Why Use Containers, Kubernetes, and OpenShift for AI/ML Workloads?
November 6, 2019 | by
Containers and Kubernetes are proving to be very valuable in helping accelerate Artificial Intelligence (AI) and Machine Learning (ML) lifecycle for organizations worldwide. ExxonMobil, BMW, Volkswagen, Discover Financial Services, Ministry of Defense (Israel), Boston Children’s Hospital, are some organizations have operationalized Red Hat OpenShift, industry leading Kubernetes-based container platform, to accelerate data science workflows, and build intelligent applications. These intelligent applications are helping achieve key business goals and providing competitive differentiation.
In a recent blog, I explained how these emerging cloud-native technologies are playing a vital role in helping solve ML Lifecycle execution challenges, and accelerate the delivery of intelligent applications. You may be thinking…”ok, so where do we start to learn about this topic?”
To help you get started on this journey, we have developed a short video that explains in under three minutes how containers, Kubernetes, and OpenShift can accelerate AI/ML initiatives for your organization. Whether you are working at your desk, driving, riding on a train, walking, or something else, this quick video will do the job for you! As always, feedback is highly appreciated.
The image garbage collector is one of two mechanisms present in every kubernetes cluster node trying to maintain enough available space in the local disks for normal operations to continue. The other ...