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About

Azure Deployment Environments provides devs with self-service, project-based templates to deploy environments for any stage of development. Support collaboration and innovation with consistent environments and best practices, and encourage experimentation and InnerSource use while maximizing security, compliance, and cost efficiency. Deploy the right environment at the right time without worrying about backend processes. Provision complex environments in minutes without waiting for your platform engineering team by choosing from a curated set of templates built specifically for your projects. Spin up self-service environments directly from where you work—including the code repository, the CLI, or a custom dev portal—while automatically applying the right identities, permissions, and Azure subscriptions.

About

Domino is an enterprise AI platform designed to help organizations build, deploy, and scale AI systems that deliver real business outcomes. It provides end-to-end support for the AI lifecycle, from data science experimentation to production deployment and governance. The platform enables teams to access data, tools, and compute resources through a self-service environment with built-in IT controls. Domino supports the development of machine learning models, generative AI applications, and AI agents using preferred tools and frameworks. It also includes governance features such as model tracking, audit trails, and policy enforcement to ensure compliance and transparency. With hybrid and multi-cloud capabilities, organizations can run AI workloads across on-premises and cloud environments. Overall, Domino helps enterprises operationalize AI at scale while maintaining control, security, and efficiency.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

DevOps teams interested in a solution to quickly spin up app infrastructure environments with project-based templates

Audience

Large enterprises, data science teams, and IT leaders looking to build, deploy, and կառավար AI systems at scale with strong governance, security, and infrastructure control

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Per user/per year
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 4.0 / 5
support 5.0 / 5

Pros & Cons from Real Users

Pros

  • Domino Data Science has the following pros: - Great Customer service. - Flexibility with notebooks and the ability to define your environment as per your needs. - Collaboration is very much easy with this software. - Launches Quickly and easily scalable of Kubernetes infrastructure.

Cons

  • The only cons that I found with this software were that the datasets are not accessible outside the platform. Other than that, this works fine for me.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Microsoft
Founded: 1974
United States
azure.microsoft.com/en-us/products/deployment-environments

Company Information

Domino Data Lab
Founded: 2013
United States
www.dominodatalab.com

Alternatives

Alternatives

Fortem

Fortem

CYBRIX

Categories

Categories

Data Science Features

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Deep Learning Features

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Machine Learning Features

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Integrations

Amazon EC2 Trn2 Instances
Anaconda
Apache Zeppelin
Bitbucket
Flask
GitHub
GitLab
H2O.ai
Jira
JupyterLab
MATLAB
Microsoft Azure
NVIDIA EGX Platform
NVIDIA NGC
NVIDIA RAPIDS
Okera
PyTorch
R
Snowflake
python-sql

Integrations

Amazon EC2 Trn2 Instances
Anaconda
Apache Zeppelin
Bitbucket
Flask
GitHub
GitLab
H2O.ai
Jira
JupyterLab
MATLAB
Microsoft Azure
NVIDIA EGX Platform
NVIDIA NGC
NVIDIA RAPIDS
Okera
PyTorch
R
Snowflake
python-sql
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