优化 Kubernetes 横向扩缩容 HPA

// 获取Pod resource request
func calculatePodRequests(pods []*v1.Pod, resource v1.ResourceName) (map[string]int64, error) {
 requests := make(map[string]int64, len(pods))
 for _, pod := range pods {
  podSum := int64(0)
  for _, container := range pod.Spec.Containers {
   if containerRequest, ok := container.Resources.Requests[resource]; ok {
    podSum += containerRequest.MilliValue()
   } else {
    return nil, fmt.Errorf("missing request for %s", resource)
   }
  }
  requests[pod.Name] = podSum
 }
 return requests, nil
}
// 计算使用率
func GetResourceUtilizationRatio(metrics PodMetricsInfo, requests map[string]int64, targetUtilization int32) (utilizationRatio float64, currentUtilization int32, rawAverageValue int64, err error) {
 metricsTotal := int64(0)
 requestsTotal := int64(0)
 numEntries := 0

 for podName, metric := range metrics {
  request, hasRequest := requests[podName]
  if !hasRequest {
   // we check for missing requests elsewhere, so assuming missing requests == extraneous metrics
   continue
  }

  metricsTotal += metric.Value
  requestsTotal += request
  numEntries++
 }


 currentUtilization = int32((metricsTotal * 100) / requestsTotal)

 return float64(currentUtilization) / float64(targetUtilization), currentUtilization, metricsTotal / int64(numEntries), nil
}

metricsTotal = sum(pod.container.metricValue)
requestsTotal = sum(pod.container.Request)
currentUtilization = int32((metricsTotal * 100) / requestsTotal)

func (a *HorizontalController) Run(stopCh <-chan struct{}) {
  // ...
 // start a single worker (we may wish to start more in the future)
 go wait.Until(a.worker, time.Second, stopCh)

 <-stopCh
}

期望副本数 = ceil[当前副本数 * (当前指标 / 期望指标)]