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Kubernetes Monitoring with Managed VictoriaMetrics

Monitoring kubernetes cluster is necessary to build SLO/SLI, to analyze performance and cost-efficiency of your workloads.

To enable kubernetes cluster monitoring, we will be collecting metrics about cluster performance and utilization from kubernetes components like kube-api-server, kube-controller-manager, kube-scheduler, kube-state-metrics, etcd, core-dns, kubelet and kube-proxy. We will also install some recording rules, alert rules and dashboards to provide visibility of cluster performance, as well as alerting for cluster metrics. For node resource utilization we will be collecting metrics from node-exporter. We will also install dashboard and alerts for node related metrics

For workloads monitoring in kubernetes cluster we will have VictoriaMetrics Operator. It enables us to define scrape jobs using kubernetes CRDs VMServiceScrape, VMPodScrape. To add alerts or recording rules for workloads we can use VMRule CRD

Overview#

In this guide we will be using victoria-metrics-k8s-stack helm chart

This chart will install VMOperator, VMAgent, NodeExporter, kube-state-metrics, grafana and some service scrape configurations to start monitoring kubernetes cluster components

Prerequisites#

  • Active Managed VictoriaMetrics instance. You can learn how to signup for Managed VictoriaMetrics here.
  • Access to your kubernetes cluster
  • Helm binary. You can find installation here

Installation steps#

Install the Helm chart in a custom namespace

  1. Create a unique Kubernetes namespace, for example monitoring

    kubectl create namespace monitoring

  2. Create kubernetes-secrets with token to access your dbaas deployment

    kubectl --namespace monitoring create secret generic dbaas-write-access-token --from-literal=bearerToken=your-token
kubectl --namespace monitoring create secret generic dbaas-read-access-token --from-literal=bearerToken=your-token

    You can find your access token on the “Access” tab of your deployment

  3. Set up a Helm repository using the following commands:

    helm repo add grafana https://grafana.github.io/helm-charts
helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm repo add vm https://victoriametrics.github.io/helm-charts
helm repo update

  4. Create a YAML file of Helm values called dbaas.yaml with following content

    externalVM:
  read:
    url: <reading url, you can find it in examples on Access page>
    bearerTokenSecret:
      name: dbaas-write-access-token
      key: bearerToken
  write:
    url: <reading url, you can find it in examples on Access page>
    bearerTokenSecret:
      name: dbaas-read-access-token
      key: bearerToken

vmsingle:
  enabled: false

vmcluster:
  enabled: false

vmalert:
  enabled: true
  spec:
    evaluationInterval: 15s

vmagent:
  enabled: true

  spec:
    scrapeInterval: 30s
    externalLabels:
      cluster: <your cluster name>

# dependencies  
# Grafana dependency chart configuration. For possible values refer to https://github.com/grafana/helm-charts/tree/main/charts/grafana#configuration
grafana:
  enabled: true

  5. Install VictoriaMetrics-k8s-stack helm chart

    helm --namespace monitoring install vm vm/victoria-metrics-k8s-stack -f dbaas.yaml -n monitoring

Connect grafana#

Connect to grafana and create your datasource

If you are using external grafana, you can skip steps 1-3 and you will need to import dashboards that can be found here manually

  1. Get grafana password

    kubectl --namespace monitoring get secret vm-grafana  -o jsonpath="{.data.admin-password}" | base64 -d

  2. Connect to grafana

    kubectl --namespace monitoring port-forward service/vm-grafana 3000:80

  3. Open grafana in your browser http://localhost:3000/datasources

    Use admin as username and password from previous step

  4. Click on add datasource Choose VictoriaMetrics or Prometheus as datasource type. Make sure you made this datasource as default for dashboards to work.

    You can find token and URL in your deployment, on Access tab

Test it#

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