使用 Helm 在 EKS 集群部署 Grafana

Grafana 是一个开源的监控和观察工具，可以与多种数据源集成，如 Prometheus、Loki 等。在本文中将详细介绍如何使用 Helm 在 Amazon EKS（Elastic Kubernetes Service）集群上部署 Grafana。

我们将通过以下几个步骤完成部署：

准备工作
安装 Helm
配置 EKS 集群
使用 Helm 部署 Grafana
访问 Grafana

1. 准备工作

在开始之前，请确保你已经完成以下准备工作：

已经创建并配置了一个 EKS 集群。
已经安装并配置了 kubectl 命令行工具。
已经安装了 AWS CLI 并配置了适当的凭证。

2. 安装 Helm

Helm 是 Kubernetes 的包管理工具。如果你还没有安装 Helm，请参阅安装 Helm。

3. 配置 EKS 集群

确保你的 kubectl 已经正确配置并可以访问你的 EKS 集群：

aws eks --region <your-region> update-kubeconfig --name <your-cluster-name>
kubectl get nodes

上述命令应该返回你的 EKS 集群中的节点列表，表明 kubectl 已经正确配置。

4. 使用 Helm 部署 Grafana

添加 Helm 仓库：

helm repo add grafana https://grafana.github.io/helm-charts
helm repo update

创建一个命名空间用于部署 Grafana：

kubectl create namespace grafana

创建自定义 values.yaml 文件

以下是一个示例配置文件，您可以根据需要进行修改：

replicas: 1
## Expose the grafana service to be accessed from outside the cluster (LoadBalancer service).
## or access it from within the cluster (ClusterIP service). Set the service type and the port to serve it.
## ref: http://kubernetes.io/docs/user-guide/services/
##
service:
  enabled: true
  type: ClusterIP
  # Set the ip family policy to configure dual-stack see [Configure dual-stack](https://kubernetes.io/docs/concepts/services-networking/dual-stack/#services)
  ipFamilyPolicy: ""
  # Sets the families that should be supported and the order in which they should be applied to ClusterIP as well. Can be IPv4 and/or IPv6.
  ipFamilies: []
  loadBalancerIP: ""
  loadBalancerClass: ""
  loadBalancerSourceRanges: []
  port: 80
  targetPort: 3000
    # targetPort: 4181 To be used with a proxy extraContainer
  ## Service annotations. Can be templated.
  annotations: {}
  labels: {}
  portName: service
  # Adds the appProtocol field to the service. This allows to work with istio protocol selection. Ex: "http" or "tcp"
  appProtocol: ""

ingress:
  enabled: true
  # For Kubernetes >= 1.18 you should specify the ingress-controller via the field ingressClassName
  # See https://kubernetes.io/blog/2020/04/02/improvements-to-the-ingress-api-in-kubernetes-1.18/#specifying-the-class-of-an-ingress
  # ingressClassName: nginx
  # Values can be templated
  annotations:
    kubernetes.io/ingress.class: alb
    alb.ingress.kubernetes.io/scheme: internet-facing
    alb.ingress.kubernetes.io/target-type: ip
    alb.ingress.kubernetes.io/listen-ports: '[{"HTTP": 80}, {"HTTPS":443}]'
    alb.ingress.kubernetes.io/certificate-arn: arn:aws:acm:us-west-1:992382721746:certificate/455cfe47-104c-46ad-9efc-5a303ba09635
  labels: {}
  path: /

  # pathType is only for k8s >= 1.1=
  pathType: Prefix

  hosts:
    - grafana.great-way.link
  ## Extra paths to prepend to every host configuration. This is useful when working with annotation based services.
  extraPaths: []
  # - path: /*
  #   backend:
  #     serviceName: ssl-redirect
  #     servicePort: use-annotation
  ## Or for k8s > 1.19
  # - path: /*
  #   pathType: Prefix
  #   backend:
  #     service:
  #       name: ssl-redirect
  #       port:
  #         name: use-annotation

resources:
  limits:
    cpu: 500m
    memory: 1024Mi
  requests:
    cpu: 200m
    memory: 256Mi

## Node labels for pod assignment
## ref: https://kubernetes.io/docs/user-guide/node-selection/
#
nodeSelector: {}

## Tolerations for pod assignment
## ref: https://kubernetes.io/docs/concepts/configuration/taint-and-toleration/
##
tolerations: []

## Affinity for pod assignment (evaluated as template)
## ref: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/#affinity-and-anti-affinity
##
affinity:
  podAntiAffinity:
    preferredDuringSchedulingIgnoredDuringExecution:
      - weight: 100
        podAffinityTerm:
          labelSelector:
            matchExpressions:
              - key: app.kubernetes.io/name
                operator: In
                values:
                  - grafana
          topologyKey: kubernetes.io/hostname
## Topology Spread Constraints
## ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-topology-spread-constraints/
##
topologySpreadConstraints: []

## Additional init containers (evaluated as template)
## ref: https://kubernetes.io/docs/concepts/workloads/pods/init-containers/
##
extraInitContainers: []

## Enable an Specify container in extraContainers. This is meant to allow adding an authentication proxy to a grafana pod
extraContainers: ""
# extraContainers: |
# - name: proxy
#   image: quay.io/gambol99/keycloak-proxy:latest
#   args:
#   - -provider=github
#   - -client-id=
#   - -client-secret=
#   - -github-org=<ORG_NAME>
#   - -email-domain=*
#   - -cookie-secret=
#   - -http-address=http://0.0.0.0:4181
#   - -upstream-url=http://127.0.0.1:3000
#   ports:
#     - name: proxy-web
#       containerPort: 4181

## Volumes that can be used in init containers that will not be mounted to deployment pods
extraContainerVolumes: []
#  - name: volume-from-secret
#    secret:
#      secretName: secret-to-mount
#  - name: empty-dir-volume
#    emptyDir: {}

## Enable persistence using Persistent Volume Claims
## ref: http://kubernetes.io/docs/user-guide/persistent-volumes/
##
persistence:
  type: pvc
  enabled: true
  # storageClassName: default
  accessModes:
    - ReadWriteOnce
  size: 10Gi
  # annotations: {}
  finalizers:
    - kubernetes.io/pvc-protection
  # selectorLabels: {}
  ## Sub-directory of the PV to mount. Can be templated.
  # subPath: ""
  ## Name of an existing PVC. Can be templated.
  # existingClaim:
  ## Extra labels to apply to a PVC.
  extraPvcLabels: {}
  disableWarning: false

  ## If persistence is not enabled, this allows to mount the
  ## local storage in-memory to improve performance
  ##
  inMemory:
    enabled: false
    ## The maximum usage on memory medium EmptyDir would be
    ## the minimum value between the SizeLimit specified
    ## here and the sum of memory limits of all containers in a pod
    ##
    # sizeLimit: 300Mi

  ## If 'lookupVolumeName' is set to true, Helm will attempt to retrieve
  ## the current value of 'spec.volumeName' and incorporate it into the template.
  lookupVolumeName: true

  ## initChownData resource requests and limits
  ## Ref: http://kubernetes.io/docs/user-guide/compute-resources/
  ##
  resources: {}
  #  limits:
  #    cpu: 100m
  #    memory: 128Mi
  #  requests:
  #    cpu: 100m
  #    memory: 128Mi
  securityContext:
    runAsNonRoot: false
    runAsUser: 0
    seccompProfile:
      type: RuntimeDefault
    capabilities:
      add:
        - CHOWN

# Administrator credentials when not using an existing secret (see below)
adminUser: admin
adminPassword: Aq8wLzRFA3bU5gO2nVlfHFlXHjYCh7tL9F4sIpwD

# Use an existing secret for the admin user.
admin:
  ## Name of the secret. Can be templated.
  existingSecret: ""
  userKey: admin-user
  passwordKey: admin-password

## Container Lifecycle Hooks. Execute a specific bash command or make an HTTP request
lifecycleHooks: {}
  # postStart:
  #   exec:
  #     command: []

## Pass the plugins you want installed as a list.
##
plugins: []
  # - digrich-bubblechart-panel
  # - grafana-clock-panel
  ## You can also use other plugin download URL, as long as they are valid zip files,
  ## and specify the name of the plugin after the semicolon. Like this:
  # - https://grafana.com/api/plugins/marcusolsson-json-datasource/versions/1.3.2/download;marcusolsson-json-datasource

## Configure grafana datasources
## ref: http://docs.grafana.org/administration/provisioning/#datasources
##
datasources: 
  datasources.yaml:
    apiVersion: 1
    datasources:
      - name: Prometheus
        type: prometheus
        access: proxy
        url: http://prometheus-server.prometheus.svc.cluster.local
        isDefault: true
      - name: Loki
        type: loki
        access: proxy
        url: http://loki-gateway.loki.svc.cluster.local


## Configure grafana alerting (can be templated)
## ref: http://docs.grafana.org/administration/provisioning/#alerting
##
alerting: {}
  # rules.yaml:
  #   apiVersion: 1
  #   groups:
  #     - orgId: 1
  #       name: '{{ .Chart.Name }}_my_rule_group'
  #       folder: my_first_folder
  #       interval: 60s
  #       rules:
  #         - uid: my_id_1
  #           title: my_first_rule
  #           condition: A
  #           data:
  #             - refId: A
  #               datasourceUid: '-100'
  #               model:
  #                 conditions:
  #                   - evaluator:
  #                       params:
  #                         - 3
  #                       type: gt
  #                     operator:
  #                       type: and
  #                     query:
  #                       params:
  #                         - A
  #                     reducer:
  #                       type: last
  #                     type: query
  #                 datasource:
  #                   type: __expr__
  #                   uid: '-100'
  #                 expression: 1==0
  #                 intervalMs: 1000
  #                 maxDataPoints: 43200
  #                 refId: A
  #                 type: math
  #           dashboardUid: my_dashboard
  #           panelId: 123
  #           noDataState: Alerting
  #           for: 60s
  #           annotations:
  #             some_key: some_value
  #           labels:
  #             team: sre_team_1
  # contactpoints.yaml:
  #   secret:
  #     apiVersion: 1
  #     contactPoints:
  #       - orgId: 1
  #         name: cp_1
  #         receivers:
  #           - uid: first_uid
  #             type: pagerduty
  #             settings:
  #               integrationKey: XXX
  #               severity: critical
  #               class: ping failure
  #               component: Grafana
  #               group: app-stack
  #               summary: |
  #                 {{ `{{ include "default.message" . }}` }}

## Configure notifiers
## ref: http://docs.grafana.org/administration/provisioning/#alert-notification-channels
##
notifiers: {}
#  notifiers.yaml:
#    notifiers:
#    - name: email-notifier
#      type: email
#      uid: email1
#      # either:
#      org_id: 1
#      # or
#      org_name: Main Org.
#      is_default: true
#      settings:
#        addresses: an_email_address@example.com
#    delete_notifiers:

## Configure grafana dashboard providers
## ref: http://docs.grafana.org/administration/provisioning/#dashboards
##
## `path` must be /var/lib/grafana/dashboards/<provider_name>
##
dashboardProviders: {}
#  dashboardproviders.yaml:
#    apiVersion: 1
#    providers:
#    - name: 'default'
#      orgId: 1
#      folder: ''
#      type: file
#      disableDeletion: false
#      editable: true
#      options:
#        path: /var/lib/grafana/dashboards/default

## Configure grafana dashboard to import
## NOTE: To use dashboards you must also enable/configure dashboardProviders
## ref: https://grafana.com/dashboards
##
## dashboards per provider, use provider name as key.
##
dashboards: {}
  # default:
  #   some-dashboard:
  #     json: |
  #       $RAW_JSON
  #   custom-dashboard:
  #     file: dashboards/custom-dashboard.json
  #   prometheus-stats:
  #     gnetId: 2
  #     revision: 2
  #     datasource: Prometheus
  #   local-dashboard:
  #     url: https://example.com/repository/test.json
  #     token: ''
  #   local-dashboard-base64:
  #     url: https://example.com/repository/test-b64.json
  #     token: ''
  #     b64content: true
  #   local-dashboard-gitlab:
  #     url: https://example.com/repository/test-gitlab.json
  #     gitlabToken: ''
  #   local-dashboard-bitbucket:
  #     url: https://example.com/repository/test-bitbucket.json
  #     bearerToken: ''
  #   local-dashboard-azure:
  #     url: https://example.com/repository/test-azure.json
  #     basic: ''
  #     acceptHeader: '*/*'

配置说明：

adminPassword: 配置 admin 密码。
ingress.enabled: 启用 Ingress。
ingress.annotations: 配置 Ingress 的注解，例如指定 Ingress 类和重写目标。
ingress.hosts: 配置 Grafana 的域名。
datasources.datasources.yaml: 配置数据源，这里配置了 Prometheus 和 Loki 的数据源。

使用 Helm 安装 Grafana：

helm install grafana grafana/grafana --namespace grafana

这将会下载并部署 Grafana 到你的 EKS 集群中。你可以使用以下命令查看部署状态：

kubectl get pods -n grafana

5. 访问 Grafana

Grafana 安装完成后，你可以通过配置的域名访问，也可以通过端口转发来访问 Grafana UI：

kubectl port-forward --namespace grafana svc/grafana 3000:80

在浏览器中访问 http://localhost:3000，使用用户名 admin 和你配置的密码进行登录。

总结

通过以上步骤，已经成功地使用 Helm 在 EKS 集群上部署了 Grafana。现在可以配置数据源和仪表板，充分利用 Grafana 强大的监控和可视化功能。

使用 Helm 在 EKS 集群部署 Grafana

使用 Helm 在 EKS 集群部署 Grafana#

1. 准备工作#

2. 安装 Helm#

3. 配置 EKS 集群#

4. 使用 Helm 部署 Grafana#

配置说明：#

5. 访问 Grafana#

总结#

使用 Helm 在 EKS 集群部署 Grafana

1. 准备工作

2. 安装 Helm

3. 配置 EKS 集群

4. 使用 Helm 部署 Grafana

配置说明：

5. 访问 Grafana

总结