Does anyone want to take a poke at handling this person's question? I don't want to be one of those "I will answer but I'm a maintainer" people.

Hi people!! I would like to hear your good impressions and concerns about Kedro (https://kedro.org/) in order to write ML Pipelines. I have tried that, and I am really excited with its potential use by a junior data science team. Please, consider following topics in this discussion:

• learning curve (how much is it difficult to start and progress with Kedro?)

• MLOps best practices (testing, logging, versioning)

• maintenance and support by community

• multi-cloud (connections with GCP, AWS, Azure)

• use with other open-source MLOps stacks (mlflow, evidently, dvc, bentoML, fastAPI, etc)

Thanks a lot!!

Link to question: https://mlops-community.slack.com/archives/C015J2Y9RLM/p1677005506203909 Link to Slack workspace: https://go.mlops.community/slack

I did my part 😎