Subject archive for "product-updates," page 6
In this “This Is My Architecture” video, Ozzy Johnson, deputy chief technology officer at Domino Data Lab shows how Domino provides containerized data science solutions for customers of any size and regulation need. You will see how Domino leverages infrastructure as code through Terraform and Jinja to build out a data science environment that works in highly customized environment through containerizing with Docker and Kubernetes. Ozzy will also cover how Domino Data Lab works in both AWS and on premise environments, while leveraging the benefits of AWS services like S3, EC2 and ELB to gain the benefits of high availability and security and shorten the development time in AWS.
By Domino Data Lab1 min read
Containerization is a key technology that accelerates the adoption and impact of data science amongst numerous companies in the world. An experiment’s state (data, code, results, package versions, parameters, etc.) at any point in time can be captured as a whole in a lightweight container and deployed on customers’ on-premise infrastructure and/or elastic compute infrastructures such as the cloud. This means data science experiments are easy and fast to reproduce, and data science teams can build on the prior work of others, which ultimately helps them drive the next level of innovation.
By Desmond Chan4 min read
We recently released new functionality that provides first-class integration between Domino and git. This post describes the new feature, and describes our perspective on the unique requirements of version control in the context of data science—as distinct from software engineering—workflows.
By Eduardo Ariño de la Rubia5 min read
We’re excited to announce a set of big new features that make it easier for you to find and reuse past data science work in your team and organization. We’re calling these features “Discoverability,” and they encompass powerful ways to search, tag, and get recommendations about relevant analytical work.
By Nick Elprin7 min read
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