D2iQ, the leading enterprise Kubernetes provider for smart cloud-native applications, announced version 2.0 of Kaptain AI/ML, the enterprise-ready distribution of open-source Kubeflow that enables organizations to develop, deploy, and run artificial intelligence (AI) and machine learning (ML) workloads in production environments.
Powered by Kubeflow 1.5, the Kubernetes machine learning toolkit, Kaptain AI/ML now provides data science teams with features such as expanded control for mounting data volumes and increased visibility into idle notebooks, so they can spend more time developing and less time managing infrastructure. The enhanced user experience enables data scientists to more effectively manage the lifecycle of AI and ML models without the need for infrastructure knowledge and skill sets.
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By simplifying the deployment and full lifecycle management of AI and ML workloads at scale, Kaptain AI/ML 2.0 accelerates the impact of smart cloud-native applications. This enables organizations to drive better business results by more quickly delivering new smart products and services, becoming more agile when updating models, and driving smarter customer experiences.
“The ability to rapidly scale workloads while remaining agile and reliable makes Kubernetes a natural fit for artificial intelligence and machine learning,” said Deepak Goel, CTO of D2iQ. “Kaptain AI/ML 2.0 represents our continued innovation around improving the customer experience. By making it easier to deploy and manage AI and ML workloads across various Kubernetes platforms, Kaptain AI/ML 2.0 reduces complexity and removes operational barriers, enabling organizations to more quickly achieve success in production environments.”
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Through integration with the newly enhanced D2iQ Kubernetes Platform (DKP), Kaptain AI/ML 2.0 can be deployed across multi-cluster environments on any CNCF-certified Kubernetes platform, including Amazon Elastic Kubernetes Service (EKS) and Microsoft Azure Kubernetes Service (AKS). Additionally, Kaptain AI/ML 2.0 offers easier installation via Helm and DKP catalog integration. These new capabilities provide more productivity, flexibility, and choice when deploying Kaptain AI/ML in Kubernetes environments.
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