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Kubernetes Kapsule cluster monitoring with Prometheus & Grafana

Reviewed on 17 June 2024Published on 18 March 2020
  • kubernetes
  • kapsule
  • Prometheus
  • monitoring
  • Grafana

Kubernetes Kapsule provides a managed Kubernetes environment to create, configure, and run a cluster of preconfigured machines for containerized applications.

This tutorial will explain how to monitor your Kubernetes Kapsule cluster. The stack that we are going to deploy is based on Prometheus, Grafana, kube-state-metrics, and node-exporter. We will use Helm to deploy the whole stack. All applications used for this how-to are well-known and widely-used open-source software that fit well in a Kubernetes environment.

  • Prometheus: Prometheus is an application used for monitoring and alerting. It records real-time metrics in a time series database. It is based on a pull model and relies on HTTP for scraping the metrics.
  • Grafana: Grafana is used for visualizing the metrics scraped by Prometheus and stored in the time series database.
  • kube-state-metrics: kube-state-metrics listens to the Kubernetes API server and generates metrics about the state of the objects. The list of the exported metrics is available here. For instance, kube-state-metrics can report the number of pods ready (kube_pod_status_ready), or the number of unschedulable pods (kube_pod_status_unschedulable).
  • node-exporter: The node-exporter is a Prometheus exporter for hardware and OS metrics exposed by the Linux Kernel. It allows you to get metrics about CPU, memory, filesystem for each Kubernetes node.

Before you start

To complete the actions presented below, you must have:

  • A Scaleway account logged into the console
  • Owner status or IAM permissions allowing you to perform actions in the intended Organization
  • Created a Kapsule cluster
  • A working kubectl on your machine
  • Installed helm (version 3.2+), the Kubernetes package manager, on your local machine

Preparing the Kubernetes Kapsule cluster

  1. Ensure you are connected to your cluster and kubectl and helm are installed on your local machine.
  2. Add the Prometheus Community Helm repo and the stable Kubernetes repo and update them:
    helm repo add prometheus-community
    helm repo add stable
    helm repo update

Deploying Prometheus

We are first going to deploy the Prometheus stack in a dedicated Kubernetes namespace called ”monitoring”. We will set the retention time for 30 days and create a persistent volume (based on Scaleway Block Storage) to store the Prometheus data.

  1. Use the helm package manager to install the stable release of Prometheus. Set the following parameters to helm for both of these:

    • server.persistentVolume: 100Gi
    • server.retention: 30d
    helm install prometheus prometheus-community/prometheus --create-namespace --namespace monitoring --set server.persistentVolume.size=100Gi,server.retention=30d
    NAME: prometheus
    LAST DEPLOYED: Fri Oct 9 16:35:50 2020
    NAMESPACE: monitoring
  2. Once the stack is deployed, verify that the created pods are all running. It is also possible to check if the 100Gi block volume was created:

    kubectl get pods,pv,pvc -n monitoring
    pod/prometheus-alertmanager-6565668c85-5vdxc 2/2 Running 0 67s
    pod/prometheus-kube-state-metrics-6756bbbb8-6qs9r 1/1 Running 0 67s
    pod/prometheus-node-exporter-fbg6s 1/1 Running 0 67s
    pod/prometheus-pushgateway-6d75c59b7b-6knfd 1/1 Running 0 67s
    pod/prometheus-server-556dbfdfb5-rx6nl 1/2 Running 0 67s
    persistentvolume/pvc-5a9def3b-22a1-4545-9adb-72823b899c36 100Gi RWO Delete Bound monitoring/prometheus-server scw-bssd 67s
    persistentvolume/pvc-c5e24d9b-3a69-46c1-9120-b16b7adf73e9 2Gi RWO Delete Bound monitoring/prometheus-alertmanager scw-bssd 67s
    persistentvolumeclaim/prometheus-alertmanager Bound pvc-c5e24d9b-3a69-46c1-9120-b16b7adf73e9 2Gi RWO scw-bssd 68s
    persistentvolumeclaim/prometheus-server Bound pvc-5a9def3b-22a1-4545-9adb-72823b899c36 100Gi RWO scw-bssd 68s
  3. To access Prometheus use the Kubernetes port forwarding feature:

    export POD_NAME=$(kubectl get pods --namespace monitoring -l "app=prometheus,component=server" -o jsonpath="{.items[0]}")
    kubectl --namespace monitoring port-forward $POD_NAME 9090
  4. Access the Prometheus dashboard using the following URL: http://localhost:9090.

  5. Verify that both node-exporter and kube-state-metrics metrics are correctly scrapped by Prometheus:

    • The node-exporter metrics begin with “node_”

    • The kube-state-metrics begin with “kube_”

  6. Prometheus can generate graphs on its own. You can test the feature by choosing metrics to analyze directly in the application:

Deploying Grafana

We are going to use and deploy Grafana to display the Prometheus metrics in some pre-defined dashboards. To do so, we are -as always- using helm. Once again we deploy it in the monitoring namespace and enable the persistence:

  • persistence.enable : true
  • persistence.type : pvc
  • persistence.size : 10Gi

Refer to the Loki tutorial to have additional information about Grafana.

  1. Add the Helm repo and install Grafana using helm with the following commands:
    helm repo add grafana
    helm install grafana grafana/grafana \
    --set persistence.enabled=true,persistence.type=pvc,persistence.size=10Gi \
  2. Once Grafana is installed retrieve the admin password:
    kubectl get secret --namespace monitoring grafana -o jsonpath="{.data.admin-password}" | base64 --decode ; echo
  3. Configure the port forwarding to access the Grafana Web interface at this address: http://localhost:3000:
    kubectl port-forward --namespace monitoring service/grafana 3000:80
    Forwarding from -> 3000
    Forwarding from [::1]:3000 -> 3000
  4. Open the Grafana Web Interface in a web browser at http://localhost:3000. The login screen displays. Enter the user admin and the password recovered in step 2:
  5. The welcome screen displays and invites you to complete the configuration of Grafana. Click Add data source to configure a new data source:
  6. Choose Prometheus as data source from the list of available options.
  7. Enter the details of the data source. You can leave the default settings and add the data source: http://prometheus-server. Click Test & Save to validate the connection to Prometheus and to save the settings:
  8. Click the + sign and then Import to import a ready-to-use dashboard from the Grafana website. To create a dashboard that uses kube-state-metrics, import the dashboard number 8588 and get information about your Deployment, Statefulset, and Daemonset:
  9. Choose Prometheus as data source and click Import.
  10. Access the dashboard with metrics for Deployment, Statefulset, and Daemonset:
  11. You can also configure additional dashboards, for example, the node exporter full dashboard (1860) to display a dashboard with system metrics for each Kubernetes node:

You now have basic monitoring for your Kubernetes Kapsule cluster. For more information on how to configure your cluster, refer to the official Kubernetes documentation.

  • kube-state-metrics
  • node-exporter
  • Prometheus and Alert Manager
  • Grafana
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