helm-charts VS k8s-prometheus-adapter

Prometheus can be deployed using the Prometheus Helm Chart. This helm chart contains a lot of features such as the already mentioned Push Gateway, Alert Manager and so on. For simplicity reasons of this tutorial I will not show all the Helm chart configuration but you can see a real example used by me here.

Building upon Bartłomiej Płotka's insightful blog on Prometheus and its passthrough agent mode, this post dives into implementing multi-cluster Prometheus support. Notably, the official inclusion of support in the widely-used kube-prometheus-stack came with the release in July 2023, making it easier to extend Prometheus monitoring across clusters.

The first thing you'll need, of course, is at least one backend to store metrics. So install Prometheus now:

For the request following, something like jeager https://www.jaegertracing.io/, because you are talking more about tracing than necessarily logging. For just monitoring, https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack would be the starting point, then it depends. Nginx gives metrics out of the box, then you can pull in the dashboard like https://grafana.com/grafana/dashboards/14314-kubernetes-nginx-ingress-controller-nextgen-devops-nirvana/ , or full metal with something like service mesh monitoring which would provably fulfil most of the requirements

kube-prometheus-stack is a Helm chart that contains several components to monitor the Kubernetes cluster, along with Grafana dashboards Grafana Dashboards to visualize the data. This option will be used in this article.

This one I highly recommend: https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack

We use kube-prometheus-stack for metrics and have added the K8s views dashboards from grafana-dashboards-kubernetes. You should check out the k8s-views-global dashboard. I believe it's just what you are looking for.

You should take a look at "kube-prometheus-stack". It not only includes prometheus, node-exporter and Grafana but also a ton of preconfigured alerts and dashboards. Will save you a lot of work!

Since their are different ways to install what exactly did you install? Vanilla charts , stack, operator? https://github.com/prometheus-community/helm-charts/tree/main/charts

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.

I'm deploying kube-prometheus-stack along with prometheus-adapter in my monitoring stack for custom metrics.

I would like to see if anyone deployed prometheus-adapter and kube-prometheus-stack together for monitoring?

For us it is saturation of CPU and thread pool. It's implemented by exposing metrics of the thread pool to prometheus and turning that into a custom metric. (see) Looking at scaling based on job queue length next.

If you are using Prometheus or kube-prometheus-stack, you will need https://github.com/kubernetes-sigs/prometheus-adapter We are using it to scale our Pods based on number of messages in RabbitMQ queue. There also a walkthrough on https://github.com/kubernetes-sigs/prometheus-adapter/blob/master/docs/walkthrough.md

A prometheus-adapter installation.

Prometheus adapter to get custom/external metrics from Prometheus instance into Kubernetes API.

I never tested this but you have customized metrics API if the value % is available should work from my point of view Check this here https://github.com/kubernetes-sigs/prometheus-adapter

CPU and memory might not be the right metrics for your application to make scaling decisions. In such cases, you can use HPA (or VPA) with custom metrics as an alternative. To use custom metrics for autoscaling, you can use a custom metrics adapter instead of the Kubernetes Metrics Server. Popular custom metrics adapters are the Prometheus adapter and Kubernetes Event-Driven Autoscaler (KEDA).