Prepare for production

The built-in Prometheus server is a great way to gain insight into the network traffic that enters Gloo Gateway. However, the pod is not set up with persistent storage and metrics are lost when the pod restarts or when the deployment is scaled down. A lot of organizations also run their own Prometheus-compatible solution or time series database that is hardened for production and integrates with other applications that might exist outside of the cluster.

To build a production-level Prometheus setup, you can choose between the following options:

To read more about each option, see Best practices for collecting metrics in production

Replace the built-in Prometheus server with your own instance

In this setup, you disable the built-in Prometheus server and configure Gloo to use your production Prometheus instance instead.

  1. Configure Gloo to disable the default Prometheus instance and instead connect to your custom Prometheus server. Make sure that the instance runs Prometheus version 2.16.0 or later. In the prometheusUrl field, enter the Prometheus URL that your instance is exposed on, such as http://kube-prometheus-stack-prometheus.monitoring:9090. You can get this value from the --web.external-url field in your Prometheus Helm values file or by selecting Status > Command-Line-Flags from the Prometheus UI. Do not use the FQDN for the Prometheus URL.

    helm upgrade --install gloo-platform gloo-platform/gloo-platform \
       --namespace gloo-mesh \
       --version $GLOO_VERSION \
       --values gloo-gateway-single.yaml \
       --set common.cluster=$CLUSTER_NAME \
       --set licensing.glooGatewayLicenseKey=$GLOO_GATEWAY_LICENSE_KEY \
       --set prometheus.enabled=false \
       --set common.prometheusUrl=<Prometheus_server_URL_and_port>

    If you installed Gloo Gateway using the gloo-mesh-enterpise, gloo-mesh-agent, and other included Helm charts, or by using meshctl version 2.2 or earlier, these Helm charts are considered legacy. Migrate your legacy installation to the new gloo-platform Helm chart.

    helm upgrade --install gloo-mgmt gloo-mesh-enterprise/gloo-mesh-enterprise \
       --namespace gloo-mesh \
       --version $GLOO_VERSION \
       --values values-mgmt-plane-env.yaml \
       --set prometheus.enabled=false \
       --set prometheusUrl=<Prometheus_server_URL_and_port> \
       --set glooGatewayLicenseKey=${GLOO_GATEWAY_LICENSE_KEY} \
       --set global.cluster=$CLUSTER_NAME

    Make sure to include your Helm values when you upgrade either as a configuration file in the –values flag or with –set flags. Otherwise, any previous custom values that you set might be overwritten. In single cluster setups, this might mean that your Gloo agent and ingress gateways are removed. To get your current values, such as for a release named gloo-platform, you can run helm get values gloo-platform -n gloo-mesh > gloo-gateway-single.yaml. For more information, see Get your Helm chart values in the upgrade guide.

  2. Configure your Prometheus server to scrape metrics from the Gloo management server endpoint gloo-mesh-mgmt-server-admin.gloo-mesh:9091. This setup might vary depending on the Prometheus server that you use. For example, if you use the Prometheus Community Chart, update the Helm values.yaml file as follows to scrape metrics from the Gloo management server.

        - job_name: gloo-mesh
          scrape_interval: 15s
          scrape_timeout: 10s
          - targets:
            - gloo-mesh-mgmt-server-admin.gloo-mesh:9091

Recommended: Federate metrics with recording rules and provide them to your production monitoring instance

In this setup, you inject recording rules in to the built-in Prometheus server in Gloo to federate the metrics that you want and reduce high cardinality labels. Then, you set up another Prometheus instance in the Gloo management cluster to scrape the federated metrics. You can optionally forward the federated metrics to a Prometheus-compatible solution or a time series database that sits outside of your Gloo management cluster and is hardened for production.

  1. Get the configuration of the built-in Prometheus server in Gloo and save it to a local file on your machine.

    kubectl get configmap prometheus-server -n gloo-mesh -o yaml > config.yaml
  2. Review the metrics that are sent to the built-in Prometheus server by default.

    1. Open the Prometheus dashboard.
        meshctl proxy prometheus
        Port-forward the `prometheus-server` deployment on 9091.
        kubectl -n gloo-mesh port-forward deploy/prometheus-server 9091
    2. Open your browser and connect to localhost:9091/.
    3. Decide on the subset of metrics that you want to federate.
  3. Add a recording rule to the configmap of your Gloo Prometheus instance that you retrieved earlier to define how you want to aggregate the metrics. Recording rules let you precompute frequently needed or computationally expensive expressions. For example, you can remove high cardinality labels and federate only the labels that you need in future dashboards or alert queries. The results are saved in a new set of time series that you can later scrape or send to an external monitoring instance that is hardened for production. With this setup, you can protect your production instance as you send only the metrics that you need. In addition, you use the compute resources in the Gloo management cluster to prepare and aggregate the metrics.

    In this example, you use the istio_requests_total metric to record the total number of requests that Gloo Gateway receives. As part of this aggregation, pod labels are removed as they might lead to cardinality issues in certain environments. The result is saved as the workload:istio_requests_total metric to make sure that you can distinguish the original istio_requests_total metric from the aggregated one.

    apiVersion: v1
      alerting_rules.yml: |
      alerts: |
      prometheus.yml: |
      recording_rules.yml: |
        - name: istio.workload.istio_requests_total
          interval: 10s
          - record: workload:istio_requests_total
            expr: |
              by (
      rules: |
    kind: ConfigMap

  4. Deploy another Prometheus instance in the Gloo management cluster to scrape the federated metrics from the Prometheus instance.

    1. Create the monitoring namespace in the Gloo management cluster.
      kubectl create namespace monitoring
    2. Add the Prometheus community Helm repository.
      helm repo add prometheus-community
    3. Install the Prometheus community chart.
      helm install kube-prometheus-stack prometheus-community/kube-prometheus-stack --version 30.0.1 -f values.yaml -n monitoring --debug
    4. Verify that the Prometheus pods are running.
      kubectl get pods -n monitoring
  5. Add a service monitor to the Prometheus instance that you just created to scrape the aggregated metrics from the built-in Prometheus instance in Gloo and to expose them on the /federate endpoint.

    In the following example, metrics from the built-in Prometheus instance that match the 'workload:(.*)' regex expression are scraped. With the recording rule that you defined earlier, workload:istio_requests_total is the only metric that matches this criteria. The service monitor configuration also removes workload: from the metric name so that it is displayed as the istio_requests_total metric in Prometheus queries. To access the aggregated metrics that you scraped, you send a request to the /federate endpoint and provide match[]={__name__=<metric>} as a request parameter.

    kind: ServiceMonitor
      name: gloo-metrics-federation
      namespace: monitoring
      labels: gloo-prometheus
        - gloo-mesh
          app: prometheus
      - interval: 30s
        scrapeTimeout: 30s
          - '{__name__=~"workload:(.*)"}'
        path: /federate
        targetPort: 9090
        honorLabels: true
        - sourceLabels: ["__name__"]
          regex: 'workload:(.*)'
          targetLabel: "__name__"
          action: replace
  6. Access the /federate endpoint to see the scraped metrics. Note that you must include the match[]={__name__=<metric>} request parameter to successfully see the aggregated metrics.

    1. Port forward the Prometheus service so that you can access the Prometheus UI on your local machine.

      kubectl port-forward service/kube-prometheus-stack-prometheus -n monitoring 9090
    2. Open the targets that are configured for your Prometheus instance.

      open https://localhost:9090/targets
    3. Select the gloo-metrics-federation target that you configured and verify that the endpoint address and match condition are correct, and that the State displays as UP.

      Gloo federation target

    4. Optional: Access the aggregated metrics on the /federate endpoint.

      open https://localhost:9090/federate?match[]={__name__="istio_requests_total"}

      Example output:

      # TYPE istio_requests_total untyped
      istio_requests_total{container="prometheus-server",destination_app="ratings",destination_service="ratings.bookinfo.svc.cluster.local",destination_workload="ratings-v1",destination_workload_namespace="bookinfo",endpoint="9090",job="prometheus-server",namespace="gloo-mesh",pod="prometheus-server-647b488bb-ns748",reporter="destination",response_code="200",response_flags="-",service="prometheus-server",source_app="istio-ingressgateway",source_workload="istioingressgateway",source_workload_namespace="istio-system",instance="",prometheus="monitoring/kube-prometheus-stack-prometheus",prometheus_replica="prometheus-kube-prometheus-stack-prometheus-0"} 11 1654888576995
      istio_requests_total{container="prometheus-server",destination_app="ratings",destination_service="ratings.bookinfo.svc.cluster.local",destination_workload="ratings-v1",destination_workload_namespace="bookinfo",endpoint="9090",job="prometheus-server",namespace="gloo-mesh",pod="prometheus-server-647b488bb-ns748",reporter="source",response_code="200",response_flags="-",service="prometheus-server",source_app="istio-ingressgateway",source_workload="istio-ingressgateway",source_workload_namespace="istio-system",instance="",prometheus="monitoring/kube-prometheus-stack-prometheus",prometheus_replica="prometheus-kube-prometheus-stack-prometheus-0"} 11 1654888576995
  7. Forward the federated metrics to your external Prometheus-compatible solution or time series database that is hardened for production. Refer to the Prometheus documentation to explore your forwarding options or try out the Prometheus agent mode.