I have been working with the team at Data Revenue on this framework for the last several weeks (personally focusing more on the tutorials and documentation).
It's a set of terraform scripts that set up a Kubernetes cluster with Prefect, JupyterHub, MLFlow and some other open source platforms to create a cohesive and comprehensive machine learning platform.
It's still pretty rough, but you can get started with some basic examples to see how everything fits together. We are still tuning the default parameters and configuration, so if you have some Kubernetes experience you might get better mileage out if it (though I had nearly none before working on this and it was also a great way to learn that).
Shout if any questions - I'll be hanging out here for the next few hours and then again tomorrow morning EU time.
If you want to skip the blog announcement and go straight to the github, the link is [0]
I have been working with the team at Data Revenue on this framework for the last several weeks (personally focusing more on the tutorials and documentation).
It's a set of terraform scripts that set up a Kubernetes cluster with Prefect, JupyterHub, MLFlow and some other open source platforms to create a cohesive and comprehensive machine learning platform.
It's still pretty rough, but you can get started with some basic examples to see how everything fits together. We are still tuning the default parameters and configuration, so if you have some Kubernetes experience you might get better mileage out if it (though I had nearly none before working on this and it was also a great way to learn that).
Shout if any questions - I'll be hanging out here for the next few hours and then again tomorrow morning EU time.
If you want to skip the blog announcement and go straight to the github, the link is [0]
[0] https://github.com/datarevenue-berlin/OpenMLOps