Kubeflow enables the efficient running of ML workloads. Kubeflow on OpenShift Container Platform offers several advantages for teams that need an enterprise-ready ML/DL platform:
- Running ML workloads in the same environment as the rest of the organization’s applications reduces IT complexity.
- Using Kubernetes as the underlying platform makes it easier for an ML engineer to develop a model locally on their development platform before deploying the application to a production Kubernetes environment such as OpenShift.
- The performance capabilities of the Intel Scalable processors combined with Intel Optimized Tensorflow distribution facilitate higher data scientist productivity by reducing model training times.