MLflow
An open-source platform for tracking, evaluating, managing, and deploying machine learning and AI models and workflows.
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Related terms
Experiment Tracking
The process of recording and managing information about AI experiments, including datasets, models, hyperparameters, code versions, metrics, and outcomes to enable reproducibility and comparison.
Model MonitoringThe practice of continuously tracking an AI model's performance, behavior, usage, and operational health in production.
Model RegistryA centralized system for storing, versioning, organizing, and managing AI models and their deployment metadata.
AI ObservabilityThe practice of monitoring, tracing, and analyzing AI systems to understand their behavior, performance, reliability, and operational health in production.