autoscaler VS kube-state-metrics

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.

git clone https://github.com/kubernetes/kube-state-metrics.git

https://github.com/kubernetes/kube-state-metrics/blob/main/docs/pod-metrics.md According to this github repo completion is responsible of termination date if I correctly understood .

kube-state-metrics

Those are entirely different types of data. You can get that from something like kube-state-metrics

I've never had a cluster of that size, so take it with a grain of salt - but maybe you could try purpose-based sharding? KSM has allowlist and denylist config flags, for configuring which metrics it exposes https://github.com/kubernetes/kube-state-metrics/blob/main/docs/cli-arguments.md

Kubernetes itself will not notify you, the way I've seen people do this, is to use something like kube-state-metrics or node_exporter, export that to Prometheus (or preferrably VictoriaMetrics because Prometheus is terrible IMO), and then setup alarms on that with alertmanager or equivalent, or just look at dashboards regularly with Grafana. Realistically I recommend only setting alerts on disk usage and application/database latency. CPU and memory utilization isn't a great metric to alert on a lot of the time.

Another tip that you could consider spelling out a little more, is to monitor the number of resources created by Kind. This is somewhat mentioned for jobs and services, but any Kind of which thousands of resources are created will put stress on the control-plane. The total number of resources per namespace/cluster can be monitored with kube-state-metrics. KSM does not emit metrics of resources created from CRDs. These metrics can be implemented with KSM's custom resource state metrics: https://github.com/kubernetes/kube-state-metrics/blob/main/docs/customresourcestate-metrics.md

We then have various other Metrics called Kubernetes Workload Metrics. These are the dashboards with names that start with “Kubernetes / Compute Resources / Workload”. These dashboards are specific to the services you are running. They take into account the Kubernetes Workloads in your various namespaces, using kube-state-metrics. For a closer look, check out otel_demo_app_k8s_dashboard.tf.

The first step to optimizing costs is gaining visibility into your costs using tools. Kubernetes provides a Metrics Server and kube-state-metrics that can give you the overall picture of resource utilization by your cluster. There are more tools that provide more granular breakdowns and provide dashboards with business metrics, infra cost, and alerting functionalities. Here are some strategies to optimize your resource utilization and cloud bills on k8s.