Learn about the technical features, capabilities, and limitations of the Public Cloud AI Notebooks offer.
AI Notebooks is covered by OVHcloud Public Cloud Special Conditions.
Features
Available features
AI Notebooks are Managed Jupyter or VS Code notebooks linked to compute resources (CPUs/GPUs) and storage. You can compare them to Google Colab or Amazon Sagemaker notebooks.
| Feature | Details |
|---|---|
| Live code editor and AI environments | |
| Jupyter and VS Code | You can use Jupyter or VS Code as your preferred live-code editor. If you opt for VS Code, you can also set up a remote connection (for example, from your laptop). |
| Preinstalled Machine Learning environments | AI Notebooks comes with a generic Python environment (Conda) or pre-installed ones, such as Pytorch, Tensorflow, HuggingFace, and more. |
| Easy customization | AI Notebooks allows installation of almost any Conda or Pip packages. You can easily customize your environment to suit your needs. |
| Management | |
| Multiple ways to manage your notebooks | You can manage your AI Notebooks through the OVHcloud Control Panel, CLI, API or Python SDK. Depending on your needs, you can easily automate their creation and deletion as well. |
| Easy start and Stop | You can start and stop a notebook in one click. Once stopped, your notebook environment is kept, and you can restart it later without losing your data and experiments. |
| Compute resources | |
| Guaranteed compute resources | Select the number of CPUs or GPUs required during the creation of the AI Notebooks. Once launched, you will keep these resources as long as your notebook is running. |
| Background execution | Your tasks can be executed in the background, meaning that closing your web browser will not affect your work. |
| No maximum runtime | Your tasks can last as long as your notebook is running. |
| Monitoring tools | Each AI Notebooks service comes with a native Grafana dashboard, allowing you to keep track of and monitor your CPU, GPU, RAM, and storage resources. |
| Storage | |
| Fast and flexible storage | Each AI Notebooks service comes with local storage, but also the ability to attach remote storage from Object Storage. From a few GiB to multiple TiB, we push your data near our compute power on fast SSD storage for better performance. |
| Git repositories importation | During the creation of your AI Notebooks, you can specify one or multiple Git repositories to download inside your notebook environment. |
| Security | |
| Open or restricted authentication | During the creation of your AI Notebooks, select open or restricted access to your notebook. If restricted, people can be granted access via token or credentials to securely access your environment. |
| Billing | |
| Easy billing | You only pay for what you consume, billed per minute. |
Command line interface (CLI)
AI Notebooks is compliant with the OVHcloud AI CLI. Discover how to install the OVHcloud AI CLI.
Monitoring tools
To see information about your notebook, you can do so with the ovhai CLI using this command:
You can access your metrics through the Monitoring Url.
You are also able to check it from the OVHcloud Control Panel in your notebook's general information by clicking the Go to Graph Dashboard button.
Planned features
We continuously improve our offers. You can follow, vote, and submit ideas to add to our roadmap.
Capabilities and limitations
Supported regions
AI Notebooks can be used from any country in the world, as long as you have an OVHcloud account. Our AI & Machine Learning services are based in the US-EAST-VA (Vint Hill, Virginia) region.
Attached resources
Compute resources
You can choose the number of GPUs or CPUs for a notebook, but cannot use both. By default, a notebook uses one GPU. The memory resource is not customizable.
If you choose GPU:
- CPU, memory, and local storage resources are not customizable but scaled linearly with each additional GPU.
If you choose CPU:
- Memory and local storage resources are not customizable but scaled linearly with each additional CPU.
The maximum amount of CPU/GPU, memory per CPU/GPU, and local storage is available on the OVHcloud website, Control Panel, and the ovhai CLI.
For your information, the current limits are:
- CPU: 12 per notebook.
- GPU: 4 per notebook.
Available hardware for AI Notebooks
Currently, we provide:
ai1-1-cpuL4-1-gpuL40s-1-gpu
Available storage
Local storage
Each AI Notebook comes with a local storage space, which is ephemeral. When you delete your notebook, this storage space is also deleted. This storage space depends on the selected instances during the notebook creation. Please refer to the compute resources section for more information.
Local storage is limited and not the recommended way to handle data, see the OVHcloud documentation on data for more information.
Attached storage
When attaching data volumes to your AI Notebooks, you can use storage from Public Cloud Object Storage. This allows you to work with large datasets, while ensuring persistence even if you delete your notebooks.
Ensure that the Object Storage bucket is located in the same region as your AI Notebook.
Your Public Cloud Project can store unlimited data in Object Storage buckets. However, when you mount an Object Storage bucket as a volume, there is a usage limit of 10 TB per Public Cloud Project. This limit applies to the total storage consumed by all volumes attached simultaneously across you AI Notebooks, AI Training jobs, and AI Deploy apps.
When the same volume is used across multiple resources, enabling caching allows shared access to the volume data, preventing multiple copies from consuming additional storage quota. Without caching, each instance will maintain a separate copy of the volume data, increasing the total storage usage linearly.
Maximum execution time
There is no duration limitation on AI Notebooks execution.
Live-code editors
You can choose between two live-code editors to launch and edit your notebook:
- Jupyterlab
- VS Code
You cannot install your own code editor on AI Notebooks.
With VS Code, you get the capability to use remote connections (from a local computer).
Pre-installed AI environments
OVHcloud AI Notebooks come with pre-installed AI environments.
List of available AI Environments:
- AutoGluon + MXNet
- FastAI
- HuggingFace Transformers
- JAX
- Miniconda (Python generic)
- Miniconda with Colab Compatibility
- MLR3
- MXNet
- One image to rule them all
- PyTorch
- Scikit-Learn
- TensorFlow
Environment customization
Each environment can be customized directly with PIP or CONDA (we support almost any package and library).
Limitations:
-
You are not the administrator (root). You cannot install Linux packages (such as apt-get).
-
AI Notebooks does not allow the use of custom Docker images. In case you need a very specific package or framework, you can bring your custom Docker images with OVHcloud AI Training.
AI Training allows you to benefit from the same technology and pricing, but you can create notebooks directly with your own Docker images. If you want to build and use a custom Docker image, you can do it with AI Training by following this tutorial.
Network
-
Public networking can be used for all the AI Tools.
-
Private networking (OVHcloud vRack) is not supported.
Available ports to public network
Each notebook has a public URL that accesses port 8080 of the notebook by default and cannot be changed.
Notebook URL for accessing the default port (starting with the notebook's ID):
- https://00000000-0000-0000-0000-000000000000.notebook.us-east-va.ai.cloud.ovh.us
Only the HTTP layer is accessible.
Quotas per Public Cloud project
GPU and CPU availability is subject to the quota set on your Public Cloud Project. You can reach out to our support team to increase your quota.
Go further
For more information and tutorials, please see our other AI & Machine Learning support guides or explore the guides for other OVHcloud products and services.
If you need training or technical assistance to implement our solutions, contact your sales representative or click on this link to get a quote and ask our Professional Services experts for a custom analysis of your project.