new AttendanceRatioGauge(15, 20); assertThat(ratioGauge.getValue(), equalTo(0.75)); 

CachedGauge adalah kelas abstrak lain yang dapat menyimpan nilai, oleh karena itu, ini sangat berguna ketika nilainya mahal untuk dihitung. Untuk menggunakannya, kita perlu mengimplementasikan kelas ActiveUsersGauge :

public class ActiveUsersGauge extends CachedGauge
    
      { @Override protected List loadValue() { return getActiveUserCount(); } private List getActiveUserCount() { List result = new ArrayList(); result.add(12L); return result; } // standard constructors }
    

Kemudian kami mengujinya untuk melihat apakah itu berfungsi seperti yang diharapkan:

Gauge
    
      activeUsersGauge = new ActiveUsersGauge(15, TimeUnit.MINUTES); List expected = new ArrayList(); expected.add(12L); assertThat(activeUsersGauge.getValue(), equalTo(expected)); 
    

Kami menyetel waktu kedaluwarsa cache menjadi 15 menit saat membuat instance ActiveUsersGauge .

DerivativeGauge juga merupakan kelas abstrak dan memungkinkan Anda mendapatkan nilai dari Gauge lain sebagai nilainya.

Mari kita lihat contohnya:

public class ActiveUserCountGauge extends DerivativeGauge
    
      { @Override protected Integer transform(List value) { return value.size(); } // standard constructors }
    

This Gauge derives its value from an ActiveUsersGauge, so we expect it to be the value from the base list's size:

Gauge
    
      activeUsersGauge = new ActiveUsersGauge(15, TimeUnit.MINUTES); Gauge activeUserCountGauge = new ActiveUserCountGauge(activeUsersGauge); assertThat(activeUserCountGauge.getValue(), equalTo(1)); 
    

JmxAttributeGauge is used when we need to access other libraries' metrics exposed via JMX.

3.3. Counter

The Counter is used for recording incrementations and decrementations:

Counter counter = new Counter(); long initCount = counter.getCount(); assertThat(initCount, equalTo(0L)); counter.inc(); assertThat(counter.getCount(), equalTo(1L)); counter.inc(11); assertThat(counter.getCount(), equalTo(12L)); counter.dec(); assertThat(counter.getCount(), equalTo(11L)); counter.dec(6); assertThat(counter.getCount(), equalTo(5L));

3.4. Histogram

Histogram is used for keeping track of a stream of Long values and it analyzes their statistical characteristics such as max, min, mean, median, standard deviation, 75th percentile and so on:

Histogram histogram = new Histogram(new UniformReservoir()); histogram.update(5); long count1 = histogram.getCount(); assertThat(count1, equalTo(1L)); Snapshot snapshot1 = histogram.getSnapshot(); assertThat(snapshot1.getValues().length, equalTo(1)); assertThat(snapshot1.getValues()[0], equalTo(5L)); histogram.update(20); long count2 = histogram.getCount(); assertThat(count2, equalTo(2L)); Snapshot snapshot2 = histogram.getSnapshot(); assertThat(snapshot2.getValues().length, equalTo(2)); assertThat(snapshot2.getValues()[1], equalTo(20L)); assertThat(snapshot2.getMax(), equalTo(20L)); assertThat(snapshot2.getMean(), equalTo(12.5)); assertEquals(10.6, snapshot2.getStdDev(), 0.1); assertThat(snapshot2.get75thPercentile(), equalTo(20.0)); assertThat(snapshot2.get999thPercentile(), equalTo(20.0)); 

Histogram samples the data by using reservoir sampling, and when we instantiate a Histogram object, we need to set its reservoir explicitly.

Reservoir is an interface and metrics-core provides four implementations of them: ExponentiallyDecayingReservoir, UniformReservoir, SlidingTimeWindowReservoir, SlidingWindowReservoir.

In the section above, we mentioned that a metric can also be created by MetricRegistry, besides using a constructor. When we use metricRegistry.histogram(), it returns a Histogram instance with ExponentiallyDecayingReservoir implementation.

3.5. Timer

Timer is used for keeping track of multiple timing durations which are represented by Context objects, and it also provides their statistical data:

Timer timer = new Timer(); Timer.Context context1 = timer.time(); TimeUnit.SECONDS.sleep(5); long elapsed1 = context1.stop(); assertEquals(5000000000L, elapsed1, 1000000); assertThat(timer.getCount(), equalTo(1L)); assertEquals(0.2, timer.getMeanRate(), 0.1); Timer.Context context2 = timer.time(); TimeUnit.SECONDS.sleep(2); context2.close(); assertThat(timer.getCount(), equalTo(2L)); assertEquals(0.3, timer.getMeanRate(), 0.1); 

3.6. Reporter

When we need to output our measurements, we can use Reporter. This is an interface, and the metrics-core module provides several implementations of it, such as ConsoleReporter, CsvReporter, Slf4jReporter, JmxReporter and so on.

Here we use ConsoleReporter as an example:

MetricRegistry metricRegistry = new MetricRegistry(); Meter meter = metricRegistry.meter("meter"); meter.mark(); meter.mark(200); Histogram histogram = metricRegistry.histogram("histogram"); histogram.update(12); histogram.update(17); Counter counter = metricRegistry.counter("counter"); counter.inc(); counter.dec(); ConsoleReporter reporter = ConsoleReporter.forRegistry(metricRegistry).build(); reporter.start(5, TimeUnit.MICROSECONDS); reporter.report(); 

Here is the sample output of the ConsoleReporter:

-- Histograms ------------------------------------------------------------------ histogram count = 2 min = 12 max = 17 mean = 14.50 stddev = 2.50 median = 17.00 75% <= 17.00 95% <= 17.00 98% <= 17.00 99% <= 17.00 99.9% <= 17.00 -- Meters ---------------------------------------------------------------------- meter count = 201 mean rate = 1756.87 events/second 1-minute rate = 0.00 events/second 5-minute rate = 0.00 events/second 15-minute rate = 0.00 events/second 

4. Module metrics-healthchecks

Metrics has an extension metrics-healthchecks module for dealing with health checks.

4.1. Maven Dependencies

To use the metrics-healthchecks module, we need to add this dependency to the pom.xml file:

 io.dropwizard.metrics metrics-healthchecks 3.1.2 

And you can find its latest version here.

4.2. Usage

First, we need several classes which are responsible for specific health check operations, and these classes must implement HealthCheck.

For example, we use DatabaseHealthCheck and UserCenterHealthCheck:

public class DatabaseHealthCheck extends HealthCheck { @Override protected Result check() throws Exception { return Result.healthy(); } } 
public class UserCenterHealthCheck extends HealthCheck { @Override protected Result check() throws Exception { return Result.healthy(); } } 

Then, we need a HealthCheckRegistry (which is just like MetricRegistry), and register the DatabaseHealthCheck and UserCenterHealthCheck with it:

HealthCheckRegistry healthCheckRegistry = new HealthCheckRegistry(); healthCheckRegistry.register("db", new DatabaseHealthCheck()); healthCheckRegistry.register("uc", new UserCenterHealthCheck()); assertThat(healthCheckRegistry.getNames().size(), equalTo(2)); 

We can also unregister the HealthCheck:

healthCheckRegistry.unregister("uc"); assertThat(healthCheckRegistry.getNames().size(), equalTo(1)); 

We can run all the HealthCheck instances:

Map results = healthCheckRegistry.runHealthChecks(); for (Map.Entry entry : results.entrySet()) { assertThat(entry.getValue().isHealthy(), equalTo(true)); } 

Finally, we can run a specific HealthCheck instance:

healthCheckRegistry.runHealthCheck("db"); 

5. Module metrics-servlets

Metrics provides us a handful of useful servlets which allow us to access metrics related data through HTTP requests.

5.1. Maven Dependencies

To use the metrics-servlets module, we need to add this dependency to the pom.xml file:

 io.dropwizard.metrics metrics-servlets 3.1.2 

And you can find its latest version here.

5.2. HealthCheckServlet Usage

HealthCheckServlet provides health check results. First, we need to create a ServletContextListener which exposes our HealthCheckRegistry:

public class MyHealthCheckServletContextListener extends HealthCheckServlet.ContextListener { public static HealthCheckRegistry HEALTH_CHECK_REGISTRY = new HealthCheckRegistry(); static { HEALTH_CHECK_REGISTRY.register("db", new DatabaseHealthCheck()); } @Override protected HealthCheckRegistry getHealthCheckRegistry() { return HEALTH_CHECK_REGISTRY; } } 

Then, we add both this listener and HealthCheckServlet into the web.xml file:

 com.baeldung.metrics.servlets.MyHealthCheckServletContextListener   healthCheck com.codahale.metrics.servlets.HealthCheckServlet   healthCheck /healthcheck 

Now we can start the web application, and send a GET request to “//localhost:8080/healthcheck” to get health check results. Its response should be like this:

{ "db": { "healthy": true } }

5.3. ThreadDumpServlet Usage

ThreadDumpServlet provides information about all live threads in the JVM, their states, their stack traces, and the state of any locks they may be waiting for.

If we want to use it, we simply need to add these into the web.xml file:

 threadDump com.codahale.metrics.servlets.ThreadDumpServlet   threadDump /threaddump 

Thread dump data will be available at “//localhost:8080/threaddump”.

5.4. PingServlet Usage

PingServlet can be used to test if the application is running. We add these into the web.xml file:

 ping com.codahale.metrics.servlets.PingServlet   ping /ping 

And then send a GET request to “//localhost:8080/ping”. The response's status code is 200 and its content is “pong”.

5.5. MetricsServlet Usage

MetricsServlet provides metrics data. First, we need to create a ServletContextListener which exposes our MetricRegistry:

public class MyMetricsServletContextListener extends MetricsServlet.ContextListener { private static MetricRegistry METRIC_REGISTRY = new MetricRegistry(); static { Counter counter = METRIC_REGISTRY.counter("m01-counter"); counter.inc(); Histogram histogram = METRIC_REGISTRY.histogram("m02-histogram"); histogram.update(5); histogram.update(20); histogram.update(100); } @Override protected MetricRegistry getMetricRegistry() { return METRIC_REGISTRY; } } 

Both this listener and MetricsServlet need to be added into web.xml:

 com.codahale.metrics.servlets.MyMetricsServletContextListener   metrics com.codahale.metrics.servlets.MetricsServlet   metrics /metrics 

This will be exposed in our web application at “//localhost:8080/metrics”. Its response should contain various metrics data:

{ "version": "3.0.0", "gauges": {}, "counters": { "m01-counter": { "count": 1 } }, "histograms": { "m02-histogram": { "count": 3, "max": 100, "mean": 41.66666666666666, "min": 5, "p50": 20, "p75": 100, "p95": 100, "p98": 100, "p99": 100, "p999": 100, "stddev": 41.69998667732268 } }, "meters": {}, "timers": {} } 

5.6. AdminServlet Usage

AdminServlet aggregates HealthCheckServlet, ThreadDumpServlet, MetricsServlet, and PingServlet.

Let's add these into the web.xml:

 admin com.codahale.metrics.servlets.AdminServlet   admin /admin/* 

It can now be accessed at “//localhost:8080/admin”. We will get a page containing four links, one for each of those four servlets.

Note that, if we want to do health check and access metrics data, those two listeners are still needed.

6. Module metrics-servlet

The metrics-servlet module provides a Filter which has several metrics: meters for status codes, a counter for the number of active requests, and a timer for request duration.

6.1. Maven Dependencies

To use this module, let's first add the dependency into the pom.xml:

 io.dropwizard.metrics metrics-servlet 3.1.2 

And you can find its latest version here.

6.2. Usage

To use it, we need to create a ServletContextListener which exposes our MetricRegistry to the InstrumentedFilter:

public class MyInstrumentedFilterContextListener extends InstrumentedFilterContextListener { public static MetricRegistry REGISTRY = new MetricRegistry(); @Override protected MetricRegistry getMetricRegistry() { return REGISTRY; } } 

Then, we add these into the web.xml:

  com.baeldung.metrics.servlet.MyInstrumentedFilterContextListener    instrumentFilter  com.codahale.metrics.servlet.InstrumentedFilter    instrumentFilter /* 

Now the InstrumentedFilter can work. If we want to access its metrics data, we can do it through its MetricRegistryREGISTRY.

7. Other Modules

Except for the modules we introduced above, Metrics has some other modules for different purposes:

  • metrics-jvm: provides several useful metrics for instrumenting JVM internals
  • metrics-ehcache: provides InstrumentedEhcache, a decorator for Ehcache caches
  • metrics-httpclient: provides classes for instrumenting Apache HttpClient (4.x version)
  • metrics-log4j: provides InstrumentedAppender, a Log4j Appender implementation for log4j 1.x which records the rate of logged events by their logging level
  • metrics-log4j2: is similar to metrics-log4j, just for log4j 2.x
  • metrics-logback: provides InstrumentedAppender, a Logback Appender implementation which records the rate of logged events by their logging level
  • metrics-json : menyediakan HealthCheckModule dan MetricsModule untuk Jackson

Terlebih lagi, selain modul proyek utama ini, beberapa pustaka pihak ketiga lainnya menyediakan integrasi dengan pustaka dan kerangka kerja lain.

8. Kesimpulan

Menginstrumentasi aplikasi adalah persyaratan umum, jadi dalam artikel ini, kami memperkenalkan Metrik, dengan harapan dapat membantu Anda menyelesaikan masalah.

Seperti biasa, kode sumber lengkap untuk contoh tersedia di GitHub.