Domino Data Lab has announced a new Kubernetes-native compute grid that supports elastic scaling for data science workloads in any of the major cloud platforms as well as on-prem. The product enables Domino to run with the full benefits of elastic scaling of heterogeneous data science workloads. It also, according to the provider, packs workloads smartly across underlying hardware to run them more efficiently. As a result, Domino can now be installed into a company’s existing kubernetes cluster.
Domino Data Lab is an enterprise data science platform that allows data scientists to build and run predictive models. Its product helps organizations with the development and delivery of these models via infrastructure automation and collaboration. Domino provides users access to a Data Science Workbench that provides open source and commercial tools for batch experiments, as well as Model Delivery so they can publish APIs and web apps or schedule reports.
In a press statement, the company’s CEO and co-founder Nick Elprin said of the new Domino Data Compute Grid: “At Domino, we are committed to empowering data science teams while giving IT leaders a leading-edge platform to realize their vision for modern enterprise infrastructure. We are proud to offer the most advanced data science platform on Kubernetes, giving data scientists and IT the agility model-driven businesses need.”
Domino Data Lab was recently featured in the 2019 Forbes AI 50. In order to qualify for inclusion, companies needed to prove that technologies like machine learning, natural language processing and computer vision make up the core of their product. The company was also prominently named in Gartner’s 2019 Magic Quadrant for Data Science and Machine Learning Platforms, and Solutions Review named Domino a Vendor to Watch this year.
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