Camel K Monitoring

The Camel K monitoring architecture relies on Prometheus and the eponymous operator.

The Prometheus Operator serves to make running Prometheus on top of Kubernetes as easy as possible, while preserving Kubernetes-native configuration options.

Prerequisites

To take full advantage of the Camel K monitoring capabilities, it is recommended to have a Prometheus Operator instance, that can be configured to integrate the Camel K operator and integrations.

Kubernetes

The easiest way of starting with the Prometheus Operator is by deploying it as part of kube-prometheus, which provisions an entire monitoring stack. You can follow the quickstart from the Prometheus Operator documentation.

Alternatively, you can quickly deploy the Prometheus operator by running:

$ kubectl apply -f https://raw.githubusercontent.com/prometheus-operator/prometheus-operator/main/bundle.yaml
Beware this installs the operator in the default namespace. You must download the file locally and replace the namespace fields to deploy the resources into another namespace. This also installs the version from the main branch, which you can change in the URL by choosing a stable release version.

Then, you can create a Prometheus resource, that the operator will use as configuration to deploy a managed Prometheus instance:

$ cat <<EOF | kubectl apply -f -
apiVersion: monitoring.coreos.com/v1
kind: Prometheus
metadata:
  name: prometheus
spec:
  podMonitorSelector:
    matchExpressions:
      - key: camel.apache.org/integration
        operator: Exists
EOF

By default, the Prometheus instance discovers applications to be monitored in the same namespace. You can use the podMonitorNamespaceSelector field from the Prometheus resource to enable cross-namespace monitoring. You may also need to specify a ServiceAccount with the serviceAccountName field, that’s bound to a Role with the necessary permissions.

OpenShift

Starting OpenShift 4.3, the Prometheus Operator, that’s already deployed as part of the monitoring stack, can be used to monitor application services. This needs to be enabled by following these instructions:

  1. Check whether the cluster-monitoring-config ConfigMap object exists in the openshift-monitoring project:

    $ oc -n openshift-monitoring edit configmap cluster-monitoring-config

  2. If it does not exist, create it:

    $ oc -n openshift-monitoring create configmap cluster-monitoring-config

  3. Start editing the cluster-monitoring-config ConfigMap:

    $ oc -n openshift-monitoring edit configmap cluster-monitoring-config

  4. Set the enableUserWorkload setting to true under data/config.yaml:

    apiVersion: v1
kind: ConfigMap
metadata:
  name: cluster-monitoring-config
  namespace: openshift-monitoring
data:
  config.yaml: |
    enableUserWorkload: true

    Note that, in OpenShift versions from 4.3 to 4.5, the configuration is as following:

    apiVersion: v1
kind: ConfigMap
metadata:
  name: cluster-monitoring-config
  namespace: openshift-monitoring
data:
  config.yaml: |
    techPreviewUserWorkload:
      enabled: true

On OpenShift versions prior to 4.3, or if you do not want to change your cluster monitoring stack configuration, you can refer to the Kubernetes section in order to deploy a separate Prometheus Operator instance.

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