Understanding cross-validation properly

I know I should use cross-validation to evaluate my model, but I'm confused about:

1. What's the difference between k-fold and stratified k-fold?
2. Should I do cross-validation before or after feature selection?
3. How do I cross-validate when doing hyperparameter tuning?

What's the right workflow to avoid data leakage?