Creating deep learning models from kubernetes api objects

A system for creating and training deep learning models in a container-based virtualization environment comprising:

• a hardware processor;
• and
• a memory coupled to the hardware processor, the memory storing instructions which are executable by the hardware processor to perform a method comprising:
• Extending the Kubernetes API with new deep learning model object. The new API object comprised of specification of the model architecture, the optimizer type and other training parameters.
• Creating a new Kubernetes deep learning API object and submitting it to the Kubernetes API server.
• Receiving said deep learning model object request about a new deep learning model object from a container orchestration layer.
• Generating a low-level program associated with the deep learning model object.
• Loading the training dataset
• Performing the actual training by running the generated program
• Storing the trained model and the training results.

A system for creating and training deep learning models in a container-based virtualization environment comprising:

• A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for security in a container-based virtualization environment, the method comprising:
• Creating a new Kubernetes deep learning API object and submitting it to the Kubernetes API server.
• Receiving said deep learning model object request about a new deep learning model object from a container orchestration layer.
• Generating a low-level program associated with the deep learning model object.
• Loading the training dataset
• Performing the actual training by running the generated program
• Storing the trained model and the training results.