D2iQ has announced the general availability of D2iQ Kaptain, the cloud native end-to-end platform for running ML workloads on Kubernetes.

According to the company, D2iQ Kaptain combines all of the open source components required to accelerate the development, training, tuning and deployment of ML models in the enterprise, cutting the time from prototype to production from months to minutes.

D2iQ Kaptain provides data scientists with a familiar, notebook-first approach that has been fully tested and integrated with all the shared resources and data access controls required to build and share models. This enables data scientists to manage the lifecycle of their machine learning models without a need for Kubernetes or production infrastructure knowledge.

D2iQ Kaptain is powered by an opinionated subset of Kubeflow, the open source machine learning toolkit for Kubernetes, while also including all of the Day 2 ready features provided by the D2iQ Konvoy Kubernetes distribution and additional production-focused components such as Horovod and Spark.

This combination empowers platform operators and data scientists with an enterprise-grade Kubernetes foundation.

D2iQ Kaptain is now available.