Last updated 8th December, 2020.
This tutorial covers the process of building your own job image for specific needs
- access to the OVHcloud Control Panel
- an AI Training project created inside a public cloud project
- a user for AI Training
- docker installed on your local computer
- some knowledge about building image and Dockerfile
Write your own Dockerfile
Create a new file and name it
Choosing a base image
First you need to choose a base image to start from, that base image should have cuda driver installed on to be able to use GPUs when running.
We recommand to choose one from the following lists if you dont want to install cuda drivers yourself.
Here is the list of base images without notebooks that we use :
Here is the list of base images including notebooks (jupyterlab + Visual Studio Code) that we use :
Header of your Dockerfile should look like this :
For example if you want to start from the base image
Install what you need
Bash command instructions on your Dockerfile should begin with
Example if your want to install vim :
RUN apt-get update && apt-get install -y vim
You can copy files from your local directory inside docker image with the
Example if you want to add the file
example.txt at the root of the image :
COPY example.txt /example.txt
Images in AI Training are not run as root user. It means that if you want to be able to write in a specific directory at runtime you will have to give it specific rights. You can do it with the following instruction :
RUN chown -R 42420:42420 <your-target-directory>
You can set environment variables with the
Example if you want to add an environment variable
KEY with value
ENV KEY VALUE
For more information about dockerfile we recommand you to refer to the official documentation
Once your Dockerfile is complete and match your needs you have to choose a name and build the image using the following command in the same directory :
docker build -t <image-name> .
Test it locally (Optional)
If you want to verify that your built image is working properly, create 2 files :
- One file named
groupwith following content :
root:x:0: ovh:x:42420: nogroup:x:65534:
- One file named
passwdwith following content :
root:x:0:0:root:/root:/bin/bash ovh:x:42420:42420:OVH:/workspace:/bin/bash nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin
And run the following command :
docker run --rm -it -v $(pwd)/group:/etc/group -v $(pwd)/passwd:/etc/passwd --user=ovh:ovh <image-name>
Push image in the registry of your choice
Pushing your image to a registry is needed in order for AI Training to pull it.
AI Training provides a default registry called Shared registry where users are able to push their custom images. It is linked with every project by default.
If you prefer using your own private docker registry instead of the shared one, feel free to use it. Just don't forget to attach your registry in your AI Training project before using it.
The basic commands to push a docker image to a registry is :
docker login -u <registry-user> -p <registry-password> <registry> docker tag <image-name> <registry>/<image-name> docker push <registry>/<image-name>
Example if you want to push an image named
custom-image inside a registry
docker login -u <registry-user> -p <registry-password> my-registry.ai.cloud.ovh.net docker tag custom-image my-registry.ai.cloud.ovh.net/custom-image docker push my-registry.ai.cloud.ovh.net/custom-image
If you want to know the exact commands to push on the shared registry, please consult the
Details button of the Shared Docker Registry section in the Home panel of AI Training.
Please send us your questions, feedback and suggestions to improve the service:
- On the OVHcloud AI community forum
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