Domino 4.3 Adds Red Hat OpenShift Kubernetes

Domino Data Lab, provider an open enterprise data science management platform, is releasing Domino 4.3, adding support for the Red Hat OpenShift distribution of Kubernetes and improving model monitoring capabilities.

”Large, sophisticated data science organizations demand flexibility in how they build and deploy their data science stacks. 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,” said Nick Elprin, co-founder and CEO at Domino Data Lab. “We’re obsessed with delivering enterprise-grade security, control, reliability, and observability in a central platform that helps our many Fortune 100 customers unleash the power of data science. We continue to focus, with this release, on helping them accelerate and confidently manage their demanding data science operations.”

Domino offers a data science management platform that centralizes predictive analytics and machine learning (ML) research and development based on an open ecosystem that lets data scientists choose their preferred tools and algorithms while reducing the burden on IT.  

The Domino 4.3 platform includes new capabilities, such as:

  • Expanded Elastic Scaling with Red Hat OpenShift Kubernetes Support: Red Hat OpenShift Kubernetes Engine offers an attractive Kubernetes option for many customers since it can run on virtually all major cloud providers, as well as on-premise deployments. With this release, Domino can now 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.
  • Domino Model Monitor (DMM) Enhancements: Domino Model Monitor (DMM), introduced in June 2020, now has powerful new capabilities that make it easier for enterprises to maintain high-performing ML models on any platform. DMM lets organizations automate the monitoring of model inputs and outputs to detect changes in production data that could signal when a model is no longer producing results that are consistent with current business conditions. Undetected data and model drift are especially problematic during a pandemic, since drastic changes to the economic environment and human behavior increase the likelihood of model inaccuracy and the associated risks of financial loss and a degraded customer experience.
  • Advanced Enterprise-grade authentication and security: Domino broadens its enterprise-grade authentication capabilities to 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. When combined with its robust SSO capabilities, these enhancements make it easier for Domino administrators to grant or revoke user access while limiting where users are able to connect from.

Domino has also significantly enhanced its internal processes and tooling to comply with enterprise application monitoring and security reporting requirements now allowing Domino logs to be exposed to Fluentd-compatible aggregation tools, application health metrics can be integrated into Prometheus monitoring systems, and container and dependencies support vulnerability scanning and remediation.

For more information about all these updates, visit