kube-state-metrics VS kubetail

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.

There is an existing project named kubetail, which is quite popular 3.2K starts https://github.com/johanhaleby/kubetail

Kubetail

Thanos - Highly available Prometheus setup with long term storage capabilities. CNCF Sandbox project. https://thanos.io Prometheus - The Prometheus monitoring system and time series database. Grafana - The tool for beautiful monitoring and metric analytics & dashboards for Graphite, InfluxDB & Prometheus & More Kubetail - Bash script to tail Kubernetes logs from multiple pods at the same time Searchlight - Alerts for Kubernetes linkerd2 Monitoring Mixin for Grafana - Grafana dashboards for linkerd2 monitoring and can work in standalone (default) or in multi cluster setup kuberhaus - Kubernetes resource dashboard with node/pod layout and resource requests Kubernetes Job/CronJob Notifier - This tool sends an alert to slack whenever there is a Kubernetes cronJob/Job failure/success Argus - This tool monitors changes in the filesystem on specified paths

Kubetail is really nice: https://github.com/johanhaleby/kubetail.

Is this the gui version of kubetail?