Are you planning to open source it?
A lot of your competitors have, like http://pipeline.ai/, https://github.com/pachyderm/pachyderm and recently https://github.com/polyaxon/polyaxon.
A lot of your competitors have, like http://pipeline.ai/, https://github.com/pachyderm/pachyderm and recently https://github.com/polyaxon/polyaxon.
I would like to outline a couple of differences between CometML and Polyaxon, as mentioned before, we are also trying to solve issues related to technical debt in ML, but not only, Polyaxon tries also to simplify training and scheduling parallel and distributed learning. there are also a couple of differences, I see CometML as dashboard, Polyaxon does not have an extensive dashboard as CometML, but it leverages Tensorboard for most of the visualisations. We use the CLI or the API for programatic access to the platform. Most importantly, Polyaxon aims to be an open source and to be installed on premise or in the cloud, it solves the issue related to code tracking based on an internal git and a docker registry, and as someone else mentioned that resources for running an experiment could be an issue for future reproducibility, Polyaxon restarts the experiments with the same resources and dockerfiles, it also tracks hyper params as part of the configuration.
For hyper params tuning and suggestion, Polyaxon can also do hyper params search based on a couple of algorithms, and for the next release, it will include also a service similar to vizier for suggesting more experiments/group of experiments based on a given search space.
Disclaimer: I am the author of Polyaxon