Learn about the lifecycle of an AI Notebook and associated billing.
Introduction
The OVHcloud AI Notebooks service provides you with Jupyter or VSCode notebooks, linked to CPU or GPU resources, without the hassle of installing or operating them. AI Notebooks are linked to a Public Cloud project. The whole project is billed at the end of the month, with pay-as-you-go. It means you will only pay for what you consume based on the compute resources you use (CPUs and GPUs) and their running time.
AI Notebooks lifecycle
During its lifetime, the notebook will go through the following statuses:
-
STARTING: the notebook is being started and the remote data, if any, is synchronized. To learn more about data synchronization, please check out the Data - Concept and best practices documentation. -
RUNNING: the notebook is running, you can connect to it and use it. Compute resources (GPUs/CPUs) are allocated to your specific notebook, and data are available. -
STOPPING: the notebook is stopping, your compute resources are freed, your status is saved, and, if any, the data is synchronized back. -
STOPPED: the notebook ended normally. You can restart it whenever you want or delete it. -
FAILED: the notebook ended in error, e.g., the process in the notebook finished with a non-0 exit code. For more information, refer to this section of our Troubleshooting documentation. -
ERROR: the notebook ended due to a backend error. You may reach our support. -
DELETING: the notebook is being removed. When it is deleted, you will no longer see it; it will no longer exist.
Billing principles
AI Notebooks are a pay-per-use solution. You only pay for the resource consumption during the RUNNING phase of your notebooks.
The billing principle is quite simple: you select the amount of compute resource (CPUs or GPUs) you would like to work with and pay only for that.
Included in AI Notebooks resources:
- AI Notebooks managed service
- Dedicated CPU/GPU compute resources (based on the selected amount)
- Ephemeral local storage (size depends on the selected compute resources)
- Workspace storage when a notebook is running
- Ingress/Egress network traffic
Optional with AI Notebooks:
- Remote storage space, based on OVHcloud Object Storage pricing
- Egress traffic for remote Object storage
- Saved workspace storage (the first 10GB are free)
Visual explanations about paid items:
A more detailed view:
Compute resources details
During the notebook creation, you can select compute resources, known as CPUs or GPUs. Their official pricing is available in the OVHcloud Control Panel or on the OVHcloud Public Cloud website.
Rates for compute are mentioned per hour to facilitate the reading of the prices, but the billing granularity remains per minute.
Storage details
Ephemeral local storage
Each compute resource (CPU or GPU) comes with local storage, which we can consider ephemeral since this storage space is not saved when you delete an AI Notebook.
The sizing depends on the selected amount of compute resources, check the details on the OVHcloud Public Cloud website.
Remote Object storage
When working with remote data, you pay separately for the storage of this data. The pricing of object storage is separate from the notebook pricing.
Workspace storage
When you attach remote data to an AI Notebook, you can select the mounting point. If you opt for /workspace/*, we will save your data when you stop your notebook.
This workspace is saved as long as your notebook is in a STOPPED state.
- Included: worskpace is included when your notebook is in a "running" state.
- Paid: the first 10GB are free for 30 consecutive days, then you pay at the price of OVHcloud Object Storage.
Pricing examples
Example 1: one GPU notebook for 45 minutes, then deleted
We start one AI Notebook with two GPUs, and we keep it running for 45 minutes, then we delete it.
- compute resources: 1 x GPU NVIDIA L4 ($0.91 / hour)
- remote storage: nothing
- duration: 45 minutes
Compute cost:
0.75 (hours) x 1 (GPU) x $0.91 (price / GPU) = $0.6825
Storage cost: none
Total: $0.6825, billed at the end of the month
Example 2: one GPU notebook for 10 hours but stopped, not deleted
We start one AI Notebook with two GPUs, run it for 10 hours, stop it, and delete it after 10 days. Workspace storage used is 100 GB (the first 10 GB is free).
- compute resources: 2 x GPU NVIDIA L4 ($0.91 / hour)
- remote storage: nothing
- workspace storage: 90 GB chargeable
- duration: 10 hours running, 10 days (240 hours) stopped
Compute cost:
10 (hours) x 2 (GPU) x $0.91 (price / GPU) = $18.20
Storage cost:
90 GB x 240 (hours) x $0.00001111 (price / hr / GB) = $0.239
Total: $18.44, billed at the end of the month
Example 3: one GPU notebook for 10 hours with 1 TB remote storage
We start one AI Notebook with two GPUs and 1 TB remote storage. It runs for 10 hours and is then deleted. Workspace usage is 1 TB (990 GB chargeable).
- compute resources: 2 x GPU NVIDIA L4 ($0.91 / hour)
- remote storage: 1,000 GB
- workspace storage: 990 GB chargeable
- duration: 10 hours
Compute cost:
10 (hours) x 2 (GPU) x $0.91 (price / GPU) = $18.20
Remote storage cost:
1,000 GB x 10 (hours) x $0.00001111 (price / hr / GB) = $0.111
Workspace storage cost:
990 GB x 10 (hours) x $0.00001111 (price / hr / GB) = $0.110
Total: $18.42, billed at the end of the month
Example 4: 15 CPU notebooks for 5 hours, then deleted
We start 15 AI Notebooks, each with one vCPU, run them for 5 hours, and then delete them.
- compute resources: 1 x vCPU ($0.04 / hour / CPU)
- remote storage: none
- duration: 5 hours
Compute cost:
5 (hours) x 15 (CPU) x $0.04 (price / CPU) = $3.00
Storage cost: none
Total: $3.00, billed at the end of the month
Images decommissioning
Objective
Products evolve and eventually reach the end of their lifecycle. Our objective is to ensure that this transition happens smoothly.
All AI images follow the Python version lifecycle policy. Once a Python version reaches its end of life, the associated AI frameworks will be decommissioned.
What does it mean?
- You will not be able to create new notebooks based on this Python version.
- Your existing notebooks will continue to work until you delete them.
- During this period, the images will still receive security updates.
- Once the underlying OS reaches its end of life, you will still be able to start your notebooks, but the image will no longer be maintained. We strongly recommend that you migrate to a newer image version.
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.