Can you please elaborate what your use case for deployment?
Besides that, I'm happy to say that ClearML supports all the cases above 🙂
Also for some further reading:
Great to hear that!
In short, we hope ClearML server can act as the bridge to connect local servers and Cloud infrastructure. (Local servers for development and Cloud for deployment and monitoring.)
- We want to deploy ClearML somewhere on the Internet.
- Then use this service to track experiments, orchestrate workflow, etc. in our local servers.
- After finished experiments, we get returned artifacts and save them somewhere, local disk or cloud for instance.
- Finally, we will want to use ClearML to deploy our whole training pipeline to the cloud environment and do monitoring, and continue the loop of automatically retraining the already deployed model on Cloud, based on the monitoring results or a fixed schedule.