Frequently asked questions
General
Is Daeploy a MLOPS tool?
No, Daeploy enters the project when a trained model already exists. Daeploy creates an application around the trained model and makes the model a part of the production-ready application.
Which ML frameworks does Daeploy support?
Daeploy supports all major ML frameworks, for instance
- PyTorch
- TensorFlow
- Keras
And many more!
I found a bug! How can I report it?
First of all, thank you for wanting to report the bug and improving Daeploy!
We have a public issue tracker on GitHub, please follow the instructions here.
Technical
Does the machine/server running the Daeploy Manager need internet access?
No! Daeploy works without internet access.
First, you need to pull the Daeploy Manager image from here from a computer with internet access. You then need to save the image as a tar file using docker save. The tar file can then be transferred to the wanted machine/server using SCP or a similar tool.
When the machine has the Daeploy Manager image, we recommend following our documentation for how to configure the manager for the production. You find the relevant documentation here.
Can my models be deployed to the cloud?
Yes! You can use Daeploy to on any machine or virtual machine, be it on premise or on the cloud. Our only requirement is Docker and access to Docker daemon.