I'd say I wouldn't discourage you from looking at several solutions. There's an MLOps community and they have a Slack: https://mlops.community/
Also, a plug: I recently submitted a "Show HN: Use your own clusters to train, track, deploy, and monitor ML models (iko.ai)"
https://news.ycombinator.com/item?id=28777589
Nothing fancy, way too small. We built it initially because we do a lot of consulting projects for enterprise clients and it took a toll on us. We either needed to hire people who knew it all (data, models, deployment, infra), or had people tapping on others' shoulders for support.
Incidentally, we use MLflow for automatic experiment tracking: this means you don't need to pollute notebooks with tracking code or to learn MLflow API. We detect params, metrics, and the models itself automatically and save to S3. It's all done for multi-user, behind authentication.
Anyway, my contact information is in my profile. I'd be interested in what your problems are.
As I said, not a competitor of something huge like Databricks. My competitor is my colleague's laptop or a "powerful workstation with GPU" in some office.