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Autoscale the DNS Service in a Cluster

This page shows how to enable and configure autoscaling of the DNS service in your Kubernetes cluster.

Before you begin


To check the version, enter kubectl version.

  • This guide assumes your nodes use the AMD64 or Intel 64 CPU architecture.

  • Make sure Kubernetes DNS is enabled.

Determine whether DNS horizontal autoscaling is already enabled

List the DeploymentsAn API object that manages a replicated application. in your cluster in the kube-system namespaceAn abstraction used by Kubernetes to support multiple virtual clusters on the same physical cluster. :

kubectl get deployment --namespace=kube-system

The output is similar to this:

NAME                      READY   UP-TO-DATE   AVAILABLE   AGE
dns-autoscaler            1/1     1            1           ...

If you see “dns-autoscaler” in the output, DNS horizontal autoscaling is already enabled, and you can skip to Tuning autoscaling parameters.

Get the name of your DNS Deployment

List the DNS deployments in your cluster in the kube-system namespace:

kubectl get deployment -l k8s-app=kube-dns --namespace=kube-system

The output is similar to this:

coredns   2/2     2            2           ...

If you don’t see a Deployment for DNS services, you can also look for it by name:

kubectl get deployment --namespace=kube-system

and look for a deployment named coredns or kube-dns.

Your scale target is


where <your-deployment-name> is the name of your DNS Deployment. For example, if the name of your Deployment for DNS is coredns, your scale target is Deployment/coredns.

Note: CoreDNS is the default DNS service for Kubernetes. CoreDNS sets the label k8s-app=kube-dns so that it can work in clusters that originally used kube-dns.

Enable DNS horizontal autoscaling

In this section, you create a new Deployment. The Pods in the Deployment run a container based on the cluster-proportional-autoscaler-amd64 image.

Create a file named dns-horizontal-autoscaler.yaml with this content:

apiVersion: apps/v1
kind: Deployment
  name: dns-autoscaler
  namespace: kube-system
    k8s-app: dns-autoscaler
      k8s-app: dns-autoscaler
        k8s-app: dns-autoscaler
      - name: autoscaler
        image: k8s.gcr.io/cluster-proportional-autoscaler-amd64:1.6.0
            cpu: 20m
            memory: 10Mi
        - /cluster-proportional-autoscaler
        - --namespace=kube-system
        - --configmap=dns-autoscaler
        - --target=<SCALE_TARGET>
        # When cluster is using large nodes(with more cores), "coresPerReplica" should dominate.
        # If using small nodes, "nodesPerReplica" should dominate.
        - --default-params={"linear":{"coresPerReplica":256,"nodesPerReplica":16,"min":1}}
        - --logtostderr=true
        - --v=2

In the file, replace <SCALE_TARGET> with your scale target.

Go to the directory that contains your configuration file, and enter this command to create the Deployment:

kubectl apply -f dns-horizontal-autoscaler.yaml

The output of a successful command is:

deployment.apps/dns-autoscaler created

DNS horizontal autoscaling is now enabled.

Tune DNS autoscaling parameters

Verify that the dns-autoscaler ConfigMapAn API object used to store non-confidential data in key-value pairs. Can be consumed as environment variables, command-line arguments, or config files in a volume. exists:

kubectl get configmap --namespace=kube-system

The output is similar to this:

NAME                  DATA      AGE
dns-autoscaler        1         ...

Modify the data in the ConfigMap:

kubectl edit configmap dns-autoscaler --namespace=kube-system

Look for this line:

linear: '{"coresPerReplica":256,"min":1,"nodesPerReplica":16}'

Modify the fields according to your needs. The “min” field indicates the minimal number of DNS backends. The actual number of backends is calculated using this equation:

replicas = max( ceil( cores × 1/coresPerReplica ) , ceil( nodes × 1/nodesPerReplica ) )

Note that the values of both coresPerReplica and nodesPerReplica are floats.

The idea is that when a cluster is using nodes that have many cores, coresPerReplica dominates. When a cluster is using nodes that have fewer cores, nodesPerReplica dominates.

There are other supported scaling patterns. For details, see cluster-proportional-autoscaler.

Disable DNS horizontal autoscaling

There are a few options for tuning DNS horizontal autoscaling. Which option to use depends on different conditions.

Option 1: Scale down the dns-autoscaler deployment to 0 replicas

This option works for all situations. Enter this command:

kubectl scale deployment --replicas=0 dns-autoscaler --namespace=kube-system

The output is:

deployment.extensions/dns-autoscaler scaled

Verify that the replica count is zero:

kubectl get rs --namespace=kube-system

The output displays 0 in the DESIRED and CURRENT columns:

NAME                                 DESIRED   CURRENT   READY   AGE
dns-autoscaler-6b59789fc8            0         0         0       ...

Option 2: Delete the dns-autoscaler deployment

This option works if dns-autoscaler is under your own control, which means no one will re-create it:

kubectl delete deployment dns-autoscaler --namespace=kube-system

The output is:

deployment.apps "dns-autoscaler" deleted

Option 3: Delete the dns-autoscaler manifest file from the master node

This option works if dns-autoscaler is under control of the (deprecated) Addon Manager, and you have write access to the master node.

Sign in to the master node and delete the corresponding manifest file. The common path for this dns-autoscaler is:


After the manifest file is deleted, the Addon Manager will delete the dns-autoscaler Deployment.

Understanding how DNS horizontal autoscaling works

  • The cluster-proportional-autoscaler application is deployed separately from the DNS service.

  • An autoscaler Pod runs a client that polls the Kubernetes API server for the number of nodes and cores in the cluster.

  • A desired replica count is calculated and applied to the DNS backends based on the current schedulable nodes and cores and the given scaling parameters.

  • The scaling parameters and data points are provided via a ConfigMap to the autoscaler, and it refreshes its parameters table every poll interval to be up to date with the latest desired scaling parameters.

  • Changes to the scaling parameters are allowed without rebuilding or restarting the autoscaler Pod.

  • The autoscaler provides a controller interface to support two control patterns: linear and ladder.

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