on OpenShift

Operationalizing AI/ML for the enterprise with and OpenShift Joint MLOps solution

Red Hat OpenShift Solution

About and Red Hat

Red Hat OpenShift, the leading hybrid cloud, enterprise Kubernetes application platform allows data scientists to launch flexible, container-based jobs and pipelines, as well as enabling infrastructure teams to manage and monitor ML workloads in a single managed and cloud-native environment.

As a Red Hat Certified Operator, then enables data scientists to rapidly launch ML workloads on remote clusters without tinkering with infrastructure or complicated configuration.

For infrastructure teams, provides the ability to manage all ML compute resources in a unified and secure environment with advanced monitoring and administration capabilities built in.

About and Red Hat

Save time on DevOps with MLOps on Openshift offers data scientists execution of a complete pipeline on DGX systems without any need to understand the infrastructure, DevOps semantics or any resource conflicts or dependencies. Industry known tools and GUI are used for each stage of the pipeline, optimizing the data scientists’ experience and eliminating the learning curve for new tools/GUI.

Save time on DevOps with MLOps on Openshift
"The AI infrastructure ecosystem is growing rapidly. We’re collaborating with as part of our OperatorHub to help provide an end-to-end MLOps solution that data scientists, IT and DevOps engineers need to effectively manage, build and deploy machine learning at the enterprise level, is a great choice for OpenShift and GPU’s to run ML workloads, and enables enhanced collaboration between data scientists and engineers for accelerated ML deployment across hybrid cloud.”
Tushar Katarki
Tushar Katarki
Product Manager, Red Hat OpenShift

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