Capítulo 1: Fundamentos de Kubernetes

Conceptos fundamentales

Despliegue de modelos de ML

apiVersion: apps/v1
kind: Deployment
metadata:
  name: churn-model
  labels:
    app: churn-model
spec:
  replicas: 3
  selector:
    matchLabels:
      app: churn-model
  template:
    metadata:
      labels:
        app: churn-model
    spec:
      containers:
      - name: model-server
        image: mlplatform/churn-model:v2.1.0
        ports:
        - containerPort: 8080
        resources:
          requests:
            memory: "2Gi"
            cpu: "1"
          limits:
            memory: "4Gi"
            cpu: "2"
        env:
        - name: MODEL_PATH
          value: "/models/churn_model.pkl"
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 5
---
apiVersion: v1
kind: Service
metadata:
  name: churn-model-service
spec:
  selector:
    app: churn-model
  ports:
  - port: 80
    targetPort: 8080
  type: LoadBalancer

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Siguiente: Capítulo 2: Kubeflow