Domino’s ML Ops platform to support hybrid and multi-cloud infrastructure
Domino Data Lab, a provider of an enterprise-scale ML Ops platform, has released a new upgrade to its platform that will improve the time-to-value and unite hybrid and multi-cloud infrastructure. The latest upgrade to Domino MLOps platform will be commercially available to help enterprise customers in their AI journey.
According to the company, the ML Ops platform is currently adopted by more than 20 percent of the Fortune 100 companies. Domino 5.3 version will expand the multi-cloud capabilities to democratize data sources and accelerate deep learning implementation. The platform will give a private preview of Domino Nexus, a hybrid and multi-cloud architecture to enable enterprises to protect edge data.
“Modern enterprise data science teams need access to a wide variety of data and infrastructure across different clouds, regions, on-premises clusters and databases,” said Nick Elprin, co-founder and CEO of Domino Data Lab. “Domino 5.3 gives our customers the ability to use the data and compute they need wherever it lives, so they can increase the speed and impact of data science without sacrificing security or cost efficiency.”
Domino Data Lab has introduced several new functionalities in the Domino 5.3 platform.
The company has provided pre-built connectors for the popular data source, advanced search capabilities, and integrated data versioning for data science engineering teams that bring more value to the existing deployment.
Domino 5.3 offers GPU-backed model inference capabilities for faster model deployment, requiring minimum DevOps skills, according to the company. New compliance and governance feature functionality for pharmaceutical companies that rely on the company’s modern Statistical Computing Environment have also been added.
Domino Nexus is a single platform that lets users control data science and machine learning workloads deployed in the cloud or on-premise. It behaves as a single pane of glass to enable enterprise customers to build, deploy and monitor the AI and data science models. The platform is designed to reduce cloud infrastructure costs for computation-intensive ML workloads and increases the utilization of on-premise infrastructure for high-performance applications.
Integrating hybrid and multi-cloud MLOps infrastructure brings operational efficiency and reduces IT workloads; also, enterprises believe hybrid cloud support by AI platforms is important for their AI strategy, Domino executives said.
“Cost optimization across different workload deployment venues is one of the top use cases for hybrid cloud,” said Melanie Posey, research director for cloud & managed services transformation at S&P Global Market Intelligence.
Domino announced Nexus in June, but it is now available only to select Domino platform customers.
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Article Topics
cost management | Domino Data Labs | hybrid cloud | infrastructure | ML Ops
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