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Version: 3.8 (unsupported)

Getting Started with Helm Charts (Monitoring using Prometheus Operator)

This document explains how to get started with Scalar products monitoring on Kubernetes using Prometheus Operator (kube-prometheus-stack). Here, we assume that you already have a Mac or Linux environment for testing. We use Minikube in this document, but the steps we will show should work in any Kubernetes cluster.

What we create​

We will deploy the following components on a Kubernetes cluster as follows.

+--------------------------------------------------------------------------------------------------+
| +------------------------------------------------------+ +-----------------+ |
| | kube-prometheus-stack | | Scalar Products | |
| | | | | |
| | +--------------+ +--------------+ +--------------+ | -----(Monitor)----> | +-----------+ | |
| | | Prometheus | | Alertmanager | | Grafana | | | | ScalarDB | | |
| | +-------+------+ +------+-------+ +------+-------+ | | +-----------+ | |
| | | | | | | +-----------+ | |
| | +----------------+-----------------+ | | | ScalarDL | | |
| | | | | +-----------+ | |
| +--------------------------+---------------------------+ +-----------------+ |
| | |
| | Kubernetes |
+----------------------------+---------------------------------------------------------------------+
| <- expose to localhost (127.0.0.1) or use load balancer etc to access
|
(Access Dashboard through HTTP)
|
+----+----+
| Browser |
+---------+

Step 1. Start a Kubernetes cluster​

First, you need to prepare a Kubernetes cluster. If you use a minikube environment, please refer to the Getting Started with Scalar Helm Charts. If you have already started a Kubernetes cluster, you can skip this step.

Step 2. Prepare a custom values file​

  1. Save the sample file scalar-prometheus-custom-values.yaml for kube-prometheus-stack.

  2. Add custom values in the scalar-prometheus-custom-values.yaml as follows.

    • settings
      • prometheus.service.type to LoadBalancer
      • alertmanager.service.type to LoadBalancer
      • grafana.service.type to LoadBalancer
      • grafana.service.port to 3000
    • Example
      alertmanager:

      service:
      type: LoadBalancer

      ...

      grafana:

      service:
      type: LoadBalancer
      port: 3000

      ...

      prometheus:

      service:
      type: LoadBalancer

      ...
    • Note:
      • If you want to customize the Prometheus Operator deployment by using Helm Charts, you'll need to set the following configurations to monitor Scalar products:

        • Set serviceMonitorSelectorNilUsesHelmValues and ruleSelectorNilUsesHelmValues to false (true by default) so that Prometheus Operator can detect ServiceMonitor and PrometheusRule for Scalar products.
      • If you want to use Scalar Manager, you'll need to set the following configurations to enable Scalar Manager to collect CPU and memory resources:

        • Set kubeStateMetrics.enabled, nodeExporter.enabled, and kubelet.enabled to true.
      • If you want to use Scalar Manager, you'll need to set the following configurations to enable Scalar Manager to embed Grafana:

        • Set grafana.ini.security.allow_embedding and grafana.ini.auth.anonymous.enabled to true.
        • Set grafana.ini.auth.anonymous.org_name to the organization you are using. If you're using the sample custom values, the value is Main Org..
        • Set grafana.ini.auth.anonymous.org_role to Editor.

Step 3. Deploy kube-prometheus-stack​

  1. Add the prometheus-community helm repository.

    helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
  2. Create a namespace monitoring on the Kubernetes.

    kubectl create namespace monitoring
  3. Deploy the kube-prometheus-stack.

    helm install scalar-monitoring prometheus-community/kube-prometheus-stack -n monitoring -f scalar-prometheus-custom-values.yaml

Step 4. Deploy (or Upgrade) Scalar products using Helm Charts​

  1. To enable Prometheus monitoring of Scalar products, set true to the following configurations in the custom values file.

    • Configurations
      • *.prometheusRule.enabled
      • *.grafanaDashboard.enabled
      • *.serviceMonitor.enabled
    • Sample configuration files
      • ScalarDB (scalardb-custom-values.yaml)
        envoy:
        prometheusRule:
        enabled: true
        grafanaDashboard:
        enabled: true
        serviceMonitor:
        enabled: true

        scalardb:
        prometheusRule:
        enabled: true
        grafanaDashboard:
        enabled: true
        serviceMonitor:
        enabled: true
      • ScalarDL Ledger (scalardl-ledger-custom-values.yaml)
        envoy:
        prometheusRule:
        enabled: true
        grafanaDashboard:
        enabled: true
        serviceMonitor:
        enabled: true

        ledger:
        prometheusRule:
        enabled: true
        grafanaDashboard:
        enabled: true
        serviceMonitor:
        enabled: true
      • ScalarDL Auditor (scalardl-auditor-custom-values.yaml)
        envoy:
        prometheusRule:
        enabled: true
        grafanaDashboard:
        enabled: true
        serviceMonitor:
        enabled: true

        auditor:
        prometheusRule:
        enabled: true
        grafanaDashboard:
        enabled: true
        serviceMonitor:
        enabled: true
  2. Deploy (or Upgrade) Scalar products using Helm Charts with the above custom values file.

    • Examples
      • ScalarDB
        helm install scalardb scalar-labs/scalardb -f ./scalardb-custom-values.yaml
        helm upgrade scalardb scalar-labs/scalardb -f ./scalardb-custom-values.yaml
      • ScalarDL Ledger
        helm install scalardl-ledger scalar-labs/scalardl -f ./scalardl-ledger-custom-values.yaml
        helm upgrade scalardl-ledger scalar-labs/scalardl -f ./scalardl-ledger-custom-values.yaml
      • ScalarDL Auditor
        helm install scalardl-auditor scalar-labs/scalardl-audit -f ./scalardl-auditor-custom-values.yaml
        helm upgrade scalardl-auditor scalar-labs/scalardl-audit -f ./scalardl-auditor-custom-values.yaml

Step 5. Access Dashboards​

If you use minikube​

  1. To expose each service resource as your localhost (127.0.0.1), open another terminal, and run the minikube tunnel command.

    minikube tunnel

    After running the minikube tunnel command, you can see the EXTERNAL-IP of each service resource as 127.0.0.1.

    kubectl get svc -n monitoring scalar-monitoring-kube-pro-prometheus scalar-monitoring-kube-pro-alertmanager scalar-monitoring-grafana

    [Command execution result]

    NAME                                      TYPE           CLUSTER-IP     EXTERNAL-IP   PORT(S)          AGE
    scalar-monitoring-kube-pro-prometheus LoadBalancer 10.98.11.12 127.0.0.1 9090:30550/TCP 26m
    scalar-monitoring-kube-pro-alertmanager LoadBalancer 10.98.151.66 127.0.0.1 9093:31684/TCP 26m
    scalar-monitoring-grafana LoadBalancer 10.103.19.4 127.0.0.1 3000:31948/TCP 26m
  2. Access each Dashboard.

    • Prometheus
      http://localhost:9090/
    • Alertmanager
      http://localhost:9093/
    • Grafana
      http://localhost:3000/
      • Note:
        • You can see the user and password of Grafana as follows.
          • user
            kubectl get secrets scalar-monitoring-grafana -n monitoring -o jsonpath='{.data.admin-user}' | base64 -d
          • password
            kubectl get secrets scalar-monitoring-grafana -n monitoring -o jsonpath='{.data.admin-password}' | base64 -d

If you use other Kubernetes than minikube​

If you use a Kubernetes cluster other than minikube, you need to access the LoadBalancer service according to the manner of each Kubernetes cluster. For example, using a Load Balancer provided by cloud service or the kubectl port-forward command.

Step 6. Delete all resources​

After completing the Monitoring tests on the Kubernetes cluster, remove all resources.

  1. Terminate the minikube tunnel command. (If you use minikube)

    Ctrl + C
  2. Uninstall kube-prometheus-stack.

    helm uninstall scalar-monitoring -n monitoring
  3. Delete minikube. (Optional / If you use minikube)

    minikube delete --all
    • Note:
      • If you deploy the ScalarDB or ScalarDL, you need to remove them before deleting minikube.