如何把Spring Cloud Data Flow部署在Kubernetes上
1 前言
Spring Cloud Data Flow在本地跑得好好的，為什麼要部署在Kubernetes上呢？主要是因為Kubernetes能提供更靈活的微服務管理；在叢集上跑，會更安全穩定、更合理利用物理資源。
Spring Cloud Data Flow入門簡介請參考：Spring Cloud Data Flow初體驗，以Local模式執行
2 部署Data Flow到Kubernetes
以簡單為原則，我們依然是基於Batch任務，不部署與Stream相關的元件。
2.1 下載GitHub程式碼
我們要基於官方提供的部署程式碼進行修改，先把官方程式碼clone下來：
$ git clone https://github.com/spring-cloud/spring-cloud-dataflow.git
我們切換到最新穩定版本的程式碼版本：
$ git checkout v2.5.3.RELEASE
2.2 建立許可權賬號
為了讓Data Flow Server有許可權來跑任務，能在Kubernetes管理資源，如新建Pod等，所以要建立對應的許可權賬號。這部分程式碼與原始碼一致，不需要修改：
（1）server-roles.yaml
kind: Role apiVersion: rbac.authorization.k8s.io/v1 metadata: name: scdf-role rules: - apiGroups: [""] resources: ["services","pods","replicationcontrollers","persistentvolumeclaims"] verbs: ["get","list","watch","create","delete","update"] - apiGroups: [""] resources: ["configmaps","secrets","pods/log"] verbs: ["get","watch"] - apiGroups: ["apps"] resources: ["statefulsets","deployments","replicasets"] verbs: ["get","update","patch"] - apiGroups: ["extensions"] resources: ["deployments","patch"] - apiGroups: ["batch"] resources: ["cronjobs","jobs"] verbs: ["create","get","patch"]
（2）server-rolebinding.yaml
kind: RoleBinding apiVersion: rbac.authorization.k8s.io/v1beta1 metadata: name: scdf-rb subjects: - kind: ServiceAccount name: scdf-sa roleRef: kind: Role name: scdf-role apiGroup: rbac.authorization.k8s.io
（3）service-account.yaml
apiVersion: v1 kind: ServiceAccount metadata: name: scdf-sa
執行以下命令，建立對應賬號：
$ kubectl create -f src/kubernetes/server/server-roles.yaml $ kubectl create -f src/kubernetes/server/server-rolebinding.yaml $ kubectl create -f src/kubernetes/server/service-account.yaml
執行完成後，可以檢查一下：
$ kubectl get role NAME AGE scdf-role 119m $ kubectl get rolebinding NAME AGE scdf-rb 117m $ kubectl get serviceAccount NAME SECRETS AGE default 1 27d scdf-sa 1 117m
2.3 部署MySQL
可以選擇其它資料庫，如果本來就有資料庫，可以不用部署，在部署Server的時候改一下配置就好了。這裡跟著官方的Guide來。為了保證部署不會因為映象下載問題而失敗，我提前下載了映象：
$ docker pull mysql:5.7.25
MySQL的yaml檔案也不需要修改，直接執行以下命令即可：
$ kubectl create -f src/kubernetes/mysql/
執行完後檢查一下：
$ kubectl get Secret NAME TYPE DATA AGE default-token-jhgfp kubernetes.io/service-account-token 3 27d mysql Opaque 2 98m scdf-sa-token-wmgk6 kubernetes.io/service-account-token 3 123m $ kubectl get PersistentVolumeClaim NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE mysql Bound pvc-e95b495a-bea5-40ee-9606-dab8d9b0d65c 8Gi RWO hostpath 98m $ kubectl get Deployment NAME READY UP-TO-DATE AVAILABLE AGE mysql 1/1 1 1 98m $ kubectl get Service NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE mysql ClusterIP 10.98.243.130 <none> 3306/TCP 98m
2.4 部署Data Flow Server
2.4.1 修改配置檔案server-config.yaml
刪除掉不用的配置，主要是Prometheus和Grafana的配置，結果如下：
apiVersion: v1
kind: ConfigMap
metadata:
name: scdf-server
labels:
app: scdf-server
data:
application.yaml: |-
spring:
cloud:
dataflow:
task:
platform:
kubernetes:
accounts:
default:
limits:
memory: 1024Mi
datasource:
url: jdbc:mysql://${MYSQL_SERVICE_HOST}:${MYSQL_SERVICE_PORT}/mysql
username: root
password: ${mysql-root-password}
driverClassName: org.mariadb.jdbc.Driver
testOnBorrow: true
validationQuery: "SELECT 1"
2.4.2 修改server-svc.yaml
因為我是本地執行的Kubernetes，所以把Service型別從LoadBalancer改為NodePort，並配置埠為30093。
kind: Service apiVersion: v1 metadata: name: scdf-server labels: app: scdf-server spring-deployment-id: scdf spec: # If you are running k8s on a local dev box or using minikube,you can use type NodePort instead type: NodePort ports: - port: 80 name: scdf-server nodePort: 30093 selector: app: scdf-server
2.4.3 修改server-deployment.yaml
主要把Stream相關的去掉，如SPRING_CLOUD_SKIPPER_CLIENT_SERVER_URI配置項：
apiVersion: apps/v1
kind: Deployment
metadata:
name: scdf-server
labels:
app: scdf-server
spec:
selector:
matchLabels:
app: scdf-server
replicas: 1
template:
metadata:
labels:
app: scdf-server
spec:
containers:
- name: scdf-server
image: springcloud/spring-cloud-dataflow-server:2.5.3.RELEASE
imagePullPolicy: IfNotPresent
volumeMounts:
- name: database
mountPath: /etc/secrets/database
readOnly: true
ports:
- containerPort: 80
livenessProbe:
httpGet:
path: /management/health
port: 80
initialDelaySeconds: 45
readinessProbe:
httpGet:
path: /management/info
port: 80
initialDelaySeconds: 45
resources:
limits:
cpu: 1.0
memory: 2048Mi
requests:
cpu: 0.5
memory: 1024Mi
env:
- name: KUBERNETES_NAMESPACE
valueFrom:
fieldRef:
fieldPath: "metadata.namespace"
- name: SERVER_PORT
value: '80'
- name: SPRING_CLOUD_CONFIG_ENABLED
value: 'false'
- name: SPRING_CLOUD_DATAFLOW_FEATURES_ANALYTICS_ENABLED
value: 'true'
- name: SPRING_CLOUD_DATAFLOW_FEATURES_SCHEDULES_ENABLED
value: 'true'
- name: SPRING_CLOUD_KUBERNETES_SECRETS_ENABLE_API
value: 'true'
- name: SPRING_CLOUD_KUBERNETES_SECRETS_PATHS
value: /etc/secrets
- name: SPRING_CLOUD_KUBERNETES_CONFIG_NAME
value: scdf-server
- name: SPRING_CLOUD_DATAFLOW_SERVER_URI
value: 'http://${SCDF_SERVER_SERVICE_HOST}:${SCDF_SERVER_SERVICE_PORT}'
# Add Maven repo for metadata artifact resolution for all stream apps
- name: SPRING_APPLICATION_JSON
value: "{ \"maven\": { \"local-repository\": null,\"remote-repositories\": { \"repo1\": { \"url\": \"https://repo.spring.io/libs-snapshot\"} } } }"
initContainers:
- name: init-mysql-wait
image: busybox
command: ['sh','-c','until nc -w3 -z mysql 3306; do echo waiting for mysql; sleep 3; done;']
serviceAccountName: scdf-sa
volumes:
- name: database
secret:
secretName: mysql
2.4.4 部署Server
完成檔案修改後，就可以執行以下命令部署了：
# 提前下載映象 $ docker pull springcloud/spring-cloud-dataflow-server:2.5.3.RELEASE # 部署Data Flow Server $ kubectl create -f src/kubernetes/server/server-config.yaml $ kubectl create -f src/kubernetes/server/server-svc.yaml $ kubectl create -f src/kubernetes/server/server-deployment.yaml
執行完成，沒有錯誤就可以訪問：http://localhost:30093/dashboard/
3 執行一個Task
檢驗是否部署成功最簡單的方式就是跑一個任務試試。還是按以前的步驟，先註冊應用，再定義Task，然後執行。
我們依舊使用官方已經準備好的應用，但要注意這次我們選擇是的Docker格式，而不是jar包了。
成功執行後，檢視Kubernetes的Dashboard，能看到一個剛建立的Pod：
4 總結
本文通過一步步講解，把Spring Cloud Data Flow成功部署在了Kubernetes上，併成功在Kubenetes上跑了一個任務，再也不再是Local本地單機模式了。
到此這篇關於把Spring Cloud Data Flow部署在Kubernetes上，再跑個任務試試的文章就介紹到這了,更多相關把Spring Cloud Data Flow部署在Kubernetes上，再跑個任務試試內容請搜尋我們以前的文章或繼續瀏覽下面的相關文章希望大家以後多多支援我們！