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Oct 21, 2021


Build Status Slack Gitpod ready-to-code

Note that everything is experimental and may change significantly at any time.

This repository collects Kubernetes manifests, Grafana dashboards, and Prometheus rules combined with documentation and scripts to provide easy to operate end-to-end Kubernetes cluster monitoring with Prometheus using the Prometheus Operator.

The content of this project is written in jsonnet. This project could both be described as a package as well as a library.

Components included in this package:

This stack is meant for cluster monitoring, so it is pre-configured to collect metrics from all Kubernetes components. In addition to that it delivers a default set of dashboards and alerting rules. Many of the useful dashboards and alerts come from the kubernetes-mixin project, similar to this project it provides composable jsonnet as a library for users to customize to their needs.


If you are migrating from release-0.7 branch or earlier please read what changed and how to migrate in our guide.

Table of contents


You will need a Kubernetes cluster, that's it! By default it is assumed, that the kubelet uses token authentication and authorization, as otherwise Prometheus needs a client certificate, which gives it full access to the kubelet, rather than just the metrics. Token authentication and authorization allows more fine grained and easier access control.

This means the kubelet configuration must contain these flags:

  • --authentication-token-webhook=true This flag enables, that a ServiceAccount token can be used to authenticate against the kubelet(s). This can also be enabled by setting the kubelet configuration value authentication.webhook.enabled to true.
  • --authorization-mode=Webhook This flag enables, that the kubelet will perform an RBAC request with the API to determine, whether the requesting entity (Prometheus in this case) is allowed to access a resource, in specific for this project the /metrics endpoint. This can also be enabled by setting the kubelet configuration value authorization.mode to Webhook.

This stack provides resource metrics by deploying the Prometheus Adapter. This adapter is an Extension API Server and Kubernetes needs to be have this feature enabled, otherwise the adapter has no effect, but is still deployed.


To try out this stack, start minikube with the following command:

$ minikube delete && minikube start --kubernetes-version=v1.20.0 --memory=6g --bootstrapper=kubeadm --extra-config=kubelet.authentication-token-webhook=true --extra-config=kubelet.authorization-mode=Webhook --extra-config=scheduler.bind-address= --extra-config=controller-manager.bind-address=

The kube-prometheus stack includes a resource metrics API server, so the metrics-server addon is not necessary. Ensure the metrics-server addon is disabled on minikube:

$ minikube addons disable metrics-server


Kubernetes compatibility matrix

The following versions are supported and work as we test against these versions in their respective branches. But note that other versions might work!

kube-prometheus stack Kubernetes 1.18 Kubernetes 1.19 Kubernetes 1.20 Kubernetes 1.21 Kubernetes 1.22


Note: For versions before Kubernetes v1.21.z refer to the Kubernetes compatibility matrix in order to choose a compatible branch.

This project is intended to be used as a library (i.e. the intent is not for you to create your own modified copy of this repository).

Though for a quickstart a compiled version of the Kubernetes manifests generated with this library (specifically with example.jsonnet) is checked into this repository in order to try the content out quickly. To try out the stack un-customized run:

  • Create the monitoring stack using the config in the manifests directory:
# Create the namespace and CRDs, and then wait for them to be available before creating the remaining resources
kubectl apply --server-side -f manifests/setup
until kubectl get servicemonitors --all-namespaces ; do date; sleep 1; echo ""; done
kubectl apply -f manifests/

We create the namespace and CustomResourceDefinitions first to avoid race conditions when deploying the monitoring components. Alternatively, the resources in both folders can be applied with a single command kubectl apply --server-side -f manifests/setup -f manifests, but it may be necessary to run the command multiple times for all components to be created successfullly.

  • And to teardown the stack:
kubectl delete --ignore-not-found=true -f manifests/ -f manifests/setup

Access the dashboards

Prometheus, Grafana, and Alertmanager dashboards can be accessed quickly using kubectl port-forward after running the quickstart via the commands below. Kubernetes 1.10 or later is required.

Note: There are instructions on how to route to these pods behind an ingress controller in the Exposing Prometheus/Alermanager/Grafana via Ingress section.


$ kubectl --namespace monitoring port-forward svc/prometheus-k8s 9090

Then access via http://localhost:9090


$ kubectl --namespace monitoring port-forward svc/grafana 3000

Then access via http://localhost:3000 and use the default grafana user:password of admin:admin.

Alert Manager

$ kubectl --namespace monitoring port-forward svc/alertmanager-main 9093

Then access via http://localhost:9093

Customizing Kube-Prometheus

This section:

  • describes how to customize the kube-prometheus library via compiling the kube-prometheus manifests yourself (as an alternative to the Quickstart section).
  • still doesn't require you to make a copy of this entire repository, but rather only a copy of a few select files.


The content of this project consists of a set of jsonnet files making up a library to be consumed.

Install this library in your own project with jsonnet-bundler (the jsonnet package manager):

$ mkdir my-kube-prometheus; cd my-kube-prometheus
$ jb init  # Creates the initial/empty `jsonnetfile.json`
# Install the kube-prometheus dependency
$ jb install # Creates `vendor/` & `jsonnetfile.lock.json`, and fills in `jsonnetfile.json`

$ wget -O example.jsonnet
$ wget -O

jb can be installed with go install -a

An e.g. of how to install a given version of this library: jb install

In order to update the kube-prometheus dependency, simply use the jsonnet-bundler update functionality:

$ jb update


e.g. of how to compile the manifests: ./ example.jsonnet

before compiling, install gojsontoyaml tool with go install and jsonnet with go install

Here's example.jsonnet:

Note: some of the following components must be configured beforehand. See configuration and customization-examples.

local kp =
  (import 'kube-prometheus/main.libsonnet') +
  // Uncomment the following imports to enable its patches
  // (import 'kube-prometheus/addons/anti-affinity.libsonnet') +
  // (import 'kube-prometheus/addons/managed-cluster.libsonnet') +
  // (import 'kube-prometheus/addons/node-ports.libsonnet') +
  // (import 'kube-prometheus/addons/static-etcd.libsonnet') +
  // (import 'kube-prometheus/addons/custom-metrics.libsonnet') +
  // (import 'kube-prometheus/addons/external-metrics.libsonnet') +
    values+:: {
      common+: {
        namespace: 'monitoring',

{ 'setup/0namespace-namespace': kp.kubePrometheus.namespace } +
  ['setup/prometheus-operator-' + name]: kp.prometheusOperator[name]
  for name in std.filter((function(name) name != 'serviceMonitor' && name != 'prometheusRule'), std.objectFields(kp.prometheusOperator))
} +
// serviceMonitor and prometheusRule are separated so that they can be created after the CRDs are ready
{ 'prometheus-operator-serviceMonitor': kp.prometheusOperator.serviceMonitor } +
{ 'prometheus-operator-prometheusRule': kp.prometheusOperator.prometheusRule } +
{ 'kube-prometheus-prometheusRule': kp.kubePrometheus.prometheusRule } +
{ ['alertmanager-' + name]: kp.alertmanager[name] for name in std.objectFields(kp.alertmanager) } +
{ ['blackbox-exporter-' + name]: kp.blackboxExporter[name] for name in std.objectFields(kp.blackboxExporter) } +
{ ['grafana-' + name]: kp.grafana[name] for name in std.objectFields(kp.grafana) } +
{ ['kube-state-metrics-' + name]: kp.kubeStateMetrics[name] for name in std.objectFields(kp.kubeStateMetrics) } +
{ ['kubernetes-' + name]: kp.kubernetesControlPlane[name] for name in std.objectFields(kp.kubernetesControlPlane) }
{ ['node-exporter-' + name]: kp.nodeExporter[name] for name in std.objectFields(kp.nodeExporter) } +
{ ['prometheus-' + name]: kp.prometheus[name] for name in std.objectFields(kp.prometheus) } +
{ ['prometheus-adapter-' + name]: kp.prometheusAdapter[name] for name in std.objectFields(kp.prometheusAdapter) }

And here's the script (which uses vendor/ to render all manifests in a json structure of {filename: manifest-content}):

#!/usr/bin/env bash

# This script uses arg $1 (name of *.jsonnet file to use) to generate the manifests/*.yaml files.

set -e
set -x
# only exit with zero if all commands of the pipeline exit successfully
set -o pipefail

# Make sure to use project tooling

# Make sure to start with a clean 'manifests' dir
rm -rf manifests
mkdir -p manifests/setup

# Calling gojsontoyaml is optional, but we would like to generate yaml, not json
jsonnet -J vendor -m manifests "${1-example.jsonnet}" | xargs -I{} sh -c 'cat {} | gojsontoyaml > {}.yaml' -- {}

# Make sure to remove json files
find manifests -type f ! -name '*.yaml' -delete
rm -f kustomization

Note you need jsonnet (go get and gojsontoyaml (go get installed to run If you just want json output, not yaml, then you can skip the pipe and everything afterwards.

This script runs the jsonnet code, then reads each key of the generated json and uses that as the file name, and writes the value of that key to that file, and converts each json manifest to yaml.

Apply the kube-prometheus stack

The previous steps (compilation) has created a bunch of manifest files in the manifest/ folder. Now simply use kubectl to install Prometheus and Grafana as per your configuration:

# Update the namespace and CRDs, and then wait for them to be available before creating the remaining resources
$ kubectl apply --server-side -f manifests/setup
$ kubectl apply -f manifests/

Note that due to some CRD size we are using kubeclt server-side apply feature which is generally available since kubernetes 1.22. If you are using previous kubernetes versions this feature may not be available and you would need to use kubectl create instead.

Alternatively, the resources in both folders can be applied with a single command kubectl apply --server-side -Rf manifests, but it may be necessary to run the command multiple times for all components to be created successfullly.

Check the monitoring namespace (or the namespace you have specific in namespace: ) and make sure the pods are running. Prometheus and Grafana should be up and running soon.

Containerized Installing and Compiling

If you don't care to have jb nor jsonnet nor gojsontoyaml installed, then use container image. Do the following from this kube-prometheus directory:

$ docker run --rm -v $(pwd):$(pwd) --workdir $(pwd) jb update
$ docker run --rm -v $(pwd):$(pwd) --workdir $(pwd) ./ example.jsonnet

Update from upstream project

You may wish to fetch changes made on this project so they are available to you.

Update jb

jb may have been updated so it's a good idea to get the latest version of this binary:

$ go get -u

Update kube-prometheus

The command below will sync with upstream project:

$ jb update

Compile the manifests and apply

Once updated, just follow the instructions under "Compiling" and "Apply the kube-prometheus stack" to apply the changes to your cluster.


Jsonnet has the concept of hidden fields. These are fields, that are not going to be rendered in a result. This is used to configure the kube-prometheus components in jsonnet. In the example jsonnet code of the above Customizing Kube-Prometheus section, you can see an example of this, where the namespace is being configured to be monitoring. In order to not override the whole object, use the +:: construct of jsonnet, to merge objects, this way you can override individual settings, but retain all other settings and defaults.

The available fields and their default values can be seen in main.libsonnet. Note that many of the fields get their default values from variables, and for example the version numbers are imported from versions.json.

Configuration is mainly done in the values map. You can see this being used in the example.jsonnet to set the namespace to monitoring. This is done in the common field, which all other components take their default value from. See for example how Alertmanager is configured in main.libsonnet:

    alertmanager: {
      name: 'main',
      // Use the namespace specified under values.common by default.
      namespace: $.values.common.namespace,
      version: $.values.common.versions.alertmanager,
      image: $.values.common.images.alertmanager,
      mixin+: { ruleLabels: $.values.common.ruleLabels },

The grafana definition is located in a different project ( ), but needed configuration can be customized from the same top level values field. For example to allow anonymous access to grafana, add the following values section:

      grafana+:: {
        config: { //
          sections: {
            "auth.anonymous": {enabled: true},

Customization Examples

Jsonnet is a turing complete language, any logic can be reflected in it. It also has powerful merge functionalities, allowing sophisticated customizations of any kind simply by merging it into the object the library provides.

To get started, we provide several customization examples in the docs/customizations/ section.

Minikube Example

To use an easy to reproduce example, see minikube.jsonnet, which uses the minikube setup as demonstrated in Prerequisites. Because we would like easy access to our Prometheus, Alertmanager and Grafana UIs, minikube.jsonnet exposes the services as NodePort type services.

Continuous Delivery

Working examples of use with continuous delivery tools are found in examples/continuous-delivery.


See the general guidelines for getting support from the community.

Error retrieving kubelet metrics

Should the Prometheus /targets page show kubelet targets, but not able to successfully scrape the metrics, then most likely it is a problem with the authentication and authorization setup of the kubelets.

As described in the Prerequisites section, in order to retrieve metrics from the kubelet token authentication and authorization must be enabled. Some Kubernetes setup tools do not enable this by default.

Authentication problem

The Prometheus /targets page will show the kubelet job with the error 403 Unauthorized, when token authentication is not enabled. Ensure, that the --authentication-token-webhook=true flag is enabled on all kubelet configurations.

Authorization problem

The Prometheus /targets page will show the kubelet job with the error 401 Unauthorized, when token authorization is not enabled. Ensure that the --authorization-mode=Webhook flag is enabled on all kubelet configurations.

kube-state-metrics resource usage

In some environments, kube-state-metrics may need additional resources. One driver for more resource needs, is a high number of namespaces. There may be others.

kube-state-metrics resource allocation is managed by addon-resizer You can control it's parameters by setting variables in the config. They default to:

    kubeStateMetrics+:: {
      baseCPU: '100m',
      cpuPerNode: '2m',
      baseMemory: '150Mi',
      memoryPerNode: '30Mi',

Error retrieving kube-proxy metrics

By default, kubeadm will configure kube-proxy to listen on for metrics. Because of this prometheus would not be able to scrape these metrics. This would have to be changed to in one of the following two places:

  1. Before cluster initialization, the config file passed to kubeadm init should have KubeProxyConfiguration manifest with the field metricsBindAddress set to
  2. If the k8s cluster is already up and running, we'll have to modify the configmap kube-proxy in the namespace kube-system and set the metricsBindAddress field. After this kube-proxy daemonset would have to be restarted with kubectl -n kube-system rollout restart daemonset kube-proxy


Apache License 2.0, see LICENSE.