KubeDL enables deep learning workloads to run on Kubernetes more easily and efficiently.

KubeDL is a CNCF sandbox project.

Its core functionalities include:

• Automatically tunes the best container-level configurations before an ML model is deployed as inference services. - Morphling Github
• Model lineage and versioning to track the history of a model natively in CRD: when the model is trained using which data and which image, each version of the model, which version is running etc.
• Enables storing and versioning a model leveraging container images. Each model version is stored as its own image and can later be served with Serving framework.
• Support inference frameworks and training workloads (Tensorflow, Pytorch. Mars etc.)in a single unified controller.

Check the website: https://kubedl.io