April 2026 monthly summary for harupy/mlflow focusing on cost reporting accuracy and model catalog expansion. Delivered targeted fixes to improve token usage reporting for Anthropic integration and expanded model access by integrating Bedrock Converse models into the catalog.

March 2026 performance summary focused on strengthening traceability and user attribution in the MLflow ingestion pipeline. Delivered a targeted enhancement to map the OpenTelemetry user ID to MLflow trace metadata, improving end-to-end user tracking and data lineage without impacting ingestion latency. No major bugs fixed this month; ongoing improvements to the OTel ingestion path and observability groundwork were laid for future features. Overall business impact includes clearer data lineage and more reliable analytics for experiments, enabling better attribution and decision-making. Technologies demonstrated include OpenTelemetry integration, MLflow tracing, Python data ingestion, and disciplined commit hygiene (signed-off commits and co-authors).