The Gloo telemetry pipeline integrates with Jaeger as the tracing platform. Jaeger is an open source tool that helps you follow the path of a request as it is forwarded between microservices. The chain of events and interactions are then captured by the Gloo telemetry pipeline and visualized in the Jaeger UI that is embedded in the Gloo UI. You can use this data to troubleshoot issues in your microservices and identify bottlenecks. You can also forward the traces from the Gloo telemetry gateway to your own Jaeger tracing platform.

Before you begin

  1. Complete the multicluster getting started guide to set up the following testing environment.

    • Three clusters along with environment variables for the clusters and their Kubernetes contexts.
    • The Gloo meshctl CLI, along with other CLI tools such as kubectl and istioctl.
    • The Gloo management server in the management cluster, and the Gloo agents in the workload clusters.
    • Istio installed in the workload clusters.
    • A simple Gloo workspace setup.
  2. Install Bookinfo and other sample apps.

Step 1: Enable tracing in Istio

Instrument Istio workloads to collect traces by updating your Istio installation. The steps to update Istio vary depending on how you installed Istio.

  1. If you use Gloo-managed Istio and gateway proxies, follow the steps in the Istio lifecycle manager upgrade guide. In the istioOperatorSpec.meshConfig section, add the following configuration to set a sampling rate of 100% of requests. The traces are forwarded to the Gloo telemetry collector agents. For more information about the sampling rate, custom tag, and maximum path length settings, see the Istio tracing configuration docs.

      
meshConfig:
  enableTracing: true
  defaultConfig:
    tracing:
      sampling: 100
      zipkin:
        address: gloo-telemetry-collector.gloo-mesh.svc.cluster.local:9411

  2. Verify that your configuration is applied in the cluster.

      

export REVISION=$(kubectl get pod -L app=istiod -n istio-system -o jsonpath='{.items[0].metadata.labels.istio\.io/rev}')
kubectl get istiooperator istiod-control-plane --context $REMOTE_CONTEXT -n gm-iop-$REVISION -o yaml

  3. Restart the Istio workloads that you want to collect traces for. For example, if you deployed the Bookinfo sample app as part of the Get started guide, you can restart the product page app with the following command.

      kubectl rollout restart deployment productpage-v1 -n bookinfo --context $REMOTE_CONTEXT

  1. Refer to the Istio documentation for instructions on how to update your Istio installation. The following example meshConfig options set a sampling rate of 100% of requests. These traces are sent to the Gloo telemetry collector agent.

      
meshConfig:      
  enableTracing: true
  defaultConfig: 
    tracing: 
      sampling: 100
      zipkin:
        address: gloo-telemetry-collector.gloo-mesh.svc.cluster.local:9411

    For more information about the sampling rate, custom tag, and maximum path length settings, see the Istio tracing configuration docs.

  2. Restart the Istio workloads that you want to collect traces for. For example, if you deployed the Bookinfo sample app as part of the Get started guide, you can restart the product page app with the following command.

      kubectl rollout restart deployment productpage-v1 -n bookinfo --context $REMOTE_CONTEXT

Step 2: Enable the Jaeger UI and add traces to the pipeline

Now that your traces are enabled for Istio workloads, you can configure the Gloo telemetry pipeline to collect the traces and provide them to the built-in Jaeger instance that is embedded in to the Gloo UI or forward the traces to your own Jaeger tracing platform.

Use the built-in Jaeger

During your Gloo Mesh Enterprise installation, you can enable Jaeger as the tracing platform for your Gloo environment and embed the Jaeger UI in to the Gloo UI.

  1. Get your current installation Helm values, and save them in a file.

      helm get values gloo-platform -n gloo-mesh -o yaml > gloo-single.yaml
open gloo-single.yaml

  2. Add the following settings to enable Jaeger and the built-in traces/istio pipeline. The traces/istio pipeline is set up on the Gloo collector agent and collects traces from Istio-enabled workloads. Traces are sent to the built-in Jaeger tracing platform.

      
jaeger:
  enabled: true
telemetryCollectorCustomization:
  pipelines:
    traces/istio:
      enabled: true

  3. Upgrade your installation by using your updated values file.

      helm upgrade gloo-platform gloo-platform/gloo-platform \
   --namespace gloo-mesh \
   --version $GLOO_VERSION \
   --values gloo-single.yaml

  4. Verify that you see a gloo-jaeger deployment in your cluster.

      kubectl get deployment gloo-jaeger -n gloo-mesh

  5. Verify that your custom Jaeger settings were added to the Gloo telemetry collector configmap.

      kubectl get configmap gloo-telemetry-collector-config -n gloo-mesh -o yaml

  6. Perform a rollout restart of the telemetry collector daemon set to force your configmap changes to be applied to the telemetry collector agent pod.

      kubectl rollout restart -n gloo-mesh daemonset/gloo-telemetry-collector-agent

  1. Get your current Helm values file for the management cluster.

      helm get values gloo-platform -n gloo-mesh -o yaml --kube-context $MGMT_CONTEXT > mgmt-plane.yaml
open mgmt-plane.yaml

  2. Enable the built-in Jaeger platform and the traces/jaeger pipeline to forward traces from the telemetry gateway to the built-in Jaeger platform. Because a Gloo telemetry collector agent is also deployed to the management cluster, you must enable the traces/istio pipeline on the collector for traces to be collected in the management cluster.

      
jaeger:
  enabled: true
telemetryGateway:
  enabled: true
telemetryGatewayCustomization:
  pipelines:
    traces/jaeger:
      enabled: true
telemetryCollector:
  enabled: true
telemetryCollectorCustomization:
  pipelines:
    traces/istio:
      enabled: true

  3. Upgrade the management cluster.

      helm upgrade gloo-platform gloo-platform/gloo-platform \
  --kube-context $MGMT_CONTEXT \
  --namespace gloo-mesh \
  -f mgmt-plane.yaml \
  --version $GLOO_VERSION

  4. Verify that your settings are applied in the management cluster.

    1. Verify that you see a gloo-jaeger deployment in your cluster.

        kubectl get deployment gloo-jaeger -n gloo-mesh --context $MGMT_CONTEXT

    2. Verify that the tracing settings were added to the Gloo telemetry collector and gateway configmaps.

        kubectl get configmap gloo-telemetry-collector-config -n gloo-mesh -o yaml --context $MGMT_CONTEXT
kubectl get configmap gloo-telemetry-gateway-config -n gloo-mesh -o yaml --context $MGMT_CONTEXT

    3. Perform a rollout restart of the telemetry gateway deployment and the telemetry collector daemon set to force your configmap changes to be applied to the telemetry gateway and collector agent pods.

        kubectl rollout restart -n gloo-mesh deployment/gloo-telemetry-gateway --context $MGMT_CONTEXT
kubectl rollout restart -n gloo-mesh daemonset/gloo-telemetry-collector-agent --context $MGMT_CONTEXT

  5. Get your current Helm values file for the workload clusters.

      helm get values gloo-platform -n gloo-mesh -o yaml --kube-context $REMOTE_CONTEXT > data-plane.yaml
open data-plane.yaml

  6. Enable the traces/istio pipeline to pick up traces from Istio-enabled workloads and forward them to the Gloo telemetry gateway.

      
telemetryCollector:
  enabled: true
telemetryCollectorCustomization:
  pipelines:
    traces/istio:
      enabled: true

  7. Upgrade the workload cluster.

      helm upgrade gloo-platform gloo-platform/gloo-platform \
  --kube-context $REMOTE_CONTEXT \
  --namespace gloo-mesh \
  -f data-plane.yaml \
  --version $GLOO_VERSION

  8. Verify that your settings are applied in the workload cluster.

    1. Verify that the tracing settings were added to the Gloo telemetry collector configmap.

        kubectl get configmap gloo-telemetry-collector-config -n gloo-mesh -o yaml --context $REMOTE_CONTEXT

    2. Perform a rollout restart of the telemetry collector daemon set to force your configmap changes to be applied to the telemetry collector agent pods.

        kubectl rollout restart -n gloo-mesh daemonset/gloo-telemetry-collector-agent --context $REMOTE_CONTEXT

Bring your own Jaeger

Instead of using the built-in Jaeger instance, you can configure the Gloo UI to point to your Jaeger instance instead.

  1. Install or use an existing Jaeger instance. For example, you might follow the Jaeger documentation to set up Jaeger in your cluster. Do not use the jaeger.enabled setting in the Helm values file as this setting enables the built-in Jaeger instance.

  2. Get your current installation Helm values, and save them in a file.

      helm get values gloo-platform -n gloo-mesh -o yaml > gloo-single.yaml
open gloo-single.yaml

  3. In the Helm chart for your management cluster, add the endpoint, port, and base path for your Jaeger instance in the glooUi section to embed the Jaeger UI into the Gloo UI, and disable the Jaeger UI that is automatically built in to Gloo Mesh Enterprise. Note that your Jaeger platform must be served from a path that is different from / as this path is reserved for the built-in Jaeger instance in Gloo Mesh Enterprise.

    To pick up traces from workloads and send them to your Jaeger instance, enable the built-in traces/istio pipeline and add an extra exporter.

      
jaeger: 
  enable: false
glooUi: 
  tracing: 
    endpoint: "<endpoint>"
    port: <port>
    basePath: "/<base-path>"
telemetryGateway:
  enabled: false
telemetryCollectorCustomization:
  extraExporters:
    otlp/jaeger-custom:
      endpoint: myjaeger:4317
      tls:
        insecure: true
  pipelines:
    traces/istio: 
      enabled: true
      pipeline: 
        exporters: 
        - otlp/jaeger-custom
telemetryCollector:
  enabled: true

  4. Upgrade your installation by using your updated values file.

      helm upgrade gloo-platform gloo-platform/gloo-platform \
   --namespace gloo-mesh \
   --version $GLOO_VERSION \
   --values gloo-single.yaml

  5. Verify that your custom Jaeger settings were added to the Gloo telemetry collector configmap.

      kubectl get configmap gloo-telemetry-collector-config -n gloo-mesh -o yaml

  6. Perform a rollout restart of the telemetry collector daemon set to force your configmap changes to be applied to the telemetry collector agent pod.

      kubectl rollout restart -n gloo-mesh daemonset/gloo-telemetry-collector-agent

  1. Get the Helm values files for your current version.

    1. Get your current values for the management cluster.
        helm get values gloo-platform -n gloo-mesh -o yaml --kube-context $MGMT_CONTEXT > mgmt-plane.yaml
open mgmt-plane.yaml
    2. Get your current values for the workload clusters.
        helm get values gloo-platform -n gloo-mesh -o yaml --kube-context $REMOTE_CONTEXT > data-plane.yaml
open data-plane.yaml

  2. In the Helm chart for your management cluster, add the endpoint, port, and base path for your Jaeger instance in the glooUi section to embed the Jaeger UI into the Gloo UI and disable the Jaeger UI that is automatically built in to Gloo Mesh Enterprise. Note that your Jaeger platform must be served from a path that is different from / as this path is reserved for the built-in Jaeger instance in Gloo Mesh Enterprise.

    To forward traces from the Gloo telemetry gateway to your Jaeger instance, set up an extra exporter on the Gloo telemetry gateway with the details of your Jaeger endpoint, and add that exporter to the default traces/jaeger pipeline in your Helm values file. For more information about how to set up the exporter, see the OTLP gRPC exporter documentation.

    To collect traces from workloads in the management cluster, enable the traces/istio pipeline in the Gloo telemetry collector agent.

      
jaeger: 
  enable: false
glooUi: 
  tracing: 
    endpoint: "<endpoint>"
    port: <port>
    basePath: "/<base-path>"
telemetryGateway:
  enabled: true
  service:
    type: ClusterIP
telemetryGatewayCustomization:
  extraExporters:
    otlp/jaeger-custom:
      endpoint: myjaeger:4317
      tls:
        insecure: true
  pipelines:
    traces/jaeger: 
      enabled: true
      pipeline: 
        exporters: 
        - otlp/jaeger-custom
telemetryCollector:
  enabled: true
telemetryCollectorCustomization:
  pipelines:
    traces/istio:
      enabled: true
  extraExporters:
    otlp/jaeger:
      endpoint: gloo-jaeger-collector.gloo-mesh.svc:4317
      tls:
        insecure: true

  3. In the Helm value file for the workload cluster, enable the default traces/istio pipeline in your Helm values file to collect traces from Istio-enabled workloads. The traces/istio pipeline is configured on the Gloo collector agents and sends traces to the Gloo telemetry gateway in the management cluster.

      
telemetryCollector:
  config:
    exporters:
      otlp:
        endpoint: gloo-telemetry-gateway.gloo-mesh:4317
telemetryCollectorCustomization:
  pipelines:
    traces/istio:
      enabled: true

  4. Upgrade the management cluster.

      helm upgrade gloo-platform gloo-platform/gloo-platform \
  --kube-context $MGMT_CONTEXT \
  --namespace gloo-mesh \
  -f mgmt-plane.yaml \
  --version $GLOO_VERSION

  5. Verify that your settings are applied in the management cluster.

    1. Verify that the tracing settings were added to the Gloo telemetry collector and gateway configmaps.

        kubectl get configmap gloo-telemetry-collector-config -n gloo-mesh -o yaml --context $MGMT_CONTEXT
kubectl get configmap gloo-telemetry-gateway-config -n gloo-mesh -o yaml --context $MGMT_CONTEXT

    2. Perform a rollout restart of the telemetry gateway deployment and the telemetry collector daemon set to force your configmap changes to be applied to the telemetry gateway and collector agent pods.

        kubectl rollout restart -n gloo-mesh deployment/gloo-telemetry-gateway --context $MGMT_CONTEXT
kubectl rollout restart -n gloo-mesh daemonset/gloo-telemetry-collector-agent --context $MGMT_CONTEXT

  6. Upgrade the workload cluster.

      helm upgrade gloo-platform gloo-platform/gloo-platform \
  --kube-context $REMOTE_CONTEXT \
  --namespace gloo-mesh \
  -f data-plane.yaml \
  --version $GLOO_VERSION

  7. Verify that your settings are applied in the workload cluster.

    1. Verify that the tracing settings were added to the Gloo telemetry collector configmap.

        kubectl get configmap gloo-telemetry-collector-config -n gloo-mesh -o yaml --context $REMOTE_CONTEXT

    2. Perform a rollout restart of the telemetry collector daemon set to force your configmap changes to be applied to the telemetry collector agent pods.

        kubectl rollout restart -n gloo-mesh daemonset/gloo-telemetry-collector-agent --context $REMOTE_CONTEXT

Step 3: Verify tracing

Open the Gloo UI and verify that traces are collected for your Istio workloads.

  1. Open the Gloo UI.

      meshctl dashboard
  
      meshctl dashboard --kubecontext $MGMT_CONTEXT

  2. From the menu, select Observability > Tracing and verify that the Jaeger UI opens.

    Figure: Jaeger UI
    Figure: Jaeger UI
    Figure: Jaeger UI
    Figure: Jaeger UI

  3. Send a few sample requests to your Istio workloads. Each request produces Istio traces that are sent to the Jaeger instance that you configured. For example, if you deployed the Bookinfo sample app from the Get started guide, use the following steps to produce traces.

    1. Port-forward the product page app.
        kubectl port-forward deployment/productpage-v1 -n bookinfo 9080
    2. Open the product page app.
    3. Refresh the page multiple times.

  4. Wait a few seconds and verify that traces are displayed in the Gloo UI.

    Figure: Product page traces
    Figure: Product page traces
    Figure: Product page traces
    Figure: Product page traces