K8S原来如此简单（五）Metrics Server与HPA

查看Node资源消耗： 
kubectl top node k8s-node1 
查看Pod资源消耗： 
kubectl top pod k8s-node1

需要注意的是，使用这个命令我们需要安装metrics server，否则会提示
Metrics API不可用。

kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

kubectl get pod --all-namespaces |grep metrics

kubectl top pod chesterdeployment-75c64cc8b6-k4jqw -n chesterns

安装好之后，我们可以看到已经可以正常使用kubectl top命令了。下面我们
开始演示通过hpa来模拟根据cpu自动水平扩展。


仍然使用之前课程的deployment，需要修改deployment的副本数为1

apiVersion: apps/v1
kind: Deployment
metadata:
  name: chesterdeployment
  namespace: chesterns
  labels:
    app: chesterapi
spec:
  replicas: 1
  selector:
    matchLabels:
      app: chesterapi
  template:
    metadata:
      labels:
        app: chesterapi
    spec:
     containers:
     - name: oneapi
       image: registry.cn-beijing.aliyuncs.com/chester-k8s/oneapi:latest
       ports:
       - containerPort: 5000
       livenessProbe:
         httpGet:
           path: /test
           port: 5000
应用deployment
kubectl apply -f deployment.yaml
在我们的oneapi里有一个highcpu的接口，可以帮助我们实现高cpu操作

    [HttpGet("highcpu")]
    public string HighCpu(int minutes)
    {
        var now = DateTime.Now;
        while (DateTime.Now - now <= TimeSpan.FromMinutes(minutes))
        {
            _logger.LogInformation(DateTime.Now.ToString());
        }
        return "ok";
    }

curl clusterip:5000/test/highcpu?minutes=1

kubectl top pod chesterdeployment-75c64cc8b6-k4jqw -n chesterns

创建HPA

下面我们创建hpa，让其实现自动扩展
apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: chesterhpa
  namespace: chesterns
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: chesterdeployment
  minReplicas: 1
  maxReplicas: 3
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: AverageValue
        averageValue: 200m

curl clusterip:5000/test/highcpu?minutes=3

kubectl describe hpa chesterhpa -n chesterns
kubectl get pods --namespace=chesterns
kubectl top pod  -n chesterns