- Closes#23874 by fixing a typo ("num_gpus" -> "num-gpus").
- Adds end-to-end test logic confirming the fix.
- Adds end-to-end test logic confirming autoscaling with custom resources works.
- Slightly refines developer instructions.
- Deflakes test logic a bit by allowing for the event that the head pod changes its identity as the Ray cluster starts up.
This PR consists of the following clean-up items for KubeRay autoscaler integration:
Remove the docker/kuberay directory
Move the Python files formerly in docker/kuberay to the autoscaler directory.
Use a rayproject/ray image for the autoscaler.
Add an entry point for the kuberay autoscaler to scripts.py. Use the entry point in the example config.
Slightly simplify the code that starts the autoscaler.
Ray versions are updated to Ray 1.11.0, which will be officially released within the next couple of days.
By default, Ray >= 1.11.0 runs without Redis. References to Redis are removed from the example config.
Add the autoscaler configuration test to the CI.
Update development documentation to reflect the changes in this PR.
This is a minimum viable product for Ray Autoscaler integration with Kuberay. It is not ready for prime time/general use, but should be enough for interested parties to get started (see the documentation in kuberay.md).
