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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
You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:
To check the version, enterkubectl 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 Deployments in your cluster in the kube-system namespace:
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:
NAME READY UP-TO-DATE AVAILABLE AGE
...
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
Deployment/<your-deployment-name>
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 labelk8s-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
metadata:
name: dns-autoscaler
namespace: kube-system
labels:
k8s-app: dns-autoscaler
spec:
selector:
matchLabels:
k8s-app: dns-autoscaler
template:
metadata:
labels:
k8s-app: dns-autoscaler
spec:
containers:
- name: autoscaler
image: k8s.gcr.io/cluster-proportional-autoscaler-amd64:1.6.0
resources:
requests:
cpu: 20m
memory: 10Mi
command:
- /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 ConfigMap 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.apps/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:
/etc/kubernetes/addons/dns-horizontal-autoscaler/dns-horizontal-autoscaler.yaml
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.
What's next
- Read about Guaranteed Scheduling For Critical Add-On Pods.
- Learn more about the implementation of cluster-proportional-autoscaler.