Highlights:

  • Domino Data Lab announced the launch of Domino 5.3, a major update that accelerates time-to-value and increases the impact of data science at scale across any cloud or on-premises infrastructure.
  • Domino maximizes the efficiency of data science teams by combining pre-built connections to the most common data sources, sophisticated search features, and integrated data versioning.

Domino Data Lab, the developer of the premier Enterprise MLOps platform trusted by over 20% of the Fortune 100, announced the launch of Domino 5.3. This significant update accelerates time-to-value and enhances the impact of data science at scale across any cloud or on-premises infrastructure.

The recent version of the platform includes a private preview of its Domino Nexus hybrid and multi-cloud capabilities, an expanded suite of connectors to simplify and democratize access to critical data sources, and new GPU inference capabilities to facilitate the production of high-value data science projects, such as deep learning.

Delivering on the vision for hybrid and multi-cloud MLOps

According to industry estimations, most Artificial Intelligence (AI) infrastructure decision-makers feel hybrid cloud support by AI platforms is crucial for their AI strategies. Nexus, Domino’s hybrid and multi-cloud architecture, was recently revealed in June. Nexus facilitates the protection of data sovereignty, minimizes computing costs, and future-proofs of an organization’s infrastructure investments across any cloud or on-premises architecture. Nexus will now be accessible by certain Domino customers only.

Domino Nexus provides businesses with a unified interface for hybrid and multi-cloud MLOps.

Melanie Posey, research director for cloud and amp; managed services transformation at S and amp;P Global Market Intelligence, said, “Organizations are stepping up their hybrid game, with 46% having some on-premises/off-premises architecture currently in place (up from 34% in 2019). Cost optimization across different workload deployment venues is one of the top use cases for a hybrid.”

Nick Elprin, co-founder and CEO of Domino Data Lab, said, “Modern enterprise data science teams need access to a wide variety of data and infrastructure across different clouds, regions, on-premises clusters, and databases. Domino 5.3 allows our customers 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.”

New data sources and GPU-supported model inference accelerate the time-to-value

Domino maximizes the efficiency of data science teams by combining pre-built connections to the most common data sources, sophisticated search features, and integrated data versioning. Domino 5.3 adds to the suite of data connectors launched earlier with new capabilities to connect to Teradata warehouses, Amazon S3 tabular data, and Trino.

Domino also provides an optimal environment for training advanced deep learning models at the cutting-edge of AI and machine learning. Domino 5.3’s new GPU-supported model inference features extend these benefits to model deployment without requiring DevOps expertise. Domino allows the most crucial workloads for the model-driven company by operationalizing deep learning at an enterprise scale.

Enabling compliant data science operations globally and by industry

Participating companies in the Nexus private preview may observe how it enables them to restrict access to data by area, aiding in enforcing data localization and sovereignty rules. In addition, Domino 5.3 introduces new compliance and governance capabilities for pharmaceutical businesses utilizing Domino as a contemporary Statistical Computing Environment. To comply with GxP criteria for regulatory filings for clinical trials, a non-modifiable audit trail outlines who has authorized access to data within a project.

Domino 5.3 is currently available to both new and existing clients.