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Monitoring Kubernetes clusters on AWS, GCP and Azure using Prometheus Operator and Grafana

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Monitoring Kubernetes clusters on AWS, GCP and Azure using Prometheus Operator by CoreOS


Note: the work on this repository is now based on CoreOS's kube-prometheus and it will be the default option for Kubernetes 1.7.X and up. For 1.5.X and 1.6.X you can deploy a simpler solution, located in

directory. The purpose of this project is to provide a simple and interactive method to deploy and configure Prometheus on Kubernetes, especially for the users that are not using Helm.


  • Prometheus Operator with support for Prometheus v2.X.X
  • highly available Prometheus and Alertmaneger
  • InCluster deployment using
    for persistent storage
  • auto-discovery for services and pods
  • automatic RBAC configuration
  • preconfigured alerts
  • preconfigured Grafana dashboards
  • easy to setup; usually less than a minute to deploy a complete monitoring solution for Kubernetes
  • support for Kubernetes v1.7.x and up running in AWS, GCP and Azure
  • tested on clusters deployed using kube-aws, kops, GKE and Azure ## One minute deployment



  • Kubernetes cluster and
  • Security Groups configured to allow the following ports:
    • 9100/TCP - node-exporter
    • 10250/TCP - kubernetes nodes metrics,
    • 10251/TCP - kube-scheduler
    • 10252/TCP - kube-controller-manager
    • 10054/TCP and 10055/TCP - kube-dns


  • SMTP Account for email alerts
  • Token for Slack alerts

Running Kubernetes 1.12 and up?

If you are running Kubernetes 1.12 or higher you will also need to run cAdvisor on your cluster (bound to host port 4194) in order to access resource usage and performance characteristics of running containers.


Clone the repository and checkout the latest release:

curl -L | sh -

Custom settings

All the components versions can be configured using the interactive deployment script. Same for the SMTP account or the Slack token.

Some other settings that can be changed before deployment: * Prometheus replicas: default 2 ==>

* persistent volume size: default 40Gi ==>
* allocated memory for Prometheus pods: default 2Gi ==>
* Alertmanager replicas: default 3 ==>
* Alertmanager configuration: ==>
* custom Grafana dashboards: add yours in
with names ending in
* custom alert rules: ==>

Note: please commit your changes before deployment if you wish to keep them. The

script will remove the changes on most of the files.



Now you can access the dashboards locally using

kubectl port-forward
command, or expose the services using a ingress or a LoadBalancer. Please check the
directory to quickly configure a ingress or proxy the services to localhost.

To remove everything, just execute the


Updating configurations

  • update alert rules: add or change the rules in
    and execute
    . Then apply the changes using
    kubectl apply -f manifests/prometheus/prometheus-k8s-rules.yaml -n monitoring
  • update grafana dashboards: add or change the existing dashboards in
    and execute
    . Then apply the changes using
    kubectl apply -f manifests/grafana/

Note: all the Grafana dashboards should have names ending in


Custom Prometheus configuration

The official documentation for Prometheus Operator custom configuration can be found here: If you wish, you can update the Prometheus configuration using the


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