If your modeling problem is that you have too many features, a solution to this problem is LASSO regularization. By forcing some feature coefficients to be zero, you remove them, thus reducing the number of features that you are using in your model. LASSO solves the problem of too many features through feature selection.
What specific problems is ridge regression practically useful for solving? This question is looking for a canonical explanation of what problems ridge regression is used to solve today (in 2018).