zoonage / prometheus-operator

Prometheus Operator creates/configures/manages Prometheus clusters atop Kubernetes

Prometheus Operator

Project status: beta Not all planned features are completed. The API, spec, status and other user facing objects may change, but in a backward compatible way.

Overview

The Prometheus Operator provides Kubernetes native deployment and management of Prometheus and related monitoring components. The purpose of this project is to simplify and automate the configuration of a Prometheus based monitoring stack for Kubernetes clusters.

The Prometheus operator includes, but is not limited to, the following features:

• Kubernetes Custom Resources: Use Kubernetes custom resources to deploy and manage Prometheus, Alertmanager, and related components.

• Simplified Deployment Configuration: Configure the fundamentals of Prometheus like versions, persistence, retention policies, and replicas from a native Kubernetes resource.

• Prometheus Target Configuration: Automatically generate monitoring target configurations based on familiar Kubernetes label queries; no need to learn a Prometheus specific configuration language.

For an introduction to the Prometheus Operator, see the initial blog post.

Prometheus Operator vs. kube-prometheus vs. community helm chart

The Prometheus Operator uses Kubernetes custom resources to simplifiy the deployment and configuration of Prometheus, Alertmanager, and related monitoring components.

kube-prometheus provides example configurations for a complete cluster monitoring stack based on Prometheus and the Prometheus Operator. This includes deployment of multiple Prometheus and Alertmanager instances, metrics exporters such as the node_exporter for gathering node metrics, scrape target configuration linking Prometheus to various metrics endpoints, and example alerting rules for notification of potential issues in the cluster.

The stable/prometheus-operator helm chart provides a similar feature set to kube-prometheus. This chart is maintained by the Helm community. For more information, please see the chart's readme

Prerequisites

Version >=0.39.0 of the Prometheus Operator requires a Kubernetes cluster of version >=1.16.0. If you are just starting out with the Prometheus Operator, it is highly recommended to use the latest version.

If you have an older version of Kubernetes and the Prometheus Operator running, we recommend upgrading Kubernetes first and then the Prometheus Operator.

CustomResourceDefinitions

A core feature of the Prometheus Operator is to monitor the Kubernetes API server for changes to specific objects and ensure that the current Prometheus deployments match these objects. The Operator acts on the following custom resource definitions (CRDs):

• Prometheus, which defines a desired Prometheus deployment.

• Alertmanager, which defines a desired Alertmanager deployment.

• ThanosRuler, which defines a desired Thanos Ruler deployment.

• ServiceMonitor, which declaratively specifies how groups of Kubernetes services should be monitored. The Operator automatically generates Prometheus scrape configuration based on the current state of the objects in the API server.

• PodMonitor, which declaratively specifies how group of pods should be monitored. The Operator automatically generates Prometheus scrape configuration based on the current state of the objects in the API server.

• Probe, which declaratively specifies how groups of ingresses or static targets should be monitored. The Operator automatically generates Prometheus scrape configuration based on the definition.

• PrometheusRule, which defines a desired set of Prometheus alerting and/or recording rules. The Operator generates a rule file, which can be used by Prometheus instances.

The Prometheus operator automatically detects changes in the Kubernetes API server to any of the above objects, and ensures that matching deployments and configurations are kept in sync.

To learn more about the CRDs introduced by the Prometheus Operator have a look at the design doc.

To automate validation of your CRD configuration files see about linting.

Dynamic Admission Control

To prevent invalid Prometheus alerting and recording rules from causing failures in a deployed Prometheus instance, an admission webhook is provided to validate PrometheusRule resources upon initial creation or update.

For more information on this feature, see the user guide.

Quickstart

Note: this quickstart does not provision an entire monitoring stack; if that is what you are looking for, see the kube-prometheus project. If you want the whole stack, but have already applied the bundle.yaml, delete the bundle first (kubectl delete -f bundle.yaml).

To quickly try out just the Prometheus Operator inside a cluster, choose a release and run the following command:

kubectl apply -f bundle.yaml

Note: make sure to adapt the namespace in the ClusterRoleBinding if deploying in a namespace other than the default namespace.

To run the Operator outside of a cluster:

make
scripts/run-external.sh <kubectl cluster name>

Removal

To remove the operator and Prometheus, first delete any custom resources you created in each namespace. The operator will automatically shut down and remove Prometheus and Alertmanager pods, and associated ConfigMaps.

for n in $(kubectl get namespaces -o jsonpath={..metadata.name}); do
  kubectl delete --all --namespace=$n prometheus,servicemonitor,podmonitor,alertmanager
done

After a couple of minutes you can go ahead and remove the operator itself.

kubectl delete -f bundle.yaml

The operator automatically creates services in each namespace where you created a Prometheus or Alertmanager resources, and defines three custom resource definitions. You can clean these up now.

for n in $(kubectl get namespaces -o jsonpath={..metadata.name}); do
  kubectl delete --ignore-not-found --namespace=$n service prometheus-operated alertmanager-operated
done

kubectl delete --ignore-not-found customresourcedefinitions \
  prometheuses.monitoring.coreos.com \
  servicemonitors.monitoring.coreos.com \
  podmonitors.monitoring.coreos.com \
  alertmanagers.monitoring.coreos.com \
  prometheusrules.monitoring.coreos.com

Development

Prerequisites

• golang environment
• docker (used for creating container images, etc.)
• minikube (optional)

Testing

Ensure that you're running tests in the following path: $GOPATH/src/github.com/coreos/prometheus-operator as tests expect paths to match. If you're working from a fork, just add the forked repo as a remote and pull against your local coreos checkout before running tests.

Running unit tests:

make test-unit

Running end-to-end tests on local minikube cluster:

1. minikube start --kubernetes-version=v1.10.0 --memory=4096 --extra-config=apiserver.authorization-mode=RBAC
2. eval $(minikube docker-env) && make image - build Prometheus Operator docker image on minikube's docker
3. make test-e2e

Running end-to-end tests on local kind cluster:

1. kind create cluster --image=kindest/node:<latest>. e.g v1.16.2 version.
2. export KUBECONFIG="$(kind get kubeconfig-path --name="kind")"
3. make image - build Prometheus Operator docker image locally.
4. for n in "operator" "config-reloader"; do kind load docker-image "quay.io/coreos/prometheus-$n:$(git rev-parse --short HEAD)"; done - publish built locally images to be accessible inside kind.
5. make test-e2e

Contributing

Many files (documentation, manifests, ...) in this repository are auto-generated. E.g. bundle.yaml originates from the Jsonnet files in /jsonnet/prometheus-operator. Before proposing a pull request:

1. Commit your changes.
2. Run make generate.
3. Commit the generated changes.

Security

If you find a security vulnerability related to the Prometheus Operator, please do not report it by opening a GitHub issue, but instead please send an e-mail to the maintainers of the project found in the OWNERS file.