chore: import upstream snapshot with attribution

python/ray/autoscaler/aws/development-example.yaml

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+# An unique identifier for the head node and workers of this cluster.
+cluster_name: development
+
+# The autoscaler will scale up the cluster faster with higher upscaling speed.
+# E.g., if the task requires adding more nodes then autoscaler will gradually
+# scale up the cluster in chunks of upscaling_speed*currently_running_nodes.
+# This number should be > 0.
+upscaling_speed: 1.0
+
+# If a node is idle for this many minutes, it will be removed.
+idle_timeout_minutes: 5
+
+# Cloud-provider specific configuration.
+provider:
+    type: aws
+    region: us-west-2
+    availability_zone: us-west-2a
+
+# How Ray will authenticate with newly launched nodes.
+auth:
+    ssh_user: ubuntu
+
+# Tell the autoscaler the allowed node types and the resources they provide.
+# The key is the name of the node type, which is just for debugging purposes.
+# The node config specifies the launch config and physical instance type.
+available_node_types:
+    # Provider-specific config for the head node, e.g. instance type. By default
+    # Ray will auto-configure unspecified fields such as SubnetId and KeyName.
+    # For more documentation on available fields, see:
+    # http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances
+    ray.head.default:
+      node_config:
+        InstanceType: m4.16xlarge
+        ImageId: ami-0def3275  # Default Ubuntu 16.04 AMI.
+
+        # Set primary volume to 25 GiB
+        BlockDeviceMappings:
+            - DeviceName: /dev/sda1
+              Ebs:
+                  VolumeSize: 50
+
+# List of shell commands to install ray from source.
+setup_commands:
+    # Consider uncommenting these if you run into dpkg locking issues
+    # - sudo pkill -9 apt-get || true
+    # - sudo pkill -9 dpkg || true
+    # - sudo dpkg --configure -a
+    # Install basics.
+    - sudo apt-get update
+    - sudo apt-get install -y build-essential curl unzip
+    # Install Node.js in order to build the dashboard.
+    - curl -sL https://deb.nodesource.com/setup_12.x | sudo -E bash
+    - sudo apt-get install -y nodejs
+    # Install Anaconda.
+    - wget https://repo.continuum.io/archive/Anaconda3-5.0.1-Linux-x86_64.sh || true
+    - bash Anaconda3-5.0.1-Linux-x86_64.sh -b -p $HOME/anaconda3 || true
+    - echo 'export PATH="$HOME/anaconda3/bin:$PATH"' >> ~/.bashrc
+    # Build Ray.
+    - git clone https://github.com/ray-project/ray || true
+    - ray/ci/env/install-bazel.sh
+    - cd ray/python/ray/dashboard/client; npm ci; npm run build
+    - pip install boto3>=1.4.8 cython==0.29.37 aiohttp grpcio psutil setproctitle
+    - cd ray/python; pip install -e . --verbose
+
+# Command to start ray on the head node. You don't need to change this.
+head_start_ray_commands:
+    - ray stop
+    - ulimit -n 65536; ray start --head --port=6379 --autoscaling-config=~/ray_bootstrap_config.yaml
+
+# Command to start ray on worker nodes. You don't need to change this.
+worker_start_ray_commands:
+    - ray stop
+    - ulimit -n 65536; ray start --address=$RAY_HEAD_IP:6379