Install ElasticSearch

Installation

Install By

Preliminary

1. Kubernetes has installed, if not check 🔗link

2. Helm has installed, if not check 🔗link

1.get helm repo

helm repo add ay-helm-mirror https://aaronyang0628.github.io/helm-chart-mirror/charts
helm repo update

2.install chart

helm install ay-helm-mirror/kube-prometheus-stack --generate-name

Using Proxy

for more information, you can check 🔗https://artifacthub.io/packages/helm/prometheus-community/prometheus

Preliminary

1. Kubernetes has installed, if not check 🔗link

2. Helm has installed, if not check 🔗link

3. ArgoCD has installed, if not check 🔗link

1.prepare `deploy-elasticsearch.yaml`

kubectl apply -f - << EOF
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: elastic-search
spec:
  syncPolicy:
    syncOptions:
    - CreateNamespace=true
  project: default
  source:
    repoURL: https://charts.bitnami.com/bitnami
    chart: elasticsearch
    targetRevision: 19.11.3
    helm:
      releaseName: elastic-search
      values: |
        global:
          kibanaEnabled: true
        clusterName: elastic
        image:
          registry: m.zjvis.net/docker.io
          pullPolicy: IfNotPresent
        security:
          enabled: false
        service:
          type: ClusterIP
        ingress:
          enabled: true
          annotations:
            cert-manager.io/cluster-issuer: self-signed-ca-issuer
            nginx.ingress.kubernetes.io/rewrite-target: /$1
          hostname: elastic-search.dev.tech
          ingressClassName: nginx
          path: /?(.*)
          tls: true
        master:
          masterOnly: false
          replicaCount: 1
          persistence:
            enabled: false
          resources:
            requests:
              cpu: 2
              memory: 1024Mi
            limits:
              cpu: 4
              memory: 4096Mi
          heapSize: 2g
        data:
          replicaCount: 0
          persistence:
            enabled: false
        coordinating:
          replicaCount: 0
        ingest:
          enabled: true
          replicaCount: 0
          service:
            enabled: false
            type: ClusterIP
          ingress:
            enabled: false
        metrics:
          enabled: false
          image:
            registry: m.zjvis.net/docker.io
            pullPolicy: IfNotPresent
        volumePermissions:
          enabled: false
          image:
            registry: m.zjvis.net/docker.io
            pullPolicy: IfNotPresent
        sysctlImage:
          enabled: true
          registry: m.zjvis.net/docker.io
          pullPolicy: IfNotPresent
        kibana:
          elasticsearch:
            hosts:
              - '{{ include "elasticsearch.service.name" . }}'
            port: '{{ include "elasticsearch.service.ports.restAPI" . }}'
        esJavaOpts: "-Xmx2g -Xms2g"        
  destination:
    server: https://kubernetes.default.svc
    namespace: application
EOF

3.sync by argocd

argocd app sync argocd/elastic-search

4.extract elasticsearch admin credentials

5.invoke http api

add `$K8S_MASTER_IP elastic-search.dev.tech` to `/etc/hosts`

curl -k -H "Content-Type: application/json" \
    -X POST "https://elastic-search.dev.tech:32443/books/_doc?pretty" \
    -d '{"name": "Snow Crash", "author": "Neal Stephenson", "release_date": "1992-06-01", "page_count": 470}'

Preliminary

1. Docker|Podman|Buildah has installed, if not check 🔗link

Using Proxy

you can run an addinational daocloud image to accelerate your pulling, check Daocloud Proxy

1.init server

Preliminary

1. Kubernetes has installed, if not check 🔗link

2. Helm has installed, if not check 🔗link

3. ArgoCD has installed, if not check 🔗link

4. Argo Workflow has installed, if not check 🔗link

1.prepare `argocd-login-credentials`

kubectl get namespaces database > /dev/null 2>&1 || kubectl create namespace database

2.apply rolebinding to k8s

kubectl apply -f - <<EOF
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: application-administrator
rules:
  - apiGroups:
      - argoproj.io
    resources:
      - applications
    verbs:
      - '*'
  - apiGroups:
      - apps
    resources:
      - deployments
    verbs:
      - '*'

---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: application-administration
  namespace: argocd
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: application-administrator
subjects:
  - kind: ServiceAccount
    name: argo-workflow
    namespace: business-workflows

---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: application-administration
  namespace: application
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: application-administrator
subjects:
  - kind: ServiceAccount
    name: argo-workflow
    namespace: business-workflows
EOF

4.prepare `deploy-xxxx-flow.yaml`

6.subimit to argo workflow client

argo -n business-workflows submit deploy-xxxx-flow.yaml

7.decode password

kubectl -n application get secret xxxx-credentials -o jsonpath='{.data.xxx-password}' | base64 -d

FAQ

Q1: Show me almost endless possibilities

You can add standard markdown syntax:

multiple paragraphs
bullet point lists
emphasized, bold and even bold emphasized text
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etc.

...and even source code

the possibilities are endless (almost - including other shortcodes may or may not work)

Q2: Show me almost endless possibilities

You can add standard markdown syntax:

multiple paragraphs
bullet point lists
emphasized, bold and even bold emphasized text
links
etc.

...and even source code

the possibilities are endless (almost - including other shortcodes may or may not work)