I am planning to deploy MLFlow server deployed in AWS ECS as a centralised repositories for my machine learning experiments and runs and to strore events and artifacts. I would like to use MLflow Tracking Server enabled with proxied artifact storage access to eliminate the need to have authentication to the underlying storage(S3 bucket) at my side(client). And I would like to have different environments or isolated environments as i keep creating projects? for example, for project titanic, i might have 10 experiments, which i would not want to see from project iris and this project will have different experiments. How do I achieve this?

Thanks.