Better, faster, less wrong: Enhancing issue grouping

Sentry upgraded its ML model for grouping errors into issues. The new model prevents 20% more duplicate issues from being created and halves the rate of incorrect merges. The model uses a transformer-based text embeddings approach to balance undergrouping and overgrouping.