DataRobot MLOps delivers the capabilities that Data Science and IT Ops teams need to work together to deploy, monitor, and manage machine learning models in production and to govern their use in production environments. With DataRobot MLOps and Governance, companies can:
Easily deploy machine learning projects from any ML platform on modern production infrastructures such as Kubernetes and Spark on any cloud or on-premise.
Monitor ML-based applications for performance issues with ML-centric capabilities like data drift analysis, model-specific metrics and infrastructure monitoring and alerts.
Manage the dynamic nature of machine learning applications with the ability to frequently update models, test new, competitive models, and change applications on-the-fly while continuing to serve business applications.
Enforce governance policies related to ML deployment and capture the data that is required for strong governance practices, including who is publishing models, why changes are being made, and what models were in place over time.