public Load loadAdjustment() {
        if (nodeTimeseries().measurementsPerNode() < 0.5) return Load.one(); // Don't change based on very little data
        Load adjustment = peakLoad().divide(idealLoad());
        if (! safeToScaleDown())
            adjustment = adjustment.map(v -> v < 1 ? 1 : v);
        return adjustment;
    }
The central decision made in autoscaling.

@return the relative load adjustment that should be made to this cluster given available measurements.
        For example, a load adjustment of 2 means we should allocate twice the amount of that resources.
node-repository/src/main/java/com/yahoo/vespa/hosted/provision/autoscale/ClusterModel.java