D2iQ Brings Machine Learning to Kubernetes - Container Journal

D2iQ has added a curated distribution of Kubeflow, open source software that makes it easier to deploy workflows that incorporate machine learning algorithms on a Kubernetes cluster, as an extension to its existing portfolio of automation tools. Jie Yu, chief architect for D2iQ, says KUDO for Kubeflow will make it easier for IT teams to deploy workloads that include frameworks such as Spark and Horovod on Kubernetes clusters. At the core of KUDO for Kubeflow is Kommander, a role-based tool that provides centralized management, governance and visibility into disparate Kubernetes regardless of where they are running. IT organizations that are building and deploying artificial intelligence (AI) applications based on machine learning algorithms have embraced containers to simplify building and managing all the elements of what otherwise would be a massive monolithic application that would be too unwieldy to build, update and deploy. Kubernetes, meanwhile, has become the de facto default standard for orchestrating containers.