Gradient Boosted Tree Algorithm performance

I am working with Gradient boosted tree (GBT), and it performs better (5-Fold CV) on most of my datasets with high metrics like AUC (1.0), kappa (0.971), etc. I can correlate the results with the capabilities of GBT like regularization and sequential learning. I even set aside 30 percent data for testing after five-fold cross-validation and got kappa (0.974) for this unseen data.
 My question is, are there any cautions or factors that need to be considered while using and interpreting results of a GBT and how good is GBT in real applications? 

Thanks