Cloud team working with Kubernetes endpoints
CLOUD & MANAGED SERVICESCLOUDKUBERNETES
19/03/2021 • Jeroen Hartgers

How to set up auto-discovery of Kubernetes endpoint services in Prometheus

It’s kicking in an open door to state that you need monitoring when having applications running in Kubernetes (K8s). As K8s is becoming more mature and more adopted year after year (and here to stay), it’s only logical that lots of companies have built professional online monitoring and alerting solutions. Others have created excellent Helm charts that easily and swiftly install a K8s namespace with kube-state-metrics, Prometheus, Grafana with dashboards and Alert manager all-ready-to-go.

K8s dashboard with kube-state-metrics, Prometheus, Grafana

The problem with that is that this is all rather ‘standard’. When you already have a fully customized Prometheus/Grafana setup in Rancher 1, such as we do, it seems a waste to throw this out the window. The journey from a Rancher 1 ‘cattle’ Prometheus/Grafana to Rancher 2 K8s went very smooth and was fairly easy.

However, with Prometheus, you historically would have to edit the prometheus.yaml file every time you want to scrape a new application, unless you had already added your own custom discovery tool as a scrape.

Fixing the incomplete data with auto-discovery

A problem that I faced with directly scraping a Longhorn and Spring Boot (or any other) Service in K8s, is that only one of the many backend pods behind that Service is scraped. So, you end up with incomplete data in Prometheus and hence incomplete data in your dashboards in Grafana. In Prometheus, you can see that only one of three existing Longhorn endpoints is scraped.

prometheus tool

In Grafana, you can see that there is only one node accounted for and the other two are reported as ‘Failed Nodes’. To make matters worse, only one of seven volumes is reported at ‘Total Number of Volumes’.

grafana dashboard

This is where auto-discovery of Kubernetes endpoint services comes in as a true savior. Many web pages describe the various aspects of scraping, but I found none of them complete and others had critical errors.

In this blog post, I’ll provide you with a minimal and simple configuration to bring your Prometheus configuration with auto-discovery of Kubernetes endpoint services up to speed.

1. Include configMap additions for Prometheus

Add this to the end of the prometheus.yaml in your Prometheus configMap. The jobname is ‘kubernetes-service-endpoints’ as it seemed appropriate.

# Scrape config for service endpoints.
#
# The relabeling allows the actual service scrape endpoint to be configured
# via the following annotations:
#
# * `prometheus.io/scrape`: Only scrape services that have a value of `true`
# * `prometheus.io/scheme`: If the metrics endpoint is secured then you will need
# to set this to `https` & most likely set the `tls_config` of the scrape config.
# * `prometheus.io/path`: If the metrics path is not `/metrics` override this.
# * `prometheus.io/port`: If the metrics are exposed on a different port to the
# service then set this appropriately.
- job_name: 'kubernetes-service-endpoints'
 scrape_interval: 5s
 scrape_timeout: 2s
 kubernetes_sd_configs:
   - role: endpoints
 relabel_configs:
   - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
     action: keep
     regex: true
   - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
     action: replace
     target_label: __scheme__
     regex: (https?)
   - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
     action: replace
     target_label: __metrics_path__
     regex: (.+)
   - source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]
     action: replace
     target_label: __address__
     regex: (.+)(?::\d+);(\d+)
     replacement: $1:$2
   - action: labelmap
     regex: __meta_kubernetes_service_label_(.+)
   - source_labels: [__meta_kubernetes_namespace]
     action: replace
     target_label: kubernetes_namespace
   - source_labels: [__meta_kubernetes_service_name]
     action: replace
     target_label: kubernetes_name

2. Configure the Services

As in the comment above of the prometheus.yaml, you can configure the following annotations. The annotation prometheus.io/scrape: “true” is mandatory, if you want to scrape a particular service. All the other annotations are optional and explained here:

  • prometheus.io/scrape: Only scrape services that have a value of `true`
  • prometheus.io/scheme: If the metrics endpoint is secured then you will need to set this to `https` & most likely set the `tls_config` of the scrape config.
  • prometheus.io/path: If the metrics path is not `/metrics` override this.
  • prometheus.io/port: If the metrics are exposed on a different port to the service then set this appropriately.

Let’s look at an example for a Longhorn Service first. (Longhorn is a great replicated storage solution!)

apiVersion: v1
kind: Service
metadata:
 annotations:
   prometheus.io/port: "9500"
   prometheus.io/scrape: "true"
 labels:
   app: longhorn-manager
 name: longhorn-backend
 namespace: longhorn-system
spec:
 ports:
 - name: manager
   port: 9500
   protocol: TCP
   targetPort: manager
 selector:
   app: longhorn-manager
 sessionAffinity: ClientIP
 sessionAffinityConfig:
   clientIP:
     timeoutSeconds: 10800
 type: ClusterIP

Next, let’s look at an example for a Spring Boot Application Service. Note the non-standard scrape path /actuator/prometheus.

apiVersion: v1
kind: Service
metadata:
 name: springbootapp
 namespace: spring
 labels:
   app: gateway
 annotations:
   prometheus.io/path: "/actuator/prometheus"
   prometheus.io/port: "8080"
   prometheus.io/scrape: "true"
spec:
 ports:
   - name: management
     port: 8080
   - name: http
     port: 80
 selector:
   app: gateway
 sessionAffinity: None
 type: ClusterIP

3. Configure Prometheus roles

ClusterRole

First, change the namespace as needed. Note: possibly this clusterRole needs to be a little tighter than it currently is.

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
 labels:
   app.kubernetes.io/component: controller
   app.kubernetes.io/name: prometheus
 name: prometheus
 namespace: prometheus
rules:
 - apiGroups:
     - apiextensions.k8s.io
   resources:
     - customresourcedefinitions
   verbs:
     - create
 - apiGroups:
     - apiextensions.k8s.io
   resourceNames:
     - alertmanagers.monitoring.coreos.com
     - podmonitors.monitoring.coreos.com
     - prometheuses.monitoring.coreos.com
     - prometheusrules.monitoring.coreos.com
     - servicemonitors.monitoring.coreos.com
     - thanosrulers.monitoring.coreos.com
   resources:
     - customresourcedefinitions
   verbs:
     - get
     - update
 - apiGroups:
     - monitoring.coreos.com
   resources:
     - alertmanagers
     - alertmanagers/finalizers
     - prometheuses
     - prometheuses/finalizers
     - thanosrulers
     - thanosrulers/finalizers
     - servicemonitors
     - podmonitors
     - prometheusrules
   verbs:
     - '*'
 - apiGroups:
     - apps
   resources:
     - statefulsets
   verbs:
     - '*'
 - apiGroups:
     - ""
   resources:
     - configmaps
     - secrets
   verbs:
     - '*'
 - apiGroups:
     - ""
   resources:
     - pods
   verbs:
     - get
     - list
     - watch
 - apiGroups:
     - ""
   resources:
     - services
     - services/finalizers
     - endpoints
   verbs:
     - "*"
 - apiGroups:
     - ""
   resources:
     - nodes
   verbs:
     - list
     - watch
 - apiGroups:
     - ""
   resources:
     - namespaces
   verbs:
     - get
     - list
     - watch
 - apiGroups:
     - extensions
   resources:
     - ingresses
   verbs: ["get", "list", "watch"]
 - nonResourceURLs: ["/metrics"]
   verbs: ["get"]

ClusterRoleBinding

Again, change the namespace as needed.

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
 labels:
   app.kubernetes.io/component: controller
   app.kubernetes.io/name: prometheus
 name: prometheus
 namespace: prometheus
roleRef:
 apiGroup: rbac.authorization.k8s.io
 kind: ClusterRole
 name: prometheus
subjects:
 - kind: ServiceAccount
   name: default
   namespace: prometheus

ServiceAccount

Once more, change the namespace as needed. DO NOT change the name unless you change the ClusterRoleBinding subjects.name as well.

apiVersion: v1
kind: ServiceAccount
metadata:
 name: default
 namespace: prometheus

Apply

First, apply the ServiceAccount, ClusterRoleBinding, ClusterRole and Services to your K8s cluster. After updating the Prometheus configMap, redeploy Prometheus to make sure that the new configMap is activated/loaded.

Results in Prometheus

Go to the Prometheus GUI and navigate to Status -> Targets. You’ll see that now all the pod endpoints ‘magically’ pop up at the kubernetes-services-endpoints heading. Any future prometheus.io related annotation changes in k8s Services will immediately come into effect after applying them!

prometheus GUI overview

Grafana Longhorn dashboard

I used a generic Grafana Longhorn dashboard, which you can find here for yourself. Thanks to the auto-discovery, the Grafana Longhorn dashboard now correctly shows three nodes and seven volumes, which is exactly correct!

Grafana Longhorn dashboard

Conclusion

After running through all the steps in this blog post, you basically never have to look at your Prometheus configuration again. With auto-discovery of Kubernetes endpoint services, adding and removing Prometheus scrapes for your applications has now become almost as simple as unlocking your cell phone!

I hope this blog post has helped you out! If you have any questions, reach out to me. Or, if you’d like professional advice and services, see how we can help you out with Kubernetes!