Contributed a performance optimization to the mlflow/mlflow repository by implementing a composite index on the metrics table, targeting the (run_uuid, key) columns with step ordering to accelerate metric history queries. This change reduced latency for metric-tracking workloads, enabling faster dashboards and historical analyses for experiment tracking. The work involved SQL for index creation, data modeling to ensure efficient query patterns, and database management to maintain integrity and performance. Collaborated closely with other contributors through co-authored commits and sign-offs, demonstrating end-to-end ownership from design through implementation and review, with a focus on code quality and alignment with project performance goals.