Cloudera Expands Machine Learning Abilities for MLOps

Cloudera, the enterprise data cloud company, is releasing an expanded set of production machine learning capabilities for MLOps, now available in Cloudera Machine Learning (CML).

Organizations can manage and secure the ML lifecycle for production machine learning with CML's new MLOps features and Cloudera SDX for models.

Data scientists, machine learning engineers, and operators can collaborate in a single unified solution, drastically reducing time to value and minimizing business risk for production machine learning models.

The release of Cloudera Machine Learning with new MLOps features and Cloudera SDX for models provides a fundamental set of model and lifecycle management capabilities to enable the repeatable, transparent, and governed approaches necessary for scaling model deployments and ML use cases.

Benefits include:

  • Unique model cataloging and lineage capabilities allow visibility into the entire ML lifecycle to eliminate silos and blind spots for full lifecycle transparency, explainability and accountability.
  • Full end-to-end machine learning lifecycle management that includes everything required to securely deploy machine learning models to production, ensure accuracy, and scale use cases.
  • A first-class model monitoring service designed to track and monitor both technical aspects and accuracy of predictions in a repeatable, secure, and scalable way.
  • Built on a 100% open source standard and fully integrated with Cloudera Data Platform, enabling customers to integrate into existing and future tooling while not being locked into a single vendor.

"Cloudera has been working across our industry and with some of our largest customers and partners to build open standards for machine learning metadata," said Arun Murthy, chief product officer, Cloudera. "We have implemented those standards as part of Cloudera Machine Learning to deliver everything enterprises need for deploying and sustaining machine learning models in production at scale. With first-class model deployment, security, governance, and monitoring, this is the first end-to-end ML solution for full-lifecycle management from data to ML driven business impact across hybrid and multi-cloud."

The expanded set of production machine learning capabilities available in Cloudera Machine Learning (CML) include new MLOps features for monitoring the functional and business performance of machine learning models and more.

For more information about this release, visit