docs/modules/ROOT/pages/observability/monitoring.adoc

[[monitoring]]
= Camel K Monitoring

The Camel K monitoring architecture relies on https://prometheus.io[Prometheus] and the eponymous operator.

The https://prometheus-operator.dev[Prometheus Operator] serves to make running Prometheus on top of Kubernetes as easy as possible, while preserving Kubernetes-native configuration options.

[[prerequisites]]
== 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]]
=== Kubernetes

The easiest way of starting with the Prometheus Operator is by deploying it as part of https://github.com/prometheus-operator/kube-prometheus[kube-prometheus], which provisions an entire monitoring stack.
You can follow the https://prometheus-operator.dev/docs/prologue/quick-start/[quickstart] from the Prometheus Operator https://prometheus-operator.dev/[documentation].

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

[source,console]
----
$ kubectl apply -f https://raw.githubusercontent.com/prometheus-operator/prometheus-operator/main/bundle.yaml
----

WARNING: 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:

[source,console]
----
$ 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]]
=== OpenShift

Starting OpenShift 4.3, the Prometheus Operator, that's already deployed as part of the monitoring stack, can be used to https://docs.openshift.com/container-platform/4.3/monitoring/monitoring-your-own-services.html[monitor application services].
This needs to be enabled by following these instructions:

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

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

. If it does not exist, create it:

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

. Start editing the cluster-monitoring-config ConfigMap:

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

. Set the `enableUserWorkload` setting to `true` under `data/config.yaml`:
+
[source,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:
+
[source,yaml]
----
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.

=== What's Next

- xref:observability/monitoring/operator.adoc[Camel K operator monitoring]
- xref:observability/monitoring/integration.adoc[Camel K integration monitoring]