Using Metrics Provider to stream metrics

Metrics Provider streams metrics of Managed Service for Kubernetes cluster objects to monitoring systems and autoscaling systems.

In this article, you will learn how to set up transfers of external metrics to Horizontal Pod Autoscaler using Metrics Provider.

To set up the transfer of metrics:

1. Set up the runtime environment.
2. Install Metrics Provider and the runtime environment.
3. Test Metrics Provider.

If you no longer need the resources you created, delete them.

Required paid resourcesRequired paid resources

The support cost includes:

• Fee for the Managed Service for Kubernetes cluster: using the master and outgoing traffic (see Managed Service for Kubernetes pricing).
• Cluster nodes (VM) fee: using computing resources, operating system, and storage (see Compute Cloud pricing).
• Fee for a public IP address assigned to cluster nodes (see Virtual Private Cloud pricing).

Getting startedGetting started

1. If you do not have the Yandex Cloud CLI yet, install and initialize it.

   The folder specified when creating the CLI profile is used by default. To change the default folder, use the yc config set folder-id <folder_ID> command. You can specify a different folder using the --folder-name or --folder-id parameter.

2. Create security groups for the Managed Service for Kubernetes cluster and its node groups.

   Warning

   The configuration of security groups determines the performance and availability of the cluster and the services and applications running in it.

3. Create a Managed Service for Kubernetes cluster and a node group in any suitable configuration. When creating them, specify the security groups prepared earlier.

4. Install kubect and configure it to work with the new cluster.

Set up the runtime environmentSet up the runtime environment

To test Metrics Provider, the following will be created: the nginx test app and Horizontal Pod Autoscaler, to which CPU utilization metrics will be provided by Metrics Provider.

1. Create the app.yaml file with the nginx app manifest:

   app.yaml

   ---
   ### Deployment
   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: nginx
     namespace: kube-system
     labels:
       app: nginx
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: nginx
     template:
       metadata:
         name: nginx
         labels:
           app: nginx
       spec:
         containers:
           - name: nginx
             image: registry.k8s.io/hpa-example
             resources:
               requests:
                 memory: "256Mi"
                 cpu: "500m"
               limits:
                 memory: "500Mi"
                 cpu: "1"
   ---
   ### Service
   apiVersion: v1
   kind: Service
   metadata:
     name: nginx
     namespace: kube-system
   spec:
     selector:
       app: nginx
     ports:
       - protocol: TCP
         port: 80
         targetPort: 80
     type: LoadBalancer
   

2. Create the hpa.yaml file with the Horizontal Pod Autoscaler manifest for test-hpa:

   apiVersion: autoscaling/v2beta2
   kind: HorizontalPodAutoscaler
   metadata:
     name: test-hpa
     namespace: kube-system
   spec:
     maxReplicas: 2
     scaleTargetRef:
       apiVersion: apps/v1
       kind: Deployment
       name: nginx
     metrics:
       - type: External
         external:
           metric:
             name: cpu_usage
             selector:
               matchLabels:
                 service: "compute"
                 resource_id: "<node_name>"
                 resource_type: "vm"
           target:
             type: Value
             value: "20"
   

   You can get the name of the node where Metrics Provider and the runtime environment will be deployed with a list of cluster nodes:

   kubectl get nodes
   

Install Metrics Provider and the runtime environmentInstall Metrics Provider and the runtime environment

1. Follow the instructions to install Metrics Provider.

2. Create a test application and Horizontal Pod Autoscaler:

   kubectl apply -f app.yaml && \
   kubectl apply -f hpa.yaml
   

3. Make sure the app pods have entered the Running state:

   kubectl get pods -n kube-system | grep nginx && \
   kubectl get pods -n kube-system | grep metrics
   

   Result:

   nginx-6c********-dbfrn                      1/1     Running   0          2d22h
   nginx-6c********-gckhp                      1/1     Running   0          2d22h
   metrics-server-v0.3.1-6b********-f7dv6      2/2     Running   4          7d3h
   

Test Metrics ProviderTest Metrics Provider

Make sure that Horizontal Pod Autoscaler gets metrics from Metrics Provider and uses them to calculate the number of the nginx app pods:

kubectl -n kube-system describe hpa test-hpa

In the expected command output, the AbleToScale and ScalingActive conditions should be True:

Name:                          test-hpa
Namespace:                     kube-system
...
Min replicas:                  1
Max replicas:                  2
Deployment pods:               2 current / 2 desired
Conditions:
  Type            Status  Reason            Message
  ----            ------  ------            -------
  AbleToScale     True    ReadyForNewScale  recommended size matches current size
  ScalingActive   True    ValidMetricFound  the HPA was able to successfully calculate a replica count from external metric cpu_usage(&LabelSelector{MatchLabels:map[string]string{resource_id: <node_name>,resource_type: vm,service: compute,},MatchExpressions:[]LabelSelectorRequirement{},})
Events:           <none>

Delete the resources you createdDelete the resources you created

Delete the resources you no longer need to avoid paying for them:

1. Delete the Managed Service for Kubernetes cluster.
2. Delete the cluster's public static IP address if you had reserved one.