Implementa una aplicación de Kubernetes con conectores de Workflows

Crea un clúster de GKE con el conector de la API de Kubernetes Engine y crea una implementación y un servicio de Kubernetes con el conector de la API de Kubernetes.

Muestra de código

YAML

# This workflow demonstrates how to:
# 1- Use the Kubernetes Engine API connector to create a GKE cluster.
# 2- Use the Kubernetes API connector to create a Kubernetes deployment and
# a service.

main:
  steps:
    - init:
        assign:
          - project_id: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
          - cluster_location: "us-central1"
          - cluster_id: "workflows-cluster"
          - cluster_full_name: ${"projects/" + project_id + "/locations/" + cluster_location + "/clusters/" + cluster_id}
    - create_k8s_cluster:
        call: googleapis.container.v1.projects.locations.clusters.create
        args:
          body:
            cluster:
              name: ${cluster_id}
              initial_node_count: 1
              autopilot:
                enabled: true
          parent: ${"projects/" + project_id + "/locations/" + cluster_location}
    - assert_running:
        call: assert_cluster_status
        args:
          expected_status: "RUNNING"
          cluster_id: ${cluster_id}
          cluster_full_name: ${cluster_full_name}
    - create_deployment:
        call: gke.request
        args:
          project: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
          cluster_id: ${cluster_id}
          location: ${cluster_location}
          method: "POST"
          path: "/apis/apps/v1/namespaces/default/deployments"
          body:
            kind: Deployment
            metadata:
              name: nginx-deployment
              labels:
                app: nginx
            spec:
              replicas: 3
              selector:
                matchLabels:
                  app: nginx
              template:
                metadata:
                  labels:
                    app: nginx
                spec:
                  containers:
                  - name: nginx
                    image: nginx:1.14.2
                    ports:
                    - containerPort: 80
        result: create_deployment_result
    - create_service:
        call: gke.request
        args:
          project: ${sys.get_env("GOOGLE_CLOUD_PROJECT_ID")}
          cluster_id: ${cluster_id}
          location: ${cluster_location}
          method: "POST"
          path: "/api/v1/namespaces/default/services"
          body:
            kind: Service
            apiVersion: v1
            metadata:
              name: nginx-service
            spec:
              ports:
              - name: http
                port: 80
                targetPort: 80
              selector:
                app: nginx
              type: LoadBalancer
        result: create_service_result
    - return_multiple_values:
        return:
          create_deployment_result: ${create_deployment_result}
          create_service_result: ${create_service_result}

assert_cluster_status:
  params:
    [expected_status, cluster_id, cluster_full_name]
  steps:
    - get_cluster:
        call: googleapis.container.v1.projects.locations.clusters.get
        args:
          clusterId: ${cluster_id}
          name: ${cluster_full_name}
        result: cluster
    - compare:
        switch:
          - condition: ${cluster.status == expected_status}
            next: end
    - fail:
        raise: ${"Expected VM status is " + expected_status + ". Got " + cluster.status + " instead."}

¿Qué sigue?

Si quieres buscar y filtrar muestras de código para otros productos de Google Cloud , consulta el navegador de muestras deGoogle Cloud .