This repository collects Kubernetes manifests, Grafana dashboards, and Prometheus rules combined with documentation and scripts to provide single-command deployments of end-to-end Kubernetes cluster monitoring with Prometheus (Operator).
First, you need a running Kubernetes cluster. If you don't have one, we recommend you create one with Tectonic Installer. Despite the name, Tectonic Installer gives you also the choice to create a barebones Kubernetes cluster, without CoreOS' Tectonic technology. Otherwise, you can simply make use of bootkube or minikube for local testing. Some sample contents of this repository are adapted to work with a multi-node setup using bootkube.
The manifests here use the Prometheus Operator, which manages Prometheus servers and their configuration in a cluster. With a single command we can install
- The Operator itself
- The Prometheus node_exporter
- kube-state-metrics
- The Prometheus specification based on which the Operator deploys a Prometheus setup
- A Prometheus configuration covering monitoring of all Kubernetes core components and exporters
- A default set of alerting rules on the cluster components' health
- A Grafana instance serving dashboards on cluster metrics
- A three node highly available Alertmanager cluster
Simply run:
export KUBECONFIG=<path> # defaults to "~/.kube/config"
cd contrib/kube-prometheus/
hack/cluster-monitoring/deploy
After all pods are ready, you can reach:
- Prometheus UI on node port
30900
- Alertmanager UI on node port
30903
- Grafana on node port
30902
To tear it all down again, run:
hack/cluster-monitoring/teardown
The example manifests in manifests/examples/example-app
deploy a fake service exposing Prometheus metrics. They additionally define a new Prometheus
server and a ServiceMonitor
,
which specifies how the example service should be monitored.
The Prometheus Operator will deploy and configure the desired Prometheus instance and continuously
manage its life cycle.
hack/example-service-monitoring/deploy
After all pods are ready you can reach the Prometheus server on node port 30100
and observe
how it monitors the service as specified. Same as before, this Prometheus server automatically
discovers the Alertmanager cluster deployed in the Monitoring Kubernetes
section.
Teardown:
hack/example-service-monitoring/teardown
The provided manifests deploy a Grafana instance serving dashboards provided via ConfigMaps. Said ConfigMaps are generated from Python scripts in assets/grafana, that all have the extension .dashboard.py as they are loaded by the grafanalib Grafana dashboard generator. Bear in mind that we are for now using a fork of grafanalib as we needed to make extensive changes to it, in order to be able to generate our dashboards. We are hoping to be able to consolidate our version with the original.
As such, in order to make changes to the dashboard bundle, you need to change the *.dashboard.py
files in assets/grafana, eventually add your own, and then run make generate
in the
kube-prometheus root directory.
To read more in depth about developing dashboards, read the Developing Prometheus Rules and Grafana Dashboards documentation.
Currently, Grafana does not support serving dashboards from static files. Instead, the grafana-watcher
sidecar container aims to emulate the behavior, by keeping the Grafana database always in sync
with the provided ConfigMap. Hence, the Grafana pod is effectively stateless.
This allows managing dashboards via git
etc. and easily deploying them via CD pipelines.
In the future, a separate Grafana operator will support gathering dashboards from multiple ConfigMaps based on label selection.
WARNING: If you deploy multiple Grafana instances for HA, you must use session affinity. Otherwise if pods restart the prometheus datasource ID can get out of sync between the pods, breaking the UI
- Grafana Operator that dynamically discovers and deploys dashboards from ConfigMaps
- KPM/Helm packages to easily provide production-ready cluster-monitoring setup (essentially contents of
hack/cluster-monitoring
) - Add meta-monitoring to default cluster monitoring setup
- Build out the provided dashboards and alerts for cluster monitoring to have full coverage of all system aspects
Discovery of API servers and kubelets works the same across all clusters. Depending on a cluster's setup several other core components, such as etcd or the scheduler, may be deployed in different ways. The easiest integration point is for the cluster operator to provide headless services of all those components to provide a common interface of discovering them. With that setup they will automatically be discovered by the provided Prometheus configuration.
For the kube-scheduler
and kube-controller-manager
there are headless
services prepared, simply add them to your running cluster:
kubectl -n kube-system create -f manifests/k8s/
Hint: if you use this for a cluster not created with bootkube, make sure you populate an endpoints object with the address to your
kube-scheduler
andkube-controller-manager
, or adapt the label selectors to match your setup.
Aside from Kubernetes specific components, etcd is an important part of a working cluster, but is typically deployed outside of it. This monitoring setup assumes that it is made visible from within the cluster through a headless service as well.
Note that minikube hides some components like etcd so to see the extend of this setup we recommend setting up a local cluster using bootkube.
An example for bootkube's multi-node vagrant setup is here.
Hint: this is merely an example for a local setup. The addresses will have to be adapted for a setup, that is not a single etcd bootkube created cluster.
With that setup the headless services provide endpoint lists consumed by Prometheus to discover the endpoints as targets:
$ kubectl get endpoints --all-namespaces
NAMESPACE NAME ENDPOINTS AGE
default kubernetes 172.17.4.101:443 2h
kube-system kube-controller-manager-prometheus-discovery 10.2.30.2:10252 1h
kube-system kube-scheduler-prometheus-discovery 10.2.30.4:10251 1h
monitoring etcd-k8s 172.17.4.51:2379 1h