SageMaker adds live MLflow tracking for benchmark and inference jobs

AWS published guidance for streaming metrics from SageMaker AI benchmark jobs and optimized inference recommendation jobs directly into MLflow.

The integration is designed to give teams a unified tracking interface for model-serving experiments, including metrics, parameters, and charts as jobs run.

For production AI teams, this reduces the gap between performance testing and experiment management, especially when comparing deployment options for inference workloads.