Comparative tables between AI Notebooks, AI Training, AI Deploy
Discover the main differences between each of the OVHcloud AI tools' bricks
Last updated 1st September, 2022.
Objective
OVHcloud provides a set of managed tools designed for building your machine learning projects. This guide explains the main differences between our AI tools, commonly called AI Notebooks, AI Training and AI Deploy.
Overview
OVHcloud AI tools work inside our Public Cloud ecosystem. Once logged in to your Public Cloud project, you have access to AI tools including:
- AI Notebooks
- AI Training
- AI Deploy
Each of them are autonomous tools, billed per minute and with shared elements, such as security tokens, etc.
All AI Tools have access to OVHcloud Object Storage as a central point, allowing you to work with your data securely and easily.
We schematize our AI offers this way:
Comparative tables
| Product offers | AI Notebooks | AI Training | AI Deploy |
|---|---|---|---|
| Description | Managed Jupyter or VSCode notebook, linked to compute resources (CPU or GPU) and storage. | Automate your trainings, deploy your own Docker container, linked to compute resources (CPU of GPU), and attached storage. | Deploy with high-availability your own AI application and models via Docker containers or select one from our catalog |
| Billing Resources | per minute | per minute | per minute |
| AI Features | AI Notebooks | AI Training | AI Deploy |
|---|---|---|---|
| Managed Jupyter Notebook with preinstalled libraries | X | ||
| Managed VSCode Notebook with preinstalled libraries | X | ||
| Automate Training phases (timeout, grid computing, ...) | X | ||
| Bring your own Docker image (with notebooks inside, models, whatever) and connect to compute and storage resources | X | X | |
| Deploy your managed applications and models with high-availability | X | ||
| Deploy AI applications from a catalog made with partners | X |
| Management | AI Notebooks | AI Training | AI Deploy |
|---|---|---|---|
| Control panel | X | X | X |
| API | X | X | X |
| CLI | X | X | X |
| Resources | AI Notebooks | AI Training | AI Deploy |
|---|---|---|---|
| CPU resources | X | X | X |
| CPU flavors available | ai1-1-CPU | ai1-1-CPU | ai1-1-CPU |
| GPU resources | X | X | X |
| GPU flavors available | ai1-1-GPU | ai1-1-GPU | ai1-1-GPU |
| RAM Memory | X | X | X |
| Dask computing | X | ||
| Cold-patch resources (adjust gpu/cpu/, attached storage) | X | ||
| Local SSD-NVMe storage | X | X | X |
| Local SSD-NVMe storage size | depends on selected flavors | depends on selected flavors | depends on selected flavors |
| Ability to attach a remote storage (Object Storage) | X | X | X |
| Pull Storage Sync (from object storage) | X | X | X |
| Push Storage sync (to object storage) | X | X | |
| Maximum runtime | unlimited | unlimited | unlimited |
| Ability to add a runtime timeout (via CLI) | X |
| Security | AI Notebooks | AI Training | AI Deploy |
|---|---|---|---|
| ACL via Openstack user | X | X | X |
| ACL via tokens | X | X | X |
| Backups and resiliency | |||
| Automatic backup | |||
| Backup when you stop | X | ||
| High availability | X (when replicas > 1) | ||
| Auto scaling | Planned |
| Advanced features and parameters | AI Notebooks | AI Training | AI Deploy |
|---|---|---|---|
| Labels | X | X | X |
| Start / Stop / Resume | X | X | |
| Easily import data from Git/* via UI | X | ||
| Unchanging endpoint URL | X |
Feedback
Please feel free to send us your questions, feedback and suggestions to help our team improve the service on the OVHcloud Discord server
Czy ten przewodnik był pomocny?
Zachęcamy do przesyłania sugestii, które pomogą nam ulepszyć naszą dokumentację.
Obrazy, zawartość, struktura - podziel się swoim pomysłem, my dołożymy wszelkich starań, aby wprowadzić ulepszenia.
Zgłoszenie przesłane za pomocą tego formularza nie zostanie obsłużone. Skorzystaj z formularza "Utwórz zgłoszenie" .
Dziękujemy. Twoja opinia jest dla nas bardzo cenna.