autoscaler VS metrics-server

We use Cluster Autoscaler to automatically adjust the number of nodes (cluster size) based on your actual usage to ensure efficiency. Additionally, we deploy Vertical and Horizontal Pod Autoscalers to scale your applications' resources as their needs change automatically.

> * Hetzner: cheap, good service, the finest pets in the world, no cattle

You can absolutely do cattle with Hetzner. They support imaging and immutable infrastructure. They don't have a native auto scaling equivalent, but if you're using Kubernetes, they have a cluster autoscaler: https://github.com/kubernetes/autoscaler/blob/master/cluster...

Here we take the VPA as a starting point to analyze the design and implementation principles of the VPA in Autoscaler. The source code for this article is based on Autoscaler HEAD fbe25e1.

Autoscaling over EKS can be accomplished using either the cluster-autoscaler project or Karpenter. If you want to use Spot instances, consider using Karpenter, as it has better integrations with AWS for optimizing spot pricing and availability, minimizing interruptions, and falling back to on-demand nodes if no spot instances are available.

Autoscaling is already provided on OVH, but we don't use it for now. Autoscaler has to be manually installed on the AWS/EKS cluster.

do you mean this: https://github.com/kubernetes/autoscaler/blob/master/vertical-pod-autoscaler/pkg/recommender/README.md

Read more about this scaler in detail here!

We have a default node group of Linux hosts, but there's a secondary nodegroup of Windows hosts that is typically scaled down to 0. When a team's build runs, a pod is scheduled based on their definition. Cluster-autoscaler will check the nodeSelector and automatically spin up a node from that nodegroup if necessary.

I am running a Kubernetes cluster(AWS EKS one) with Autoscaler pod So that Cluster will autoscale according to the resource request within the cluster.

The last one is mostly an observability stack with Prometheus, Metric server, and Prometheus adapter to have excellent insights into what is happening on the cluster. You can reuse the same stack for autoscaling by repurposing all the data collected for monitoring.

and the Metrics Server.

Metrics-server is installed by default on OVH, and has to be installed manually on AWS/EKS cluster.

I have also installed metrics-server (though not sure whether that was required or not) using the following statement:kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.3.6/components.yaml

For #2: There are MANY solutions but the simplest and easiest is https://github.com/kubernetes-sigs/metrics-server and then you can use kubectl top to view pods resource usage. If you want fancy graphs, long retention, alerting, analysis, etc. of resource metrics.. then you need to use something like new relic, data dog, or something open source but much more complex like prometheus/thanos/grafana.. or a managed SaaS version of those open source tools... also some k8s platforms like AWS, Spot.io, GKE, OpenShift, may have this stuff built in or turnkey

It's an autoscaler with a metrics server (so I don't need to install 2 different tools).

Sure, here's an example of how to configure the Kubernetes Metrics Server along with the Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) configurations we provided earlier. The Metrics Server is a Kubernetes add-on that provides resource utilization metrics for pods and nodes, which are used by the HPA and VPA to determine when and how to scale an application. First, you'll need to install the Metrics Server into your Kubernetes cluster. You can do this by running the following command: kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml Once the Metrics Server is installed, you can configure your HPA and VPA to use it for metrics by adding the following annotation to your deployment: apiVersion: apps/v1 kind: Deployment metadata: name: my-app annotations: autoscaling.alpha.kubernetes.io/metrics-provider: "metrics-server" With this annotation in place, the HPA and VPA will use the Metrics Server to obtain CPU and memory utilization metrics for your pods and nodes. Here's an updated example of the HPA configuration we provided earlier, with the addition of the Metrics Server configuration: apiVersion: autoscaling/v2beta2 kind: HorizontalPodAutoscaler metadata: name: my-app-hpa spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: my-app minReplicas: 1 maxReplicas: 10 metrics: - type: Resource resource: name: cpu targetAverageUtilization: 50 - type: Resource resource: name: memory targetAverageUtilization: 80 In this example, we've added a second metric to the HPA configuration that targets memory utilization at 80%. Here's an updated example of the VPA configuration we provided earlier, with the addition of the Metrics Server configuration: apiVersion: autoscaling.k8s.io/v1 kind: VerticalPodAutoscaler metadata: name: my-app-vpa spec: targetRef: apiVersion: apps/v1 kind: Deployment name: my-app updatePolicy: updateMode: "Off" resourcePolicy: containerPolicies: - containerName: "*" minAllowed: cpu: 50m memory: 256Mi maxAllowed: cpu: 500m memory: 1Gi metrics: - type: Resource resource: name: cpu target: type: Utilization averageUtilization: 50 - type: Resource resource: name: memory target: type: Utilization averageUtilization: 80 In this example, we've added two metrics to the VPA configuration that target CPU and memory utilization, with target average utilization of 50% and 80% respectively. I hope this helps you configure the Metrics Server, HPA, and VPA for your application in Kubernetes!

Id go for k3s then install metrics-server, then you can deploy some hpa’s

# Create EKS Cluster with version 1.23 eksctl create cluster -f eks-cluster.yaml # Output like below shows cluster has been successfully created 2022-12-30 16:26:46 [ℹ] kubectl command should work with "/home/ec2-user/.kube/config", try 'kubectl get nodes' 2022-12-30 16:26:46 [✔] EKS cluster "ca-demo" in "us-west-2" region is ready # Deploy the Metric server kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml # Output of the above command looks something like below - serviceaccount/metrics-server created clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created clusterrole.rbac.authorization.k8s.io/system:metrics-server created rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created service/metrics-server created deployment.apps/metrics-server created apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created

ubuntu@korifi:~$ kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.6.2/components.yaml serviceaccount/metrics-server created clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created clusterrole.rbac.authorization.k8s.io/system:metrics-server created rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created service/metrics-server created deployment.apps/metrics-server created apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created ubuntu@korifi:~$ kubectl get po,svc -A NAMESPACE NAME READY STATUS RESTARTS AGE cert-manager pod/cert-manager-74d949c895-w6gzm 1/1 Running 0 13m cert-manager pod/cert-manager-cainjector-d9bc5979d-jhr9m 1/1 Running 0 13m cert-manager pod/cert-manager-webhook-84b7ddd796-xw878 1/1 Running 0 13m kpack pod/kpack-controller-84cbbcdff6-nnhdn 1/1 Running 0 9m40s kpack pod/kpack-webhook-56c6b59c4-9zvlb 1/1 Running 0 9m40s kube-system pod/coredns-565d847f94-kst2l 1/1 Running 0 31m kube-system pod/coredns-565d847f94-rv8pn 1/1 Running 0 31m kube-system pod/etcd-kind-control-plane 1/1 Running 0 32m kube-system pod/kindnet-275pd 1/1 Running 0 31m kube-system pod/kube-apiserver-kind-control-plane 1/1 Running 0 32m kube-system pod/kube-controller-manager-kind-control-plane 1/1 Running 0 32m kube-system pod/kube-proxy-qw9fj 1/1 Running 0 31m kube-system pod/kube-scheduler-kind-control-plane 1/1 Running 0 32m kube-system pod/metrics-server-8ff8f88c6-69t9z 0/1 Running 0 4m21s local-path-storage pod/local-path-provisioner-684f458cdd-f6zqf 1/1 Running 0 31m metallb-system pod/controller-84d6d4db45-bph5x 1/1 Running 0 29m metallb-system pod/speaker-pcl4p 1/1 Running 0 29m projectcontour pod/contour-7b9b9cdfd6-h5jzg 1/1 Running 0 6m43s projectcontour pod/contour-7b9b9cdfd6-nhbq2 1/1 Running 0 6m43s projectcontour pod/contour-certgen-v1.23.2-hxh7k 0/1 Completed 0 6m43s projectcontour pod/envoy-v4xk9 2/2 Running 0 6m43s servicebinding-system pod/servicebinding-controller-manager-85f7498cf-xd7jc 2/2 Running 0 115s NAMESPACE NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE cert-manager service/cert-manager ClusterIP 10.96.153.49 9402/TCP 13m cert-manager service/cert-manager-webhook ClusterIP 10.96.102.82 443/TCP 13m default service/kubernetes ClusterIP 10.96.0.1 443/TCP 32m kpack service/kpack-webhook ClusterIP 10.96.227.201 443/TCP 9m40s kube-system service/kube-dns ClusterIP 10.96.0.10 53/UDP,53/TCP,9153/TCP 32m kube-system service/metrics-server ClusterIP 10.96.204.62 443/TCP 4m21s metallb-system service/webhook-service ClusterIP 10.96.186.139 443/TCP 29m projectcontour service/contour ClusterIP 10.96.138.58 8001/TCP 6m43s projectcontour service/envoy LoadBalancer 10.96.126.44 172.18.255.200 80:30632/TCP,443:30730/TCP 6m43s servicebinding-system service/servicebinding-controller-manager-metrics-service ClusterIP 10.96.147.189 8443/TCP 115s servicebinding-system service/servicebinding-webhook-service ClusterIP 10.96.14.224 443/TCP 115s