Cloud Data Science
Domino's Enterprise MLOps Platform serves as the front end to the cloud, automating elastic compute designed for data science workloads, while letting IT monitor and control resource usage.
Hybrid and Multi-Cloud Infrastructure
Data science across any cloud, region, or on-premises
A recent survey found that 71% of AI infrastructure decision-makers view hybrid cloud support as important for their AI strategy, of which 29% say it’s already critical.
Domino Nexus is a single pane of glass that unifies data science silos across the enterprise, so you have one place to build, deploy, and monitor models. Protect data sovereignty, reduce compute spend, and future-proof your infrastructure.
Self-serve elastic compute
One-click access to scalable compute
Say goodbye to DevOps learning curves and wait times. Stop trying to guess compute needs in advance. With Domino, you can self-serve dynamically adjusting Kubernetes-based compute clusters with just a few clicks. You can easily access distributed frameworks such as Spark, Ray 2.0, and Dask, as well as NVIDIA GPUs, to power the most computationally hungry algorithms.
IT immediately benefits from centralized infrastructure management that optimizes resource use and facilitates chargeback to business units based on usage.
Accelerate Research with Elastic Compute
Getting data scientists quickly to work on solving business problems is key for scaling data science and driving business impact.
Domino’s data science workbench provides the flexibility and power that data scientists need to accelerate research. They are free to use the tools they want, on hardware optimized for the task at hand, in a governed and scalable environment that fosters reproducibility, reusability, and collaboration. With elastically scaled compute at their fingertips and MLFlow integration, they can run hundreds of machine learning experiments in parallel and easily compare the results, maximizing their productivity.
Integration with Feast provides a single source of truth for features in the organization, driving reuse, consistency, and reproducibility.
Model and App Deployment
Deploy to Production at Scale
With Domino, you can accelerate processes to create, manage, scale, and secure production models. Models are easily deployed through scalable APIs, Apps, and Launchers, or exported as Docker images to CI/CD pipelines, AWS Sagemaker, or other infrastructure. Interactive, scalable Apps created with Shiny, Dash, and Flask make it easy for non-technical users to interact with models.
Domino handles horizontal scalability, high availability, security, and everything else you shouldn't need to worry about.
Resource Management & Cost Control
Domino automatically spins down machines when analyses finish, so you avoid runaway costs when users forget to stop them. Configure limits on different types of hardware to avoid unexpected costs. View utilization at a point in time or historically by user and project and track compute costs across different projects and users for internal chargeback.
Cloud data science resources
DBRS Accelerates Data Science Domino on AWS
Moving Data Science to the Cloud
How AES went from Zero to 50 Deployed Models in Two Years