Subject archive for "domino-engineering"

Data Science

Announcing Trial and Domino 3.5: Control Center for Data Science Leaders

Even the most sophisticated data science organizations struggle to keep track of their data science projects. Data science leaders want to know, at any given moment, not just how many data science projects are in flight but what the latest updates and roadblocks are when it comes to model development and what projects need their immediate attention.

By Domino8 min read

Data Science

Model Deployment Powered by Kubernetes

In this article we explain how we’re using Kubernetes to enable data scientists to deploy predictive models as production-grade APIs.

By Alexandre Bergeron7 min read

Data Science

Image diffing with CSS tricks

We've been hard at work delivering exciting new features in Domino. Our latest release included a lot, including the ability to import/share data sets across projects, easier ways to manage organizations of users, and improvements to how we host Jupyter notebooks, along with changes that make it easier to manage an on-premise deployment of Domino.

By Nick Elprin2 min read

Data Science

Building an Open Product for Power Users

This post describes our engineering philosophy of building an “open” product, i.e., one that supports existing tools and libraries, rather than building our own custom version of existing functionality. Aside from letting our developers be more productive, we’ve found this approach makes our users much more productive — especially power users, who are especially important to us.

By Nick Elprin8 min read

Data Science

A Mongo-based Cache Plugin for Play

A quick engineering-related post: we built a cache plugin for Play that uses capped collections in Mongo. It's available on Github if you'd like to use it.

By Nick Elprin1 min read

Data Science

R Notebooks in the Cloud

We recently added a feature to Domino that lets you spin up an interactive R session on any class of hardware you choose, with a single click, enabling more powerful interactive, exploratory work in R without any infrastructure or setup hassle. This post describes how and why we built our "R Notebook" feature.

By Nick Elprin5 min read

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