8.2. 使用 Red Hat OpenShift distributed tracing 启用分布式追踪

流程

1. 创建 OpenTelemetryCollector 自定义资源 (CR) ：

   OpenTelemetryCollector CR 示例

   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. 验证有两个 pod 在安装了 Red Hat OpenShift distributed tracing 的命名空间中运行：

   $ oc get pods -n <namespace>

   输出示例

   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. 验证是否已创建以下无头服务：

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

   输出示例

   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

   这些服务用于配置 Jaeger、Knative Serving 和 Knative Eventing。Jaeger 服务的名称可能会有所不同。

4. 按照"安装 OpenShift Serverless Operator"文档安装 OpenShift Serverless Operator。

5. 通过创建以下 KnativeServing CR 来安装 Knative Serving：

   KnativeServing CR 示例

   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

   sample-rate 定义抽样概率。sample-rate: "0.1" 表示在 10 个 trace 中会抽样 1 个。

6. 通过创建以下 KnativeEventing CR 来安装 Knative Eventing ：

   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

   sample-rate 定义抽样概率。sample-rate: "0.1" 表示在 10 个 trace 中会抽样 1 个。

7. 创建 Knative 服务：

   服务示例

   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. 向服务发出一些请求：

   HTTPS 请求示例

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

9. 获取 Jaeger web 控制台的 URL：

   示例命令

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

   现在，您可以使用 Jaeger 控制台检查 trace。