prometheus-operator VS kube-prometheus

The project repository for Prometheus-operator can be found here, The repo defines the CRDs and the controller. You can follow this documentation for the installation. which will require the creation of metrics exporters, node exporters, scrape configurations, etc.

Personally I use kubernetes, k3s is kind of lightweight, with the Prometheus operator.

https://k3s.io/

https://prometheus-operator.dev/

Kubernetes is not for everyone and is far from perfect but you already use Docker and you seem to seek many features offered by Kubernetes.

I see that the operator is a community-run project. Does anybody have any experience (positive or negative) on running the operator itself? I wonder if it is more for multi-tenant Prometheus. For single tenant Prometheus collection, I guess the big gain is abstracting scrape config into ServiceMonitor and PodMonitor resources? Is there anything else that this makes much better?

But in all honesty if you’re on k8s you’re probably best served by the Prometheus operator. It’ll give you all that and more, easily.

Try some monitoring.

It’s a common pattern [1] how else can users override the child objects you’re controller creates?

1 https://github.com/prometheus-operator/prometheus-operator/b...

The Prometheus operator is this one https://github.com/prometheus-operator/prometheus-operator

At a minimum, you want to look at your metrics using the Prometheus Operator. You can write alerts for resource requests.

Prometheus Operator is an independent project from the Prometheus project. I know, it can lead to confusion. In the official README you can find short comparison. Basically, Prometheus Operator does what an operator should do - provides Kubernetes native deployment and management of Prometheus and related monitoring components like Grafana or Alert Manager.

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.

kustomize Kube Prometheus

On the other hand, the Kube-prometheus project provides documentation and scripts to operate end-to-end Kubernetes cluster monitoring using the Prometheus Operator, making easier the process of monitoring the Kubernetes cluster.

For our load testing we’ve deployed Temporal on Kubernetes, and we’re using MySQL for the persistence backend. The MySQL instance has 4 CPU cores and 32GB RAM, and each Temporal service (Frontend, History, Matching, and Worker) has 2 pods, with requests for 1 CPU core and 1GB RAM as a starting point. We’re not setting CPU limits for our pods—see our upcoming Temporal on Kubernetes post for more details on why. For monitoring we’ll use Prometheus and Grafana, installed via the kube-prometheus stack, giving us some useful Kubernetes metrics.

The 2 most common approaches I have seen are kube-prometheus-stack and kube-prometheus..

- I'm missing a lot of the Grafana dashboards that are provisioned during the deployment, not sure why as it has worked before, and wanted to add them after install... I believe it's different ConfigMaps like the one in kube-prometheus but I was wondering if there's a way to force provisioning them all again at once (multiple k8s, node_exporter, vm, etc)?

Check out the kube Prometheus project -- https://github.com/prometheus-operator/kube-prometheus It's a bit heavy, but the included recording rules and dashboards give you a great start at understanding your cluster.

The actual link to the prometheus/grafana bundle: https://github.com/prometheus-operator/kube-prometheus

Here’s a list of what’s installed: https://github.com/prometheus-operator/kube-prometheus/tree/main/manifests