kube-state-metrics VS kaniko

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.

If all you need to do is build container, you can use https://github.com/GoogleContainerTools/kaniko

Kaniko for building the container images

kaniko

You should maybe look into Kaniko or use some other build tool

If you are using the docker socket just for building container images, you might want to look into kaniko. It doesn't use docker to build images. If you use the socket also for starting containers (we are actually doing that in our CI pipelines), you could think about limiting the pods Kubernetes schedules on a node (you can change the default of 110 using the kubelet config file).

Check out Kaniko for building containers https://github.com/GoogleContainerTools/kaniko . Only issue is it doesnt support windows containers.

It took less than 5 minutes to install. It quickly analysed the repo and identified easy ways to make the project more secure. Priya Wadhwa, Kaniko

I'd suggest to take a look at the Kaniko project, combined with custom container images in Lambda functions.

kaniko is a tool that allows you to build container images inside Kubernetes without the need for the Docker daemon. Effectively, it allows you to build Docker images without docker build.

Kubernetes prefers to pull containers from registries. You may be able to work around it by specifying a local image in your Kube manifest. Both https://github.com/GoogleContainerTools/kaniko and/ or https://www.devspace.sh/ may help.