Introduzione alle metriche di Dropwizard

1. Introduzione

Metrics è una libreria Java che fornisce strumenti di misura per applicazioni Java.

Ha diversi moduli e in questo articolo elaboreremo il modulo metrics-core, il modulo metrics-healthchecks, il modulo metrics-servlet e il modulo metrics-servlet e abbozzeremo il resto, come riferimento.

2. Metriche-core del modulo

2.1. Dipendenze di Maven

Per utilizzare il modulo metrics-core , è richiesta solo una dipendenza che deve essere aggiunta al file pom.xml :

 io.dropwizard.metrics metrics-core 3.1.2  

E puoi trovare la sua ultima versione qui.

2.2. MetricRegistry

In poche parole, useremo la classe MetricRegistry per registrare una o più metriche.

Possiamo utilizzare un registro delle metriche per tutte le nostre metriche, ma se vogliamo utilizzare metodi di reporting diversi per metriche diverse, possiamo anche dividere le nostre metriche in gruppi e utilizzare registri di metriche diversi per ogni gruppo.

Creiamo ora un MetricRegistry :

MetricRegistry metricRegistry = new MetricRegistry();

E poi possiamo registrare alcune metriche con questo MetricRegistry :

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

Esistono due modi di base per creare una nuova metrica: istanziarne una o ottenerne una dal registro delle metriche. Come puoi vedere, li abbiamo usati entrambi nell'esempio sopra, stiamo istanziando l' oggetto Meter "meter1" e stiamo ottenendo un altro oggetto Meter "meter2" che è creato da metricRegistry .

In un registro di metriche, ogni metrica ha un nome univoco, poiché abbiamo utilizzato "meter1" e "meter2" come nomi di metrica sopra. MetricRegistry fornisce anche una serie di metodi di supporto statici per aiutarci a creare nomi di metriche appropriati:

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

Se è necessario gestire un set di registri di metriche, è possibile utilizzare la classe SharedMetricRegistries , che è singleton e thread-safe. Possiamo aggiungere un registro di metrica al suo interno, recuperare questo registro di metrica da esso e rimuoverlo:

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

3. Concetti di metrica

Il modulo metriche-core fornisce diversi tipi metriche comunemente utilizzati: tester , calibro , Contatore , Istogramma e Timer e Reporter ai valori di metrica di uscita .

3.1. Meter

Un multimetro misura il conteggio e la frequenza delle occorrenze degli eventi:

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(); 

Il metodo getCount () restituisce il conteggio delle occorrenze degli eventi e il metodo mark () aggiunge 1 o n al conteggio delle occorrenze degli eventi. L' oggetto Meter fornisce quattro frequenze che rappresentano le frequenze medie per l'intera durata del Meter , per l'ultimo minuto, per gli ultimi cinque minuti e per l'ultimo trimestre, rispettivamente.

3.2. Valutare

Gauge è un'interfaccia che viene semplicemente utilizzata per restituire un valore particolare. Il modulo metrics-core fornisce diverse implementazioni di esso: RatioGauge , CachedGauge , DerivativeGauge e JmxAttributeGauge .

RatioGauge è una classe astratta e misura il rapporto tra un valore e un altro.

Vediamo come usarlo. Innanzitutto, implementiamo una classe AttendanceRatioGauge :

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

E poi lo testiamo:

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

CachedGauge è un'altra classe astratta che può memorizzare nella cache il valore, quindi è abbastanza utile quando i valori sono costosi da calcolare. Per usarlo, dobbiamo implementare una classe 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 }
    

Quindi lo testiamo per vedere se funziona come previsto:

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

Abbiamo impostato il tempo di scadenza della cache a 15 minuti durante l'istanza di ActiveUsersGauge .

DerivativeGauge è anche una classe astratta e permette di ricavare un valore da altri Gauge come valore.

Diamo un'occhiata a un esempio:

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 : fornisce HealthCheckModule e MetricsModule per Jackson

Inoltre, oltre a questi moduli principali del progetto, alcune altre librerie di terze parti forniscono l'integrazione con altre librerie e framework.

8. Conclusione

La strumentazione delle applicazioni è un requisito comune, quindi in questo articolo abbiamo introdotto le metriche, sperando che possano aiutarti a risolvere il tuo problema.

Come sempre, il codice sorgente completo per l'esempio è disponibile su GitHub.