Method autoscaleFn

pkg/autoscaler/autoscaler.go:145–286

(api userconfig.Resource)

}

func (a *Autoscaler) autoscaleFn(api userconfig.Resource) (func() error, error) {
	log := a.logger.With(
		zap.String("apiName", api.Name),
		zap.String("apiKind", api.Kind.String()),
	)

	scaler, ok := a.scalers[api.Kind]
	if !ok {
		return nil, errors.ErrorUnexpected(
			fmt.Sprintf("autoscaler does not have a scaler for the %s kind", api.Kind),
		)
	}

	log.Info("autoscaler init")

	var startTime time.Time
	a.recs[api.Name] = newRecommendations()

	return func() error {
		autoscalingSpec, err := scaler.GetAutoscalingSpec(api.Name)
		if err != nil {
			return errors.Wrap(err, "failed to get autoscaling spec")
		}

		currentRequestedReplicas, err := scaler.CurrentRequestedReplicas(api.Name)
		if err != nil {
			return errors.Wrap(err, "failed to get current replicas")
		}

		if startTime.IsZero() {
			startTime = time.Now()
		}

		avgInFlight, err := scaler.GetInFlightRequests(api.Name, autoscalingSpec.Window)
		if err != nil {
			return errors.Wrap(err, "failed to get in-flight requests")
		}
		if avgInFlight == nil {
			log.Debug("autoscaler tick: metrics not available yet")
			return nil
		}

		rawRecommendation := *avgInFlight / *autoscalingSpec.TargetInFlight
		recommendation := int32(math.Ceil(rawRecommendation))

		if rawRecommendation < float64(currentRequestedReplicas) && rawRecommendation > float64(currentRequestedReplicas)*(1-autoscalingSpec.DownscaleTolerance) {
			recommendation = currentRequestedReplicas
		}

		if rawRecommendation > float64(currentRequestedReplicas) && rawRecommendation < float64(currentRequestedReplicas)*(1+autoscalingSpec.UpscaleTolerance) {
			recommendation = currentRequestedReplicas
		}

		// always allow subtraction of 1
		downscaleFactorFloor := libmath.MinInt32(currentRequestedReplicas-1, int32(math.Ceil(float64(currentRequestedReplicas)*autoscalingSpec.MaxDownscaleFactor)))
		if recommendation < downscaleFactorFloor {
			recommendation = downscaleFactorFloor
		}