Prometheus relatived

hpa-sample-servicemonitor.yaml

kind: ServiceMonitor
apiVersion: monitoring.coreos.com/v1
metadata:
  name: hpa-app
  namespace: kube-public
  labels:
    app: hpa-app
spec:
  namespaceSelector:
    matchNames:
    - kube-public
  selector:
    matchLabels:
      app: hpa-app
  endpoints: 
  - port: http

hpa-sample.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: hpa-app
  namespace: kube-public
  labels:
    app: hpa-app
spec:
  replicas: 1
  selector:
    matchLabels:
      app: hpa-app
  template:
    metadata:
      labels:
        app: hpa-app
    spec:
      containers:
      - image: luxas/autoscale-demo:v0.1.2
        name: metrics-provider
        ports:
        - name: http
          containerPort: 8080
---
apiVersion: v1
kind: Service
metadata:
  name: hpa-app
  namespace: kube-public
  labels:
    app: hpa-app
spec:
  selector:
    app: hpa-app
  ports:
    - protocol: TCP
      port: 80
      targetPort: 8080
      name: http

hpa.yaml

kind: HorizontalPodAutoscaler
apiVersion: autoscaling/v2beta1
metadata:
  name: hpa-app
  namespace: kube-public
spec:
  scaleTargetRef:
    # point the HPA at the sample application
    # you created above
    apiVersion: apps/v1
    kind: Deployment
    name: hpa-app
  # autoscale between 1 and 10 replicas
  minReplicas: 1
  maxReplicas: 10
  metrics:
  # use a "Pods" metric, which takes the average of the
  # given metric across all pods controlled by the autoscaling target
  - type: Pods
    pods:
      # use the metric that you used above: pods/http_requests
      metricName: http_requests
      # target 500 milli-requests per second,
      # which is 1 request every two seconds
      targetAverageValue: 500m