Domino Enterprise MLOps Platform

Score8 out of 10

6 Reviews and Ratings

What is Domino Enterprise MLOps Platform?

The Domino Enterprise MLOps Platform helps data science teams improve the speed, quality and impact of data science at scale. Domino is presented as open and flexible, to empower professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect.

The Domino Enterprise MLOps platform comprises three essential layers:

The Self-Service Infrastructure Portal makes data science teams become more productive with access to their preferred tools, scalable compute, and diverse data sets. By automating time-consuming and tedious DevOps tasks, data scientists can focus on the tasks at hand.
The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle.
The System of Record has a reproducibility engine, search and knowledge management, and integrated project management. Teams can find, reuse, reproduce, and build on any data science work to amplify innovation.

What makes Domino unique?

It's Open & Flexible. Domino supports an ecosystem of open-source and commercial tools and infrastructure. The vendor states this differentiates it from Sagemaker which is AWS-specific or Databricks which is tied to Spark. Domino is an open system and its architecture supports on-premise, cloud, and hybrid environments for more flexibility. Domino supports tools, packages, and compute frameworks such as Spark, Ray, and Dask.
It's Built for Teams. Domino is designed for data science at scale. Teams using different tools can collaborate on projects and rely on Domino to automatically track all data science artifacts. Domino establishes full visibility, repeatability, and reproducibility at any time for every use case. Dashboards let managers set project goals and inspect in-flight work.
Its focus is on Integrated Workflows. Domino integrates workflows to accelerate the full lifecycle from experiment to production. For example, Domino automatically sets up prediction data capture pipelines and model monitoring for deployed models to ensure peak model performance. Everyone can use end-to-end workflows with common patterns and practices, regardless of their preferred tools. Domino’s integrated approach helps users involved in data science to maximize their productivity.