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SmallRye Metrics

The following guide demonstrates how a Quarkus application can use SmallRye Metrics, an implementation of the MicroProfile Metrics specification.

SmallRye Metrics allows applications to gather metrics and statistics that provide insights into what is happening inside an application. The metrics can be read remotely using the JSON or OpenMetrics format to be processed by additional tools such as Prometheus and stored for analysis and visualization.

Apart from application-specific metrics described in this guide, you may also use built-in metrics exposed by various Quarkus extensions. These are described in the guide for each particular extension that supports built-in metrics.

Micrometer is the recommended approach to metrics for Quarkus. Use the SmallRye Metrics extension when it is required to retain MicroProfile specification compatibility.

When Quarkus will upgrade to Eclipse MicroProfile 6, the SmallRye Metrics support will be discontinued.

Essa tecnologia é considerada deprecated.

Ser deprecated significa que essa extensão provavelmente será substituída ou removida em uma versão futura do Quarkus.

Para obter uma lista completa de possíveis status, consulte nosso FAQ.

Pré-requisitos

Para concluir este guia, você precisa:

  • Cerca de 15 minutos

  • Um IDE

  • JDK 17+ installed with JAVA_HOME configured appropriately

  • Apache Maven 3.9.9

  • Opcionalmente, o Quarkus CLI se você quiser usá-lo

  • Opcionalmente, Mandrel ou GraalVM instalado e configurado apropriadamente se você quiser criar um executável nativo (ou Docker se você usar uma compilação de contêiner nativo)

Arquitetura

In this example, we build a very simple microservice that offers one REST endpoint. This endpoint serves for determining whether a number is prime. The implementation class is annotated with certain metric annotations so that while responding to users' requests, certain metrics are gathered. The meaning of each metric is explained later.

Solução

We recommend that you follow the instructions in the next sections and create the application step by step. However, you can skip to the completed example.

  1. Clone the Git repository:

    git clone https://github.com/quarkusio/quarkus-quickstarts.git

Creating a Maven project

To create a new project:

CLI
quarkus create app org.acme:microprofile-metrics-quickstart \
    --extension='rest,smallrye-metrics' \
    --no-code
cd microprofile-metrics-quickstart

Para criar um projeto Gradle, adicione a opção --gradle ou --gradle-kotlin-dsl.

Para obter mais informações sobre como instalar e usar a CLI do Quarkus, consulte o guia Quarkus CLI.

Maven
mvn io.quarkus.platform:quarkus-maven-plugin:3.17.2:create \
    -DprojectGroupId=org.acme \
    -DprojectArtifactId=microprofile-metrics-quickstart \
    -Dextensions='rest,smallrye-metrics' \
    -DnoCode
cd microprofile-metrics-quickstart

Para criar um projeto Gradle, adicione a opção '-DbuildTool=gradle' ou '-DbuildTool=gradle-kotlin-dsl'.

Para usuários do Windows:

  • Se estiver usando cmd, (não use barra invertida '\' e coloque tudo na mesma linha)

  • Se estiver usando o Powershell, envolva os parâmetros '-D' entre aspas duplas, por exemplo, '"-DprojectArtifactId=microprofile-metrics-quickstart"'

This command generates a Quarkus project that uses the smallrye-metrics extension.

If you already have your Quarkus project configured, you can add the smallrye-metrics extension to your project by running the following command in your project base directory:

CLI
quarkus extension add smallrye-metrics
Maven
./mvnw quarkus:add-extension -Dextensions='smallrye-metrics'
Gradle
./gradlew addExtension --extensions='smallrye-metrics'

This adds the following to your build file:

pom.xml
<dependency>
    <groupId>io.quarkus</groupId>
    <artifactId>quarkus-smallrye-metrics</artifactId>
</dependency>
build.gradle
implementation("io.quarkus:quarkus-smallrye-metrics")

Writing an application

The following procedures create a Quarkus application that consists of a single class that implements an algorithm for checking whether a number is prime. This algorithm is exposed over a REST interface. Additionally, specific annotations are required to ensure that the desired metrics are calculated over time and can be exported for manual analysis or processing by additional tooling.

The application will gather the following metrics:

  • performedChecks: A counter that increases by one each time the user asks about a number.

  • highestPrimeNumberSoFar: A gauge that stores the highest number asked about by the user if the number was determined to be prime.

  • checksTimer: A compound metric that benchmarks how much time the primality tests take. Additional details are provided later.

The full source code looks as follows:

package org.acme.microprofile.metrics;

import org.eclipse.microprofile.metrics.MetricUnits;
import org.eclipse.microprofile.metrics.annotation.Counted;
import org.eclipse.microprofile.metrics.annotation.Gauge;
import org.eclipse.microprofile.metrics.annotation.Timed;

import jakarta.ws.rs.GET;
import jakarta.ws.rs.Path;
import jakarta.ws.rs.Produces;
import jakarta.ws.rs.core.MediaType;

@Path("/")
public class PrimeNumberChecker {

    private long highestPrimeNumberSoFar = 2;

    @GET
    @Path("/{number}")
    @Produces(MediaType.TEXT_PLAIN)
    @Counted(name = "performedChecks", description = "How many primality checks have been performed.")
    @Timed(name = "checksTimer", description = "A measure of how long it takes to perform the primality test.", unit = MetricUnits.MILLISECONDS)
    public String checkIfPrime(long number) {
        if (number < 1) {
            return "Only natural numbers can be prime numbers.";
        }
        if (number == 1) {
            return "1 is not prime.";
        }
        if (number == 2) {
            return "2 is prime.";
        }
        if (number % 2 == 0) {
            return number + " is not prime, it is divisible by 2.";
        }
        for (int i = 3; i < Math.floor(Math.sqrt(number)) + 1; i = i + 2) {
            if (number % i == 0) {
                return number + " is not prime, is divisible by " + i + ".";
            }
        }
        if (number > highestPrimeNumberSoFar) {
            highestPrimeNumberSoFar = number;
        }
        return number + " is prime.";
    }

    @Gauge(name = "highestPrimeNumberSoFar", unit = MetricUnits.NONE, description = "Highest prime number so far.")
    public Long highestPrimeNumberSoFar() {
        return highestPrimeNumberSoFar;
    }

}

Running and using the application

To execute the application created in Writing an application, do the following:

  1. Run the microservice in dev mode:

    CLI
    quarkus dev
    Maven
    ./mvnw quarkus:dev
    Gradle
    ./gradlew --console=plain quarkusDev
  2. Generate values for the metrics.

    1. Query the endpoint to determine whether some numbers are prime numbers:

      curl localhost:8080/350

      The application will respond that 350 is not a prime number because it can be divided by 2.

      • For large prime numbers, the test takes more time.

        curl localhost:8080/629521085409773

        The application will respond that 629521085409773 is a prime number.

    2. Perform additional calls with numbers of your choice.

  3. Review the generated metrics:

    curl -H"Accept: application/json" localhost:8080/q/metrics/application

    You will receive a response such as:

    {
      "org.acme.microprofile.metrics.PrimeNumberChecker.checksTimer" : {			                    (1)
        "p50": 217.231273,										                                        (2)
        "p75": 217.231273,
        "p95": 217.231273,
        "p98": 217.231273,
        "p99": 217.231273,
        "p999": 217.231273,
        "min": 0.58961,										                                            (3)
        "mean": 112.15909190834819,								                                        (4)
        "max": 217.231273,									                                            (5)
        "stddev": 108.2721053982776,							    	                                (6)
        "count": 2,											                                            (7)
        "meanRate": 0.04943519091742238,							                                    (8)
        "oneMinRate": 0.2232140583080189,
        "fiveMinRate": 0.3559527083952095,
        "fifteenMinRate": 0.38474303050928976
      },
      "org.acme.microprofile.metrics.PrimeNumberChecker.performedChecks" : 2,		                    (9)
      "org.acme.microprofile.metrics.PrimeNumberChecker.highestPrimeNumberSoFar" : 629521085409773		(10)
    }
1 checksTimer: A compound metric that benchmarks how much time the primality tests take. All durations are measured in milliseconds. It consists of these values below.
2 p50, p75, p95, p99, p999: Percentiles of the durations. For example, the value in p95 means that 95 % of the measurements were faster than this duration.
3 min: The shortest duration it took to perform a primality test was probably performed for a small number.
4 mean: The mean value of the measured durations.
5 max: The longest duration, probably it was with a large prime number.
6 stddev: The standard deviation.
7 count: The number of observations, the value of which is the same as performedChecks.
8 meanRate, oneMinRate, fiveMinRate, fifteenMinRate: Mean throughput and one-, five-, and fifteen-minute exponentially-weighted moving average throughput.
9 performedChecks: A counter which is increased by one each time the user asks about a number.
10 highestPrimeNumberSoFar: A gauge that stores the highest number that was asked about by the user and which was determined to be prime.
If you prefer an OpenMetrics export rather than the JSON format, remove the -H"Accept: application/json" argument from your command line.
Management interface

By default, the metrics are exposed on the main HTTP server. You can expose them on a separate network interface and port by enabling the management interface with the quarkus.management.enabled=true property. Refer to the management interface reference for more information.

Propriedade de Configuração Fixa no Momento da Compilação - Todas as outras propriedades de configuração podem ser sobrepostas em tempo de execução.

Configuration property

Tipo

Padrão

The path to the metrics handler. By default, this value will be resolved as a path relative to ${quarkus.http.non-application-root-path}. If the management interface is enabled, the value will be resolved as a path relative to ${quarkus.management.root-path}.

Environment variable: QUARKUS_SMALLRYE_METRICS_PATH

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string

metrics

Whether metrics published by Quarkus extensions should be enabled.

Environment variable: QUARKUS_SMALLRYE_METRICS_EXTENSIONS_ENABLED

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boolean

true

Apply Micrometer compatibility mode, where instead of regular 'base' and 'vendor' metrics, Quarkus exposes the same 'jvm' metrics that Micrometer does. Application metrics are unaffected by this mode. The use case is to facilitate migration from Micrometer-based metrics, because original dashboards for JVM metrics will continue working without having to rewrite them.

Environment variable: QUARKUS_SMALLRYE_METRICS_MICROMETER_COMPATIBILITY

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boolean

false

Whether detailed JAX-RS metrics should be enabled.

Environment variable: QUARKUS_SMALLRYE_METRICS_JAXRS_ENABLED

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boolean

false

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