Embracing the future, Domino is now Kubernetes-native and ready to fluidly support innovations yet to come. The benefits of Kubernetes and the core values of Domino are solidly aligned - flexibility, reliability, cost reduction, and avoidance of vendor and tool lock-in. Knowing the importance that Kubernetes will play in Enterprise IT architecture in the next five years and beyond, our engineering team took on the task of fully replatforming Domino.
We realize that the support of data science and the coordination of IT strategy is no easy task. The good news is that the needs of data scientists and future-looking IT strategy can both be supported by the flexibility of container orchestration with Kubernetes. If you talk to many an IT team, you will hear a focus on being cloud-native, with future goals of implementing a multi-cloud or hybrid cloud strategies. Kubernetes will play a huge part in these strategies and will increasingly be key to supporting data scientist needs.
With a Kubernetes-native Domino, we are doubling down on openness and support for all enterprise infrastructures - AWS, GCP, and Azure, as well as on-premises. Further, Domino can help enterprise IT providers avoid cloud-lock in and implement multi-cloud strategies while taking advantage of their existing monitoring and operational infrastructures.
As Joshua Cluff, data science operations manager at National Oilwell Varco said, “Domino on Kubernetes gives our data science team the flexibility we need while offering peace of mind to our partners in IT. We can now run Domino across diverse infrastructure, including both on-premises and cloud-based environments, while also plugging into existing monitoring, logging, and enterprise security tools that our IT team knows and trusts. It’s a big step forward on the path to make Data Science a first-class citizen that’s aligned with Enterprise IT.”
Domino on Kubernetes allows opens up a host of benefits for you and your teams:
Enable multi-cloud data science: Kubernetes supports Domino’s multi-cloud strategy, allowing Domino to run natively in any cloud or on-premise environment with the full benefits of elastic scaling of heterogeneous data science workloads;
Reduced cost of data science workloads: By scaling workloads elastically and packing them smartly across underlying hardware resources, Domino runs data science workloads more efficiently, reducing compute costs; and
Operational efficiency: Domino can now install into a company’s existing Kubernetes cluster, reducing management surface area and simplifying administration by integration with the existing devops stack.
We are thrilled to announce that Domino is making it easier than ever for IT to successfully support their data scientists. With Domino on Kubernetes, forward-looking IT organizations can streamline and enhance their data science infrastructure with scalable multi-cloud support on top of the industry-leading orchestrator, Kubernetes.
Striding into the future, Kubernetes-native Domino will “make the world run on models” wherever those models are run.