[D] Experiment Management in Kubernetes
I’ve yet to witness a solution that containerizes my laptop environment and replicates my experiment in the cloud. Suppose I run a jupyter experiment on my laptop. Now with a modicum of fiddling I want to fire off 10 instances of the same experiment in AWS with different learning rates (and have my results neatly collated, perhaps in git branches).
I acknowledge the efforts of MLflow, Kubeflow, Comet.ml, deepkit, guide.ai, dvc, sacred, speedrun, and trains but none of these at first glance addresses basic replication in the cloud. Moreover several of them like Kubeflow are prohibitively complex for academics on a budget.
Requesting comments and/or sympathies.