The opentelemetry-tracing quickstart demonstrates the use of the OpenTelemetry tracing specification in WildFly.
OpenTelemetry is a set of APIs, SDKs, tooling and integrations that are designed for the creation and management of
telemetry data such as traces, metrics, and logs. OpenTelemetry support in WildFly is limited to traces only.
WildFly’s support of OpenTelemetry provides out of the box tracing of Jakarta REST calls, as well as
container-managed Jakarta REST Client invocations. Additionally, applications can have injected a Tracer instance
in order to create and manage custom `Span`s as a given application may require. These traces are exported
to an OpenTelemetry Collector instance listening on the same host.
In this quickstart, we have a collection of CDI beans and REST endpoints that expose functionalities of the OpenTelemetry support in WildFly.
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.
To complete this guide, you will need:
-
less than 15 minutes
-
JDK 11+ installed with
JAVA_HOMEconfigured appropriately -
Apache Maven 3.5.3+
-
Docker Compose, or alternatively Podman Compose
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.
-
Open a terminal and navigate to the root of the WildFly directory.
-
Start the WildFly server with the default profile by typing the following command.
$ WILDFLY_HOME/bin/standalone.shNoteFor Windows, use the WILDFLY_HOME\bin\standalone.batscript.
You enable OpenTelemetry by running JBoss CLI commands. For your convenience, this quickstart batches the commands into a configure-opentelemtry.cli script provided in the root directory of this quickstart.
-
Before you begin, make sure you do the following:
-
Back up the WildFly standalone server configuration as described above.
-
Start the WildFly server with the standalone default profile as described above.
-
-
Review the
configure-opentelemtry.clifile in the root of this quickstart directory. This script adds the configuration that enables OpenTelemetry for the quickstart components. Comments in the script describe the purpose of each block of commands. -
Open a new terminal, navigate to the root directory of this quickstart, and run the following command, replacing
WILDFLY_HOMEwith the path to your server:$ WILDFLY_HOME/bin/jboss-cli.sh --connect --file=configure-opentelemetry.cliNoteFor Windows, use the WILDFLY_HOME\bin\jboss-cli.batscript.You should see the following result when you run the script:
The batch executed successfully process-state: reload-required -
You’ll need to reload the configuration after that:
$ WILDFLY_HOME/bin/jboss-cli.sh --connect --commands=reload
By default, WildFly will publish traces 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"
volumes:
shared-volume:
# - logs:/var/log
services:
otel-collector:
image: otel/opentelemetry-collector:0.89.0
command: [--config=/etc/otel-collector-config.yaml]
volumes:
- ./otel-collector-config.yaml:/etc/otel-collector-config.yaml:Z
ports:
- 1888:1888 # pprof extension
- 13133:13133 # health_check extension
- 4317:4317 # OTLP gRPC receiver
- 4318:4318 # OTLP http receiver
- 55679:55679 # zpages extensionThe 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:
logging:
verbosity: detailed
service:
pipelines:
traces:
receivers: [otlp]
processors: []
exporters: [logging]
extensions: [health_check, pprof, zpages]We can now bring up the collector instance:
$ docker-compose upThe service should be available almost immediately, which you can verify by looking for the log entry Everything is ready. Begin running and processing data..
|
Note
|
You may use Podman as alternative to Docker if you prefer, in such case the command should be |
|
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. Please ensure the same OpenTelemetry version as the one in the docker-compose.yaml above is used, otherwise such configuration may fail to work. |
|
Note
|
Part of the value of OpenTelemetry is its vendor-agnostic approach to exporting its various supported signals. As such, this demo will only log the incoming traces, leaving the relaying of those signals to a downstream aggregation platform as an exercise for the reader. |
Now we can start adding our custom spans from our application.
The OpenTelemetry support in WildFly provides an implicit tracing of all Jakarta REST resources. That means that for all applications, WildFly will automatically:
-
extract the Span context from the incoming Jakarta REST request
-
start a new Span on incoming Jakarta REST request and close it when the request is completed
-
inject Span context to any outgoing Jakarta REST request
-
start a Span for any outgoing Jakarta REST request and finish the Span when the request is completed
The OpenTelemetry API also supports explicit tracing should your application required it:
package org.wildfly.quickstarts.opentelemetry;
import jakarta.enterprise.context.RequestScoped;
import jakarta.inject.Inject;
import io.opentelemetry.api.trace.Span;
import io.opentelemetry.api.trace.Tracer;
@RequestScoped
public class ExplicitlyTracedBean {
@Inject
private Tracer tracer;
public String getHello() {
Span prepareHelloSpan = tracer.spanBuilder("prepare-hello").startSpan();
prepareHelloSpan.makeCurrent();
String hello = "hello";
Span processHelloSpan = tracer.spanBuilder("process-hello").startSpan();
processHelloSpan.makeCurrent();
hello = hello.toUpperCase();
processHelloSpan.end();
prepareHelloSpan.end();
return hello;
}
}-
Make sure WildFly server is started.
-
Open a terminal and navigate to the root directory of this quickstart.
-
Type the following command to build the quickstart.
$ mvn clean package -
Type the following command to deploy the quickstart.
$ mvn wildfly:deploy
This deploys the opentelemetry-tracing/target/opentelemetry-tracing.war to the running instance of the server.
You should see a message in the server log indicating that the archive deployed successfully.
You can either access the application via your browser at http://localhost:8080/opentelemetry-tracing/implicit-trace, or http://localhost:8080/opentelemetry-tracing/explicit-trace. You can also access it from the command line:
$ curl http://localhost:8080/opentelemetry-tracing/implicit-trace
$ curl http://localhost:8080/opentelemetry-tracing/explicit-traceEither endpoint should return a simple document:
helloYou can view the traces by looking at the Collector’s log. You should see something like this:
otel-collector_1 | 2023-12-13T21:05:28.002Z info TracesExporter {"kind": "exporter", "data_type": "traces", "name": "logging", "resource spans": 1, "spans": 1}
otel-collector_1 | 2023-12-13T21:05:28.002Z info ResourceSpans #0
otel-collector_1 | Resource SchemaURL: https://opentelemetry.io/schemas/1.20.0
otel-collector_1 | Resource attributes:
otel-collector_1 | -> service.name: Str(opentelemetry-tracing.war)
otel-collector_1 | -> telemetry.sdk.language: Str(java)
otel-collector_1 | -> telemetry.sdk.name: Str(opentelemetry)
otel-collector_1 | -> telemetry.sdk.version: Str(1.29.0)
otel-collector_1 | ScopeSpans #0
otel-collector_1 | ScopeSpans SchemaURL:
otel-collector_1 | InstrumentationScope io.smallrye.opentelemetry 2.6.0
otel-collector_1 | Span #0
otel-collector_1 | Trace ID : c761e8fadec36d222adac36dcff1f4b1
otel-collector_1 | Parent ID :
otel-collector_1 | ID : 08f93dd25f75b5cd
otel-collector_1 | Name : GET /opentelemetry-tracing/implicit-trace
otel-collector_1 | Kind : Server
otel-collector_1 | Start time : 2023-12-13 21:05:20.560054393 +0000 UTC
otel-collector_1 | End time : 2023-12-13 21:05:20.621635685 +0000 UTC
otel-collector_1 | Status code : Unset
otel-collector_1 | Status message :
otel-collector_1 | Attributes:
otel-collector_1 | -> net.host.port: Int(8080)
otel-collector_1 | -> http.scheme: Str(http)
otel-collector_1 | -> http.method: Str(GET)
otel-collector_1 | -> http.status_code: Int(200)
otel-collector_1 | -> net.transport: Str(ip_tcp)
otel-collector_1 | -> user_agent.original: Str(curl/8.2.1)
otel-collector_1 | -> net.host.name: Str(localhost)
otel-collector_1 | -> http.route: Str(/opentelemetry-tracing/implicit-trace)
otel-collector_1 | -> http.target: Str(/opentelemetry-tracing/implicit-trace)
otel-collector_1 | -> net.sock.host.addr: Str(127.0.0.1)
otel-collector_1 | {"kind": "exporter", "data_type": "traces", "name": "logging"}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.
-
Make sure WildFly server is started.
-
Make sure the quickstart is deployed.
-
Type the following command to run the
verifygoal with theintegration-testingprofile activated.$ mvn verify -Pintegration-testing
When you are finished testing the quickstart, follow these steps to undeploy the archive.
-
Make sure WildFly server is started.
-
Open a terminal and navigate to the root directory of this quickstart.
-
Type this command to undeploy the archive:
$ mvn wildfly:undeploy
You can restore the original server configuration using either of the following methods.
-
You can run the
restore-configuration.cliscript provided in the root directory of this quickstart. -
You can manually restore the configuration using the backup copy of the configuration file.
-
Start the WildFly server as described above.
-
Open a new terminal, navigate to the root directory of this quickstart, and run the following command, replacing
WILDFLY_HOMEwith the path to your server:$ WILDFLY_HOME/bin/jboss-cli.sh --connect --file=restore-configuration.cliNoteFor Windows, use the WILDFLY_HOME\bin\jboss-cli.batscript.
When you have completed testing the quickstart, you can restore the original server configuration by manually restoring the backup copy the configuration file.
-
If it is running, stop the WildFly server.
-
Replace the
WILDFLY_HOME/standalone/configuration/standalone.xmlfile with the backup copy of the file.
Instead of using a standard WildFly server distribution, you can alternatively provision a WildFly server to deploy and run the quickstart. The functionality is provided by the WildFly Maven Plugin, and you may find its configuration in the quickstart pom.xml:
<profile>
<id>provisioned-server</id>
<activation>
<activeByDefault>true</activeByDefault>
</activation>
<build>
<plugins>
<plugin>
<groupId>org.wildfly.plugins</groupId>
<artifactId>wildfly-maven-plugin</artifactId>
<configuration>
<discover-provisioning-info>
<version>${version.server}</version>
</discover-provisioning-info>
<add-ons>...</add-ons>
</configuration>
<executions>
<execution>
<goals>
<goal>package</goal>
</goals>
</execution>
</executions>
</plugin>
...
</plugins>
</build>
</profile>When built, the provisioned WildFly server can 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.
Follow these steps to run the quickstart using the provisioned server.
-
Make sure the server is provisioned.
$ mvn clean package -
Start the WildFly provisioned server, using the WildFly Maven Plugin
startgoal.$ mvn wildfly:start -
Type the following command to run the integration tests.
$ mvn verify -Pintegration-testing -
Shut down the WildFly provisioned server.
$ mvn wildfly:shutdown
You can use the WildFly Maven Plugin 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>
<activation>
<activeByDefault>true</activeByDefault>
</activation>
<build>
<plugins>
<plugin>
<groupId>org.wildfly.plugins</groupId>
<artifactId>wildfly-maven-plugin</artifactId>
<configuration>
<discover-provisioning-info>
<version>${version.server}</version>
</discover-provisioning-info>
<bootable-jar>true</bootable-jar>
<add-ons>...</add-ons>
</configuration>
<executions>
<execution>
<goals>
<goal>package</goal>
</goals>
</execution>
</executions>
</plugin>
...
</plugins>
</build>
</profile>The bootable-jar profile is activate by default, and when built the WildFly bootable jar may be found at target/opentelemetry-tracing-bootable.jar
-
Ensure the bootable jar is built.
$ mvn clean clean package -
Start the WildFly bootable jar use the WildFly Maven Plugin
start-jargoal.$ mvn wildfly:start-jar -
Run the integration tests use the
verifygoal, with theintegration-testingprofile activated.$ mvn verify -Pintegration-testing -
Shut down the WildFly bootable jar use the WildFly Maven Plugin
shutdowngoal.$ mvn wildfly:shutdown
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>
<discover-provisioning-info>
<version>${version.server}</version>
<context>cloud</context>
</discover-provisioning-info>
<add-ons>...</add-ons>
</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 context which enables a configuration tuned for OpenShift environment.
The plugin uses WildFly Glow to discover the feature packs and layers required to run the application, and provisions a server containing those layers.
If you get an error or the server is missing some functionality which cannot be auto-discovered, you can download the WildFly Glow CLI and run the following command to see more information about what add-ons are available:
wildfly-glow show-add-onsThis section contains the basic instructions to build and deploy this quickstart to WildFly for OpenShift or WildFly for OpenShift Online using Helm Charts.
-
You must be logged in OpenShift and have an
occlient 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 applicationsThe 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, to configure the OpenTelemetry Collector as well as any external routes needed:
---
apiVersion: v1
kind: ConfigMap
metadata:
name: collector-config
data:
collector.yml: |
receivers:
otlp:
protocols:
grpc:
http:
processors:
exporters:
logging:
verbosity: detailed
service:
pipelines:
traces:
receivers: [otlp]
processors: []
exporters: [logging]
---
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
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: NoneTo make things simpler, you can find these commands in charts/opentelemetry-collector-openshift.yaml, and to apply them run the following command in your terminal:
$ oc apply -f charts/opentelemetry-collector-openshift.yaml|
Note
|
When done with the quickstart, the |
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 opentelemetry-tracing -f charts/helm.yaml wildfly/wildfly --wait --timeout=10m0s
NAME: opentelemetry-tracing
...
STATUS: deployed
REVISION: 1This 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 opentelemetry-tracingThe 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: opentelemetry-tracing
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/wildflyGet the URL of the route to the deployment.
$ oc get route opentelemetry-tracing -o jsonpath="{.spec.host}"Access the application in your web browser using the displayed URL.
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://$(oc get route opentelemetry-tracing --template='{{ .spec.host }}') |
Note
|
The tests are using SSL to connect to the quickstart running on OpenShift. So you need the certificates to be trusted by the machine the tests are run from. |
For Kubernetes, the build with Apache Maven uses an openshift Maven profile to provision a WildFly server, suitable for running on Kubernetes.
The server provisioning functionality is provided by the WildFly Maven Plugin, and you may find its configuration in the quickstart pom.xml:
<profile>
<id>openshift</id>
<build>
<plugins>
<plugin>
<groupId>org.wildfly.plugins</groupId>
<artifactId>wildfly-maven-plugin</artifactId>
<configuration>
<discover-provisioning-info>
<version>${version.server}</version>
<context>cloud</context>
</discover-provisioning-info>
<add-ons>...</add-ons>
</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 context which enables a configuration tuned for Kubernetes environment.
The plugin uses WildFly Glow to discover the feature packs and layers required to run the application, and provisions a server containing those layers.
If you get an error or the server is missing some functionality which cannot be auto-discovered, you can download the WildFly Glow CLI and run the following command to see more information about what add-ons are available:
wildfly-glow show-add-onsThis section contains the basic instructions to build and deploy this quickstart to Kubernetes using Helm Charts.
In this example we are using Minikube as our Kubernetes provider. See the Minikube Getting Started guide for how to install it. After installing it, we start it with 4GB of memory.
minikube start --memory='4gb'The above command should work if you have Docker installed on your machine. If, you are using Podman instead of Docker, you will also need to pass in --driver=podman, as covered in the Minikube documentation.
Once Minikube has started, we need to enable its registry since that is where we will push the image needed to deploy the quickstart, and where we will tell the Helm charts to download it from.
minikube addons enable registryIn order to be able to push images to the registry we need to make it accessible from outside Kubernetes. How we do this depends on your operating system. All the below examples will expose it at localhost:5000
# On Mac:
docker run --rm -it --network=host alpine ash -c "apk add socat && socat TCP-LISTEN:5000,reuseaddr,fork TCP:$(minikube ip):5000"
# On Linux:
kubectl port-forward --namespace kube-system service/registry 5000:80 &
# On Windows:
kubectl port-forward --namespace kube-system service/registry 5000:80
docker run --rm -it --network=host alpine ash -c "apk add socat && socat TCP-LISTEN:5000,reuseaddr,fork TCP:host.docker.internal:5000"-
Helm must be installed to deploy the backend on Kubernetes.
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 applicationsThe 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 Kubernetes cluster, to configure the OpenTelemetry Collector as well as any external routes needed:
---
apiVersion: v1
kind: ConfigMap
metadata:
name: collector-config
data:
collector.yml: |
receivers:
otlp:
protocols:
grpc:
http:
processors:
exporters:
logging:
verbosity: detailed
service:
pipelines:
traces:
receivers: [otlp]
processors: []
exporters: [logging]
---
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
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: NoneTo make things simpler, you can find these commands in charts/opentelemetry-collector-openshift.yaml, and to apply them run the following command in your terminal:
$ kubectl apply -f charts/opentelemetry-collector-kubernetes.yaml|
Note
|
When done with the quickstart, the |
The backend will be built and deployed on Kubernetes with a Helm Chart for WildFly.
Navigate to the root directory of this quickstart and run the following commands:
mvn -Popenshift package wildfly:imageThis will use the openshift Maven profile we saw earlier to build the application, and create a Docker image containing the WildFly server with the application deployed. The name of the image will be opentelemetry-tracing.
Next we need to tag the image and make it available to Kubernetes. You can push it to a registry like quay.io. In this case we tag as localhost:5000/opentelemetry-tracing:latest and push it to the internal registry in our Kubernetes instance:
# Tag the image
docker tag opentelemetry-tracing localhost:5000/opentelemetry-tracing:latest
# Push the image to the registry
docker push localhost:5000/opentelemetry-tracing:latestIn the below call to helm install which deploys our application to Kubernetes, we are passing in some extra arguments to tweak the Helm build:
-
--set build.enabled=false- This turns off the s2i build for the Helm chart since Kubernetes, unlike OpenShift, does not have s2i. Instead, we are providing the image to use. -
--set deploy.route.enabled=false- This disables route creation normally performed by the Helm chart. On Kubernetes we will use port-forwards instead to access our application, since routes are an OpenShift specific concept and thus not available on Kubernetes. -
--set image.name="localhost:5000/opentelemetry-tracing"- This tells the Helm chart to use the image we built, tagged and pushed to Kubernetes' internal registry above.
$ helm install opentelemetry-tracing -f charts/helm.yaml wildfly/wildfly --wait --timeout=10m0s --set build.enabled=false --set deploy.route.enabled=false --set image.name="localhost:5000/opentelemetry-tracing"
NAME: opentelemetry-tracing
...
STATUS: deployed
REVISION: 1This 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:
kubectl get deployment opentelemetry-tracingThe 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: opentelemetry-tracing
deploy:
replicas: 1
env:
- name: OTEL_COLLECTOR_HOST
value: "opentelemetrycollector"This will create a new deployment on Kubernetes 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/wildflyTo be able to connect to our application running in Kubernetes from outside, we need to set up a port-forward to the opentelemetry-tracing service created for us by the Helm chart.
This service will run on port 8080, and we set up the port forward to also run on port 8080:
kubectl port-forward service/opentelemetry-tracing 8080:8080The server can now be accessed via http://localhost:8080 from outside Kubernetes. Note that the command to create the port-forward will not return, so it is easiest to run this in a separate terminal.
The integration tests included with this quickstart, which verify that the quickstart runs correctly, may also be run with the quickstart running on Kubernetes.
|
Note
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The integration tests expect a deployed application, so make sure you have deployed the quickstart on Kubernetes 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=http://localhost:8080 OpenTelemetry Tracing provides the mechanisms for your application to participate
in the distributed tracing with minimal effort on the application side. The Jakarta REST
resources are always traced by default, but the specification allows you to create
individual spans directly with the CDI injection of the io.opentelemetry.api.trace.Tracer.