Powerful infrastructure at your fingertips
Data scientists are more productive with easy access to their preferred tools, scalable compute, and diverse data sets. By automating time-consuming and tedious DevOps tasks they focus more on innovation.
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 for model training and inference, 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.
Software and Environment Management
The right tools for the job, centrally provisioned
Maximize productivity and collaboration by using the right tools for the job, accessed from a secure governed platform. No more bespoke laptops!
Domino provides one-click access to a wide variety of open-source and commercial tools and languages including Python, R, SAS, and MATLAB. Versions are tracked to avoid conflicts when team members try to reuse work. As technology changes, it's easy to add new emerging tools when needed, future-proofing your data science platform.
Unified Data Access Layer
Easy, governed, and secure access to data
Data is the fuel for all models but data access, preparation, and governance is a struggle. Not with Domino.
Domino Data Sources provide rapid, secure access so you can quickly get to work while also adhering to data access policies. Domino’s Data Access Library unifies access patterns for disparate data types through SQL syntax. Analytic-ready data, along with its associated metadata, is easily saved in a result set for later reuse, saving time and compute costs.
Out-of-the-box support for Feast– the emerging, open-source standard for feature stores – increases the reproducibility, consistency, and reusability of features while also helping to mitigate skew between the features used in training and those used in production. Organizations now have a single source of truth for calculating important features.
Audit trails and granular data access controls ensure that only team members authorized to see data can do so, and you can show how access has changed over time.
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.
Domino gives us the openness and flexibility we need to seamlessly experiment and collaborate rapidly, using our choice of scalable compute and infrastructure
Luca Foschini, Ph.D.
Co-founder and Chief Data Scientist
Empowering individuals to participate in better health outcomesRead The Story
Frequently Asked Questions
Can Domino support both on-prem, hybrid and cloud infrastructure?
Yes, because Domino is fully Kubernetes native, we can support both on-prem and cloud infrastructure. Nexus provides support for hybrid and multi-cloud architectures. As a result, Domino aligns with your current and future IT strategy and infrastructure vision and can be a key enabler as you move towards a full cloud, or hybrid on-prem and cloud deployment.
Does Domino support GPUs?
Yes, with Domino you can centrally provision GPU resources for data scientists to leverage in projects. They are shared across all users allowing you to maximize the benefit and utilization.
Is Spark supported in Domino?
Yes, Domino supports Spark, as well as other distributed computing frameworks like Ray and Dask.