- NodeUpdater gets its' IP in parallel now (no longer in __init__)
- We use persistent connections in SSH (temp folder created only for ray; ControlMaster)
- hash_runtime_conf was performing a pointless hexlify step, wasting time on large files
- We use NodeUpdaterThreads and share the NodeProvider; NodeUpdaterProcess is removed
- AWSNodeProvider caches nodes more aggressively
- NodeProvider now has a shim batch terminate_nodes() call; AWSNodeProvider parallelises it; the autoscaler uses it
- AWSNodeProvider batches EC2 update_tags calls
- Logging changes throughout to provide standardised timing information for profiling
- Pulled out a few unnecessary is_running calls (NodeUpdater will loop waiting for SSH anyway)
## Related issue number
Issue #3599
## What do these changes do?
This option goes along with `min_workers`, and `max_workers`. When the
cluster is first brought up (or when it is refreshed with a subsequent
`ray up`) this number of nodes will be started.
It's a workaround for issues of scaling (see related issues) where it
can take a long time (or forever in the case where the head node has
`--num-cpus 0`) to scale up a cluster in response to increasing demand.
## Related issue number
Workaround for https://github.com/ray-project/ray/issues/3339 and https://github.com/ray-project/ray/issues/2106
- Surfaces local cluster usage
- Increases visability of these instructions
- Removes some docker docs (that are really out of scope for Ray
documentation IMO)
Closes#3517.
Adds a tmux flag that can be used to support background execution of experiments. Cannot be used together with screen. Seems to be useful feature that has shown up with different users.
This adds some experimental (undocumented) support for launching Ray on existing nodes. You have to provide the head ip, and the list of worker ips.
There are also a couple additional utils added for rsyncing files and port-forward.
