这个方法主要分为两部分，一部分是调用stabilizeRecommendationWithBehaviors方法来根据时间窗口来获取一个建议副本数；另一部分convertDesiredReplicasWithBehaviorRate方法是根据scaleDown或scaleUp指定的参数做限制。
stabilizeRecommendationWithBehaviors
func (a *HorizontalController) stabilizeRecommendationWithBehaviors(args NormalizationArg) (int32, string, string) { recommendation := args.DesiredReplicas foundOldSample := false oldSampleIndex := 0 var scaleDelaySeconds int32 var reason, message string var betterRecommendation func(int32, int32) int32 // 如果期望的副本数大于等于当前的副本数,则延迟时间=scaleUpBehaviro的稳定窗口时间 if args.DesiredReplicas >= args.CurrentReplicas { scaleDelaySeconds = *args.ScaleUpBehavior.StabilizationWindowSeconds betterRecommendation = min reason = "ScaleUpStabilized" message = "recent recommendations were lower than current one, applying the lowest recent recommendation" } else { // 期望副本数<当前的副本数 scaleDelaySeconds = *args.ScaleDownBehavior.StabilizationWindowSeconds betterRecommendation = max reason = "ScaleDownStabilized" message = "recent recommendations were higher than current one, applying the highest recent recommendation" } //获取一个最大的时间窗口 maxDelaySeconds := max(*args.ScaleUpBehavior.StabilizationWindowSeconds, *args.ScaleDownBehavior.StabilizationWindowSeconds) obsoleteCutoff := time.Now().Add(-time.Second * time.Duration(maxDelaySeconds)) cutoff := time.Now().Add(-time.Second * time.Duration(scaleDelaySeconds)) for i, rec := range a.recommendations[args.Key] { if rec.timestamp.After(cutoff) { // 在截止时间之后，则当前建议有效, 则根据之前的比较函数来决策最终的建议副本数 recommendation = betterRecommendation(rec.recommendation, recommendation) } //如果被遍历到的建议时间是在obsoleteCutoff之前，那么需要重新设置建议 if rec.timestamp.Before(obsoleteCutoff) { foundOldSample = true oldSampleIndex = i } } //如果被遍历到的建议时间是在obsoleteCutoff之前，那么需要重新设置建议 if foundOldSample { a.recommendations[args.Key][oldSampleIndex] = timestampedRecommendation{args.DesiredReplicas, time.Now()} } else { a.recommendations[args.Key] = append(a.recommendations[args.Key], timestampedRecommendation{args.DesiredReplicas, time.Now()}) } return recommendation, reason, message }这个方法首先会去校验当前是扩容还是缩容，如果是扩容，那么将scaleDelaySeconds设置为ScaleUpBehavior的时间，并将betterRecommendation方法设置为min；如果是缩容那么则相反。
然后会遍历建议，如果建议时间在窗口时间cutoff之后，那么需要调用betterRecommendation方法来获取建议值，然后将获取到的最终结果返回。
convertDesiredReplicasWithBehaviorRate
func (a *HorizontalController) convertDesiredReplicasWithBehaviorRate(args NormalizationArg) (int32, string, string) { var possibleLimitingReason, possibleLimitingMessage string //如果期望副本数大于当前副本数 if args.DesiredReplicas > args.CurrentReplicas { //获取预期扩容的pod数量 scaleUpLimit := calculateScaleUpLimitWithScalingRules(args.CurrentReplicas, a.scaleUpEvents[args.Key], args.ScaleUpBehavior) if scaleUpLimit < args.CurrentReplicas { // We shouldn't scale up further until the scaleUpEvents will be cleaned up scaleUpLimit = args.CurrentReplicas } maximumAllowedReplicas := args.MaxReplicas if maximumAllowedReplicas > scaleUpLimit { maximumAllowedReplicas = scaleUpLimit possibleLimitingReason = "ScaleUpLimit" possibleLimitingMessage = "the desired replica count is increasing faster than the maximum scale rate" } else { possibleLimitingReason = "TooManyReplicas" possibleLimitingMessage = "the desired replica count is more than the maximum replica count" } if args.DesiredReplicas > maximumAllowedReplicas { return maximumAllowedReplicas, possibleLimitingReason, possibleLimitingMessage } } else if args.DesiredReplicas < args.CurrentReplicas { //获取预期缩容的pod数量 scaleDownLimit := calculateScaleDownLimitWithBehaviors(args.CurrentReplicas, a.scaleDownEvents[args.Key], args.ScaleDownBehavior) if scaleDownLimit > args.CurrentReplicas { // We shouldn't scale down further until the scaleDownEvents will be cleaned up scaleDownLimit = args.CurrentReplicas } minimumAllowedReplicas := args.MinReplicas if minimumAllowedReplicas < scaleDownLimit { minimumAllowedReplicas = scaleDownLimit possibleLimitingReason = "ScaleDownLimit" possibleLimitingMessage = "the desired replica count is decreasing faster than the maximum scale rate" } else { possibleLimitingMessage = "the desired replica count is less than the minimum replica count" possibleLimitingReason = "TooFewReplicas" } if args.DesiredReplicas < minimumAllowedReplicas { return minimumAllowedReplicas, possibleLimitingReason, possibleLimitingMessage } } return args.DesiredReplicas, "DesiredWithinRange", "the desired count is within the acceptable range" }