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micrometer: Micrometer QuickStart

The micrometer quickstart demonstrates the use of the Micrometer library in WildFly.

What is it?

Micrometer is a vendor-neutral facade that allows application developers to collect and report application and system metrics to the backend of their choice in an entirely portable manner. By simply replacing the MeterRegistry used, or combining them in Micrometer’s CompositeRegistry data can be exported a variety of monitoring systems with no application code changes.

Architecture

In this quickstart, we will build a small, simple application that shows the usage of a number of Micrometer’s Meter implementations. We will also demonstrate the means by which WildFly exports the metrics data, which is via the OpenTelemetry Protocol (OTLP) to the OpenTelemetry Collector. To provide simpler access to the published metrics, the Collector will be configured with a Prometheus endpoint, from which we can scrape data.

Prerequisites

To complete this guide, you will need:

  • less than 15 minutes

  • JDK 11+ installed with JAVA_HOME configured appropriately

  • Apache Maven 3.5.3+

  • Docker Compose, or alternatively Podman Compose

Use of the WILDFLY_HOME and QUICKSTART_HOME Variables

In the following instructions, replace WILDFLY_HOME with the actual path to your WildFly installation. The installation path is described in detail here: Use of WILDFLY_HOME and JBOSS_HOME Variables.

When you see the replaceable variable QUICKSTART_HOME, replace it with the path to the root directory of all of the quickstarts.

Steps

Start the WildFly Standalone Server

  1. Open a terminal and navigate to the root of the WildFly directory.

  2. Start the WildFly server with the default profile by typing the following command.

    $ WILDFLY_HOME/bin/standalone.sh
    Note
    		 For Windows, use the WILDFLY_HOME\bin\standalone.bat script.

Configure the Server

You enable Micrometer by running JBoss CLI commands. For your convenience, this quickstart batches the commands into a configure-micrometer.cli script provided in the root directory of this quickstart.

  1. Before you begin, make sure you do the following:

  2. Review the configure-micrometer.cli file in the root of this quickstart directory. This script adds the configuration that enables Micrometer for the quickstart components. Comments in the script describe the purpose of each block of commands.

  3. Open a new terminal, navigate to the root directory of this quickstart, and run the following command, replacing WILDFLY_HOME with the path to your server:

    $ WILDFLY_HOME/bin/jboss-cli.sh --connect --file=configure-micrometer.cli
    Note
    		 For Windows, use the WILDFLY_HOME\bin\jboss-cli.bat script.

    You should see the following result when you run the script:

    The batch executed successfully
process-state: reload-required

  4. You’ll need to reload the configuration after that:

    $ WILDFLY_HOME/bin/jboss-cli.sh --connect --commands=reload

Starting the OpenTelemetry Collector

By default, WildFly will publish metrics every 10 seconds, so you will soon start seeing errors about a refused connection.

This is because we told WildFly to publish to a server that is not there, so we need to fix that. To make that as simple as possible, you can use Docker Compose to start an instance of the OpenTelemetry Collector.

The Docker Compose configuration file is docker-compose.yaml:

version: "3"

services:
  otel-collector:
    image: otel/opentelemetry-collector
    command: [--config=/etc/otel-collector-config.yaml]
    volumes:
      - ./otel-collector-config.yaml:/etc/otel-collector-config.yaml:Z
    ports:
      - 1888:1888 # pprof extension
      - 8888:8888 # Prometheus metrics exposed by the collector
      - 8889:8889 # Prometheus exporter metrics
      - 13133:13133 # health_check extension
      - 4317:4317 # OTLP gRPC receiver
      - 4318:4318 # OTLP http receiver
      - 55679:55679 # zpages extension
      - 1234:1234 # /metrics endpoint

The Collector server configuration file is otel-collector-config.yaml:

extensions:
  health_check:
  pprof:
    endpoint: 0.0.0.0:1777
  zpages:
    endpoint: 0.0.0.0:55679

receivers:
  otlp:
    protocols:
      grpc:
      http:

processors:
  batch:

exporters:
  prometheus:
    endpoint: "0.0.0.0:1234"

service:
  pipelines:
    metrics:
      receivers: [otlp]
      processors: [batch]
      exporters: [prometheus]

  extensions: [health_check, pprof, zpages]

We can now bring up the collector server instance:

$ docker-compose up

The service should be available almost immediately, which you can verify by looking at the Prometheus endpoint we’ve configured by pointing your browser at http://localhost:1234/metrics. You should see quite a few metrics listed, none of which are what our application has registered. What you’re seeing are the system and JVM metrics automatically registered and published by WildFly to give systems/applications administrators a comprehensive view of system health and performance.

Note

You may use Podman as alternative to Docker if you prefer, in such case the command should be podman-compose up.
Note

If your environment does not support Docker or Podman, please refer to Otel Collector documentation for alternatives on how to install and run the OpenTelemetry Collector.

Registering metrics

Micrometer uses a programmatic approach to metrics definition, as opposed the more declarative, annotation-based approach of other libraries. Because of that, we need to explicitly register our Meter s before they can be used:

@Path("/")
@ApplicationScoped
public class RootResource {
    // ...
    @Inject
    private MeterRegistry registry;

    private Counter performCheckCounter;
    private Counter originalCounter;
    private Counter duplicatedCounter;

    @PostConstruct
    private void createMeters() {
        Gauge.builder("prime.highestSoFar", () -> highestPrimeNumberSoFar)
                .description("Highest prime number so far.")
                .register(registry);
        performCheckCounter = Counter
                .builder("prime.performedChecks")
                .description("How many prime checks have been performed.")
                .register(registry);
        originalCounter = Counter
                .builder("prime.duplicatedCounter")
                .tags(List.of(Tag.of("type", "original")))
                .register(registry);
        duplicatedCounter = Counter
                .builder("prime.duplicatedCounter")
                .tags(List.of(Tag.of("type", "copy")))
                .register(registry);
    }
    // ...
}

Notice that we start by @Inject ing the MeterRegistry. This is a WildFly-managed instance, so all applications need to do it inject it and start using. Once we have that, we can use to build and register our meters, which we do in @PostConstuct private void createMeters()

Note

This must be done post-construction, as the MeterRegistry must be injected before it can be used to register the meters.

In this example, we register several different types to demonstrate their use. With those registered, we can start writing application logic:

@GET
@Path("/prime/{number}")
public String checkIfPrime(@PathParam("number") long number) throws Exception {
    performCheckCounter.increment();

    Timer timer = registry.timer("prime.timer");

    return timer.recordCallable(() -> {

        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) {
            try {
                Thread.sleep(10);
            } catch (InterruptedException e) {
                //
            }
            if (number % i == 0) {
                return number + " is not prime, is divisible by " + i + ".";
            }
        }

        if (number > highestPrimeNumberSoFar) {
            highestPrimeNumberSoFar = number;
        }

        return number + " is prime.";
    });
}

This method represents a simple REST endpoint that is able to determine whether the number passed as a path parameter is a prime number.

Build and Deploy the Quickstart

  1. Make sure you start the WildFly server as described above.

  2. Open a terminal and navigate to the root directory of this quickstart.

  3. Type the following command to build the quickstart.

    $ mvn clean package

  4. Type the following command to deploy the quickstart.

    $ mvn wildfly:deploy

This deploys the micrometer/target/micrometer.war to the running instance of the server.

You should see a message in the server log indicating that the archive deployed successfully.

Access the quickstart application

You can either access the application via your browser at http://localhost:8080/micrometer/prime/13, or from the command line:

$ curl http://localhost:8080/micrometer/prime/13

It should return a simple document:

13 is prime.

Once given enough time to allow WildFly to publish metrics updates, you now see your application’s meters reported in the Prometheus export. You can also view them via the command-line:

$ curl -s http://localhost:1234/metrics | grep "prime_"
# HELP prime_duplicatedCounter
# TYPE prime_duplicatedCounter counter
prime_duplicatedCounter{job="wildfly",type="copy"} 0
prime_duplicatedCounter{job="wildfly",type="original"} 0
# HELP prime_highestSoFar Highest prime number so far.
# TYPE prime_highestSoFar gauge
prime_highestSoFar{job="wildfly"} 13
# HELP prime_performedChecks How many prime checks have been performed.
# TYPE prime_performedChecks counter
prime_performedChecks{job="wildfly"} 1
# HELP prime_timer
# TYPE prime_timer histogram
prime_timer_bucket{job="wildfly",le="+Inf"} 1
prime_timer_sum{job="wildfly"} 10.941035
prime_timer_count{job="wildfly"} 1

Notice that all four meters registered in the @PostConstruct method as well as the Timer in our endpoint method have all been published.

Run the Integration Tests

This quickstart includes integration tests, which are located under the src/test/ directory. The integration tests verify that the quickstart runs correctly when deployed on the server.

Follow these steps to run the integration tests.

  1. Make sure you start the WildFly server, as previously described.

  2. Make sure you build and deploy the quickstart, as previously described.

  3. Type the following command to run the verify goal with the integration-testing profile activated.

    $ mvn verify -Pintegration-testing
Note

You may also use the environment variable SERVER_HOST or the system property server.host to define the target URL of the tests.

Undeploy the Quickstart

When you are finished testing the quickstart, follow these steps to undeploy the archive.

  1. Make sure you start the WildFly server as described above.

  2. Open a terminal and navigate to the root directory of this quickstart.

  3. Type this command to undeploy the archive:

    $ mvn wildfly:undeploy

Restore the WildFly Standalone Server Configuration

You can restore the original server configuration using either of the following methods.

Restore the WildFly Standalone Server Configuration by Running the JBoss CLI Script

  1. Start the WildFly server as described above.

  2. Open a new terminal, navigate to the root directory of this quickstart, and run the following command, replacing WILDFLY_HOME with the path to your server:

    $ WILDFLY_HOME/bin/jboss-cli.sh --connect --file=restore-configuration.cli
    Note
    		 For Windows, use the WILDFLY_HOME\bin\jboss-cli.bat script.

Restore the WildFly Standalone Server Configuration Manually

When you have completed testing the quickstart, you can restore the original server configuration by manually restoring the backup copy the configuration file.

  1. If it is running, stop the WildFly server.

  2. Replace the WILDFLY_HOME/standalone/configuration/standalone.xml file with the backup copy of the file.

Building and running the quickstart application with provisioned WildFly server

Instead of using a standard WildFly server distribution, you can alternatively provision a WildFly server to deploy and run the quickstart, by activating the Maven profile named provisioned-server when building the quickstart:

$ mvn clean package -Pprovisioned-server

The provisioned WildFly server, with the quickstart deployed, can then be found in the target/server directory, and its usage is similar to a standard server distribution, with the simplification that there is never the need to specify the server configuration to be started.

The server provisioning functionality is provided by the WildFly Maven Plugin, and you may find its configuration in the quickstart pom.xml:

        <profile>
            <id>provisioned-server</id>
            <build>
                <plugins>
                    <plugin>
                        <groupId>org.wildfly.plugins</groupId>
                        <artifactId>wildfly-maven-plugin</artifactId>
                        <configuration>
                            <feature-packs>
                                <feature-pack>
                                    <location>org.wildfly:wildfly-galleon-pack:${version.server}</location>
                                </feature-pack>
                            </feature-packs>
                            <layers>...</layers>
                            <!-- deploys the quickstart on root web context -->
                            <name>ROOT.war</name>
                        </configuration>
                        <executions>
                            <execution>
                                <goals>
                                    <goal>package</goal>
                                </goals>
                            </execution>
                        </executions>
                    </plugin>
                    ...
                </plugins>
            </build>
        </profile>
Note

Since the plugin configuration above deploys quickstart on root web context of the provisioned server, the URL to access the application should not have the /micrometer path segment after HOST:PORT.

Run the Integration Tests with a provisioned server

The integration tests included with this quickstart, which verify that the quickstart runs correctly, may also be run with a provisioned server.

Follow these steps to run the integration tests.

  1. Make sure the server is provisioned.

    $ mvn clean package -Pprovisioned-server

  2. Start the WildFly provisioned server, this time using the WildFly Maven Plugin, which is recommended for testing due to simpler automation. The path to the provisioned server should be specified using the jbossHome system property.

    $ mvn wildfly:start -DjbossHome=target/server

  3. Type the following command to run the verify goal with the integration-testing profile activated, and specifying the quickstart’s URL using the server.host system property, which for a provisioned server by default is http://localhost:8080.

    $ mvn verify -Pintegration-testing -Dserver.host=http://localhost:8080

  4. Shutdown the WildFly provisioned server, this time using the WildFly Maven Plugin too.

    $ mvn wildfly:shutdown

Building and running the quickstart application in a bootable JAR

You can use the WildFly JAR Maven plug-in to build a WildFly bootable JAR to run this quickstart.

The quickstart pom.xml file contains a Maven profile named bootable-jar which configures the bootable JAR building:

      <profile>
          <id>bootable-jar</id>
          <build>
              <plugins>
                  <plugin>
                      <groupId>org.wildfly.plugins</groupId>
                      <artifactId>wildfly-jar-maven-plugin</artifactId>
                      <configuration>
                          <feature-pack-location>wildfly@maven(org.jboss.universe:community-universe)#${version.server}</feature-pack-location>
                          <layers>
                              <layer>jaxrs-server</layer>
                              <layer>microprofile-config</layer>
                          </layers>
                          <plugin-options>
                              <jboss-fork-embedded>true</jboss-fork-embedded>
                          </plugin-options>
                      </configuration>
                      <executions>
                          <execution>
                              <goals>
                                  <goal>package</goal>
                              </goals>
                          </execution>
                      </executions>
                  </plugin>
              </plugins>
          </build>
      </profile>
Procedure

  1. Build the quickstart bootable JAR with the following command:

    $ mvn clean package -Pbootable-jar

  2. Run the quickstart application contained in the bootable JAR:

    $ java -jar target/micrometer-bootable.jar

  3. You can now interact with the quickstart application.

Note

After the quickstart application is deployed, the bootable JAR includes the application in the root context. Therefore, any URLs related to the application should not have the /micrometer path segment after HOST:PORT.

Run the Integration Tests with a bootable jar

The integration tests included with this quickstart, which verify that the quickstart runs correctly, may also be run with a bootable jar.

Follow these steps to run the integration tests.

  1. Make sure the bootable jar is provisioned.

    $ mvn clean package -Pbootable-jar

  2. Start the WildFly bootable jar, this time using the WildFly Maven Jar Plugin, which is recommend for testing due to simpler automation.

    $ mvn wildfly-jar:start -Djar-file-name=target/micrometer-bootable.jar

  3. Type the following command to run the verify goal with the integration-testing profile activated, and specifying the quickstart’s URL using the server.host system property, which for a bootable jar by default is http://localhost:8080.

    $ mvn verify -Pintegration-testing -Dserver.host=http://localhost:8080

  4. Shutdown the WildFly bootable jar, this time using the WildFly Maven Jar Plugin too.

    $ mvn wildfly-jar:shutdown

Building and running the quickstart application with OpenShift

Build the WildFly Source-to-Image (S2I) Quickstart to OpenShift with Helm Charts

On OpenShift, the S2I build with Apache Maven uses an openshift Maven profile to provision a WildFly server, deploy and run the quickstart in OpenShift environment.

The server provisioning functionality is provided by the WildFly Maven Plugin, and you may find its configuration in the quickstart pom.xml:

        <profile>
            <id>openshift</id>
            <build>
                <plugins>
                    <plugin>
                        <groupId>org.wildfly.plugins</groupId>
                        <artifactId>wildfly-maven-plugin</artifactId>
                        <configuration>
                            <feature-packs>
                                <feature-pack>
                                    <location>org.wildfly:wildfly-galleon-pack:${version.server}</location>
                                </feature-pack>
                                <feature-pack>
                                    <location>org.wildfly.cloud:wildfly-cloud-galleon-pack:${version.pack.cloud}</location>
                                </feature-pack>
                            </feature-packs>
                            <layers>...</layers>
                            <name>ROOT.war</name>
                        </configuration>
                        <executions>
                            <execution>
                                <goals>
                                    <goal>package</goal>
                                </goals>
                            </execution>
                        </executions>
                    </plugin>
                    ...
                </plugins>
            </build>
        </profile>

You may note that unlike the provisioned-server profile it uses the cloud feature pack which enables a configuration tuned for OpenShift environment.

Getting Started with WildFly for OpenShift and Helm Charts

This section contains the basic instructions to build and deploy this quickstart to WildFly for OpenShift or WildFly for OpenShift Online using Helm Charts.

Prerequisites

  • You must be logged in OpenShift and have an oc client to connect to OpenShift

  • Helm must be installed to deploy the backend on OpenShift.

Once you have installed Helm, you need to add the repository that provides Helm Charts for WildFly.

$ helm repo add wildfly https://docs.wildfly.org/wildfly-charts/
"wildfly" has been added to your repositories
$ helm search repo wildfly
NAME                    CHART VERSION   APP VERSION     DESCRIPTION
wildfly/wildfly         ...             ...            Build and Deploy WildFly applications on OpenShift
wildfly/wildfly-common  ...             ...            A library chart for WildFly-based applications
Install OpenTelemetry Collector on OpenShift

The functionality of this quickstart depends on a running instance of the OpenTelemetry Collector.

To deploy and configure the OpenTelemetry Collector, you will need to apply a set of configurations to your OpenShift cluster:

---
apiVersion: v1
kind: ConfigMap
metadata:
  name: collector-config
data:
  collector.yml: |
    receivers:
      otlp:
        protocols:
          grpc:
          http:
    processors:
    exporters:
      logging:
        verbosity: detailed
      prometheus:
        endpoint: "0.0.0.0:1234"
    service:
      pipelines:
        metrics:
          receivers: [otlp]
          processors: []
          exporters: [logging,prometheus]
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: opentelemetrycollector
spec:
  replicas: 1
  selector:
    matchLabels:
      app.kubernetes.io/name: opentelemetrycollector
  template:
    metadata:
      labels:
        app.kubernetes.io/name: opentelemetrycollector
    spec:
      containers:
        - name: otelcol
          args:
            - --config=/conf/collector.yml
          image: otel/opentelemetry-collector:0.89.0
          volumeMounts:
            - mountPath: /conf
              name: collector-config
      volumes:
        - configMap:
            items:
              - key: collector.yml
                path: collector.yml
            name: collector-config
          name: collector-config
---
apiVersion: v1
kind: Service
metadata:
  name: opentelemetrycollector
spec:
  ports:
    - name: otlp-grpc
      port: 4317
      protocol: TCP
      targetPort: 4317
    - name: otlp-http
      port: 4318
      protocol: TCP
      targetPort: 4318
    - name: prometheus
      port: 1234
      protocol: TCP
      targetPort: 1234
  selector:
    app.kubernetes.io/name: opentelemetrycollector
  type: ClusterIP
---
apiVersion: route.openshift.io/v1
kind: Route
metadata:
  name: otelcol-otlp-grpc
  labels:
    app.kubernetes.io/name: microprofile
spec:
  port:
    targetPort: otlp-grpc
  to:
    kind: Service
    name: opentelemetrycollector
  tls:
    termination: edge
    insecureEdgeTerminationPolicy: Redirect
  wildcardPolicy: None
---
apiVersion: route.openshift.io/v1
kind: Route
metadata:
  name: otelcol-otlp-http
  labels:
    app.kubernetes.io/name: microprofile
spec:
  port:
    targetPort: otlp-http
  to:
    kind: Service
    name: opentelemetrycollector
  tls:
    termination: edge
    insecureEdgeTerminationPolicy: Redirect
  wildcardPolicy: None
---
apiVersion: route.openshift.io/v1
kind: Route
metadata:
  name: otelcol-prometheus
  labels:
    app.kubernetes.io/name: microprofile
spec:
  port:
    targetPort: prometheus
  to:
    kind: Service
    name: opentelemetrycollector
  tls:
    termination: edge
    insecureEdgeTerminationPolicy: Redirect
  wildcardPolicy: None

To make things simpler, you can find these commands in charts/opentelemetry-collector.yaml, and to apply them run the following command in your terminal:

$ oc apply -f charts/opentelemetry-collector.yaml
Note

When done with the quickstart, the oc delete -f charts/opentelemetry-collector.yaml command may be used to revert the applied changes.

Deploy the WildFly Source-to-Image (S2I) Quickstart to OpenShift with Helm Charts

Log in to your OpenShift instance using the oc login command. The backend will be built and deployed on OpenShift with a Helm Chart for WildFly.

Navigate to the root directory of this quickstart and run the following command:

$ helm install micrometer -f charts/helm.yaml wildfly/wildfly --wait --timeout=10m0s
NAME: micrometer
...
STATUS: deployed
REVISION: 1

This command will return once the application has successfully deployed. In case of a timeout, you can check the status of the application with the following command in another terminal:

oc get deployment micrometer

The Helm Chart for this quickstart contains all the information to build an image from the source code using S2I on Java 17:

build:
  uri: https://github.com/wildfly/quickstart.git
  ref: main
  contextDir: micrometer
deploy:
  replicas: 1
  env:
    - name: OTEL_COLLECTOR_HOST
      value: "opentelemetrycollector"

This will create a new deployment on OpenShift and deploy the application.

If you want to see all the configuration elements to customize your deployment you can use the following command:

$ helm show readme wildfly/wildfly

Get the URL of the route to the deployment.

$ oc get route micrometer -o jsonpath="{.spec.host}"

Access the application in your web browser using the displayed URL.

Note

The Maven profile named openshift is used by the Helm chart to provision the server with the quickstart deployed on the root web context, and thus the application should be accessed with the URL without the /micrometer path segment after HOST:PORT.

Run the Integration Tests with OpenShift

The integration tests included with this quickstart, which verify that the quickstart runs correctly, may also be run with the quickstart running on OpenShift.

Note

The integration tests expect a deployed application, so make sure you have deployed the quickstart on OpenShift before you begin.

Run the integration tests using the following command to run the verify goal with the integration-testing profile activated and the proper URL:

$ mvn verify -Pintegration-testing -Dserver.host=https://$(oc get route micrometer --template='{{ .spec.host }}')
Note

The tests are using SSL to connect to the quickstart running on OpenShift. So you need the certificates to be trusted by the machine the tests are run from.

Undeploy the WildFly Source-to-Image (S2I) Quickstart from OpenShift with Helm Charts

$ helm uninstall micrometer

Conclusion

Micrometer provides a de facto standard way of capturing and publishing metrics to the monitoring solution of your choice. WildFly provides a convenient, out-of-the-box integration of Micrometer to make it easier to capture those metrics and monitor your application’s health and performance. For more information on Micrometer, please refer to the project’s website.