There are several other platforms/tools taking different approaches to productionizing ML workload. At Polyaxon[1], we used to create a container for each task and also log the git commit for reference, and provide ways to push the container to an in-cluster registry or a cloud registry. In the new version of our platform, we basically improved the process by injecting specific git commit inside pre-built docker images to not only reduce the build time, but also to allow easier integration with external tool such as Github actions.

[1]: https://github.com/polyaxon/polyaxon