Long Running Tests

This directory contains the long-running workloads which are intended to run forever until they fail. To set up the project you need to run

pip install anyscale
anyscale project create

Note that all the long running test is running inside virtual environment, tensorflow_p36

Running the Workloads

You can start all the workloads with:

anyscale session start -y run --workload="*" --wheel=https://s3-us-west-2.amazonaws.com/ray-wheels/releases/0.7.5/6da7eff4b20340f92d3fe1160df35caa68922a97/ray-0.7.5-cp36-cp36m-manylinux1_x86_64.whl

This will start one EC2 instance per workload and will start the workloads running (one per instance). You can start a specific workload by specifying its name as an argument --workload= instead of "*". A list of available options is available via any session start run --help.

Check Workload Statuses

To check up on the workloads, run either anyscale session --name="*" execute check-load, which will print the load on each machine, or anyscale session --name="*" execute show-output, which will print the tail of the output for each workload.

To debug workloads that have failed, you may find it useful to ssh to the relevant machine, attach to the tmux session (usually tmux a -t 0), inspect the logs under /tmp/ray/session*/logs/, and also inspect /tmp/ray/session*/debug_state.txt.

Shut Down the Workloads

The instances running the workloads can all be killed by running anyscale session stop --name "*".

Adding a Workload

To create a new workload, simply add a new Python file under workloads/ and add the workload in the run command in ray-project/project.yaml.