4.2. Using Red Hat OpenShift distributed tracing

Procedure

1. Create an OpenTelemetryCollector custom resource (CR):

   Example OpenTelemetryCollector CR

   apiVersion: opentelemetry.io/v1alpha1
   kind: OpenTelemetryCollector
   metadata:
     name: cluster-collector
     namespace: <namespace>
   spec:
     mode: deployment
     config: |
       receivers:
         zipkin:
       processors:
       exporters:
         jaeger:
           endpoint: jaeger-all-in-one-inmemory-collector-headless.tracing-system.svc:14250
           tls:
             ca_file: "/var/run/secrets/kubernetes.io/serviceaccount/service-ca.crt"
         logging:
       service:
         pipelines:
           traces:
             receivers: [zipkin]
             processors: []
             exporters: [jaeger, logging]

2. Verify that you have two pods running in the namespace where Red Hat OpenShift distributed tracing is installed:

   $ oc get pods -n <namespace>

   Example output

   NAME                                          READY   STATUS    RESTARTS   AGE
   cluster-collector-collector-85c766b5c-b5g99   1/1     Running   0          5m56s
   jaeger-all-in-one-inmemory-ccbc9df4b-ndkl5    2/2     Running   0          15m

3. Verify that the following headless services have been created:

   $ oc get svc -n <namespace> | grep headless

   Example output

   cluster-collector-collector-headless            ClusterIP   None             <none>        9411/TCP                                 7m28s
   jaeger-all-in-one-inmemory-collector-headless   ClusterIP   None             <none>        9411/TCP,14250/TCP,14267/TCP,14268/TCP   16m

   These services are used to configure Jaeger, Knative Serving, and Knative Eventing. The name of the Jaeger service may vary.

4. Install the OpenShift Serverless Operator by following the "Installing the OpenShift Serverless Operator" documentation.

5. Install Knative Serving by creating the following KnativeServing CR:

   Example KnativeServing CR

   apiVersion: operator.knative.dev/v1beta1
   kind: KnativeServing
   metadata:
       name: knative-serving
       namespace: knative-serving
   spec:
     config:
       tracing:
         backend: "zipkin"
         zipkin-endpoint: "http://cluster-collector-collector-headless.tracing-system.svc:9411/api/v2/spans"
         debug: "false"
         sample-rate: "0.1" 

   1

   1

   The sample-rate defines sampling probability. Using sample-rate: "0.1" means that 1 in 10 traces are sampled.

6. Install Knative Eventing by creating the following KnativeEventing CR:

   Example KnativeEventing CR

   apiVersion: operator.knative.dev/v1beta1
   kind: KnativeEventing
   metadata:
       name: knative-eventing
       namespace: knative-eventing
   spec:
     config:
       tracing:
         backend: "zipkin"
         zipkin-endpoint: "http://cluster-collector-collector-headless.tracing-system.svc:9411/api/v2/spans"
         debug: "false"
         sample-rate: "0.1" 

   1

   1

   The sample-rate defines sampling probability. Using sample-rate: "0.1" means that 1 in 10 traces are sampled.

7. Create a Knative service:

   Example service

   apiVersion: serving.knative.dev/v1
   kind: Service
   metadata:
     name: helloworld-go
   spec:
     template:
       metadata:
         labels:
           app: helloworld-go
         annotations:
           autoscaling.knative.dev/minScale: "1"
           autoscaling.knative.dev/target: "1"
       spec:
         containers:
         - image: quay.io/openshift-knative/helloworld:v1.2
           imagePullPolicy: Always
           resources:
             requests:
               cpu: "200m"
           env:
           - name: TARGET
             value: "Go Sample v1"

8. Make some requests to the service:

   Example HTTPS request

   $ curl https://helloworld-go.example.com

9. Get the URL for the Jaeger web console:

   Example command

   $ oc get route jaeger-all-in-one-inmemory  -o jsonpath='{.spec.host}' -n <namespace>

   You can now examine traces by using the Jaeger console.