Batch Normalization vs. Constraints

I understand that Batch Normalization prevents weights from getting too skewed and keeps your model from diverging. How does this compare to imposing constraints on the weights: ( ?

  1. Any intuition on when batch norm works better than constraints and vice versa?

  2. Is it my correct understanding that it would be somewhat redundant to use both constraints and batch norm?