Latest Domino Data Lab Release Supports Red Hat OpenShift
- By John K. Waters
Enterprise data science management platform provider Domino Data Lab today released the latest version of its namesake platform. Domino 4.3 comes with new support for the Red Hat OpenShift distribution of Kubernetes, which the company says makes it easy for users to scale data science workloads on any platform. This release also adds new model monitoring capabilities to make it easier for enterprises to maintain high-performing machine learning (ML) models, and it extends IT security features.
The Domino platform was designed to centralize predictive analytics and ML research and development based on an open ecosystem that lets data scientists choose their tools and algorithms, while reducing the burden on IT, Nick Elprin, the company's co-founder and CEO, said in a statement.
"Large, sophisticated data science organizations demand flexibility in how they build and deploy their data science stacks," he said. "Adding Red Hat OpenShift to our wide variety of deployment options gives customers even more flexibility to run on almost any cloud provider or on their own on-prem hardware."
The OpenShift Kubernetes support in this release expands the platform's elastic scaling capabilities. Domino can now take advantage of the capabilities of the Red Hat OpenShift Kubernetes Engine, which offers an appealing Kubernetes option for some customers, because it can run on virtually all major cloud providers, as well as on-premise deployments. Domino 4.3 can take advantage of intelligent Kubernetes orchestration on OpenShift clusters for efficient management and smart utilization of computing resources. "Rapidly scaling containerized workloads is particularly important as the demand for high-powered CPUs, GPUs and RAM can spike dramatically when training models or engineering features, and then quickly scale down once completed," the company said in a statement.
Also, Domino now supports multi-tenant Kubernetes clusters, so a dedicated cluster for installation is not required--an advantage for enterprises that have invested in large, centralized Kubernetes clusters to improve hardware utilization across a large pool of users and application workloads.
This release also comes with enhancements to the recently introduced Domino Model Monitor (DMM), which allow organizations to automate the monitoring of model inputs and outputs to detect changes in production data. And new enterprise-grade authentication and security capabilities include options for certification of Domino APIs and third-party services via short-lived Domino identity (OpenID) tokens to connect to any external authentication service.
More information is available on the company website.
John K. Waters is the editor in chief of a number of Converge360.com sites, with a focus on high-end development, AI and future tech. He's been writing about cutting-edge technologies and culture of Silicon Valley for more than two decades, and he's written more than a dozen books. He also co-scripted the documentary film Silicon Valley: A 100 Year Renaissance, which aired on PBS. He can be reached at [email protected].