Domino Data Lab, a provider of an enterprise MLOps platform, today at NVIDIA’s GTC, a global conference on AI and the Metaverse, announces new updates giving every enterprise access to open-source tools and techniques to achieve AI value sooner.
Domino’s Spring 2023 release expands enterprise-grade support for open-source ML tools — Ray 2.0, MLflow, and Feast’s feature store — used to develop today’s most advanced AI apps. Additionally, Domino Cloud, a fully-managed MLOps platform-as-a-service is available for fast and easy data science at scale. Finally, Domino’s hybrid- and multi-cloud Nexus capability is generally available with fractional GPU options.
Domino now supports version 2.0 of the Ray open-source framework that enables data science teams to develop and train generative AI models at scale, including ChatGPT. The integration with Domino’s on-demand, auto-scaling compute clusters streamlines the development process, while it supports data preparation via Apache Spark and machine learning and deep learning via XGBoost, TensorFlow and PyTorch.
Domino’s integration with MLflow simplifies machine learning lifecycle management for data scientists. It enables data science teams to track, reproduce and share machine-learning experiments and artifacts within their Domino projects, while Domino’s security layer ensures metrics, logs and artifacts are secured.
Feast, an open-source feature store for machine learning, integrates natively within Domino, providing users with easy access to query and transform ML features. This integration allows teams to reuse feature logic consistently and efficiently across data science projects while tracking feature lineage and ensuring data accuracy and security, as well as cost savings from not re-computing business logic for each feature.
Domino also launched Domino Cloud, a fully managed software-as-a-service version of its MLOps platform. It reduces AI time-to-value by providing scalable resources and a secure, governed enterprise-grade platform without any platform setup or management investment.
Customers can save costs by paying only for the compute used while accessing GPUs and distributed computing frameworks. Domino Cloud eliminates the need for data science teams to worry about deploying, upgrading, or managing infrastructure, allowing them to focus on their core responsibilities.
Announced in June 2022 with NVIDIA as the first launch partner, Domino Nexus is generally available to enterprises with powerful accelerated computing for workloads like generative AI across hybrid- and multi-cloud environments. A member of the NVIDIA AI Accelerated program, Domino workloads can be deployed from data centers to the edge, with seamless workload migration across cloud and on-premises environments.
Domino also announced new cost- and performance-enhancing Nexus capabilities via validation with Vultr, an independent cloud computing platform. It enables Domino Nexus customers to burst to Vultr Cloud with virtualized fractional NVIDIA A100 Tensor Core GPUs.
The combination of Domino’s Enterprise MLOps platform, Vultr infrastructure, the NVIDIA NGC catalog, and the NVIDIA AI Enterprise software suite makes innovations in generative AI, computer vision and more accessible and affordable for all enterprises. Data science teams can focus on delivering business impact, while IT has confidence in a validated solution architecture giving granular governance over cost, performance, and security.
Domino’s Spring 2023 release (Domino 5.5), Domino Cloud and Domino Nexus are all available today. MLflow experiment tracking and Feast feature store integration are available in preview. The Domino and Vultr solution will be available later this year.
For more information, visit www.dominodatalab.com
