# An unique identifier for the head node and workers of this cluster.
cluster_name: default

# The minimum number of workers nodes to launch in addition to the head
# node. This number should be >= 0.
min_workers: 2

# The maximum number of workers nodes to launch in addition to the head
# node. This takes precedence over min_workers.
max_workers: 2

# 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
# By default Ray creates a new private keypair, but you can also use your own.
# If you do so, make sure to also set "KeyName" in the head and worker node
# configurations below.
#    ssh_private_key: /path/to/your/key.pem

# 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
head_node:
    InstanceType: m4.16xlarge
    ImageId: ami-0def3275  # Default Ubuntu 16.04 AMI.

    # Set primary volume to 25 GiB
    BlockDeviceMappings:
        - DeviceName: /dev/sda1
          Ebs:
              VolumeSize: 50

    # Additional options in the boto docs.

# Provider-specific config for worker nodes, 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
worker_nodes:
    InstanceType: m4.16xlarge
    ImageId: ami-0def3275  # Default Ubuntu 16.04 AMI.

    # Set primary volume to 25 GiB
    BlockDeviceMappings:
        - DeviceName: /dev/sda1
          Ebs:
              VolumeSize: 50

    # Run workers on spot by default. Comment this out to use on-demand.
    InstanceMarketOptions:
        MarketType: spot
        # Additional options can be found in the boto docs, e.g.
        #   SpotOptions:
        #       MaxPrice: MAX_HOURLY_PRICE

    # Additional options in the boto docs.

# Files or directories to copy to the head and worker nodes. The format is a
# dictionary from REMOTE_PATH: LOCAL_PATH, e.g.
file_mounts: {
#    "/path1/on/remote/machine": "/path1/on/local/machine",
#    "/path2/on/remote/machine": "/path2/on/local/machine",
}

# List of shell commands to run to set up nodes.
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/travis/install-bazel.sh
    - cd ray/python/ray/dashboard/client; npm ci; npm run build
    - pip install boto3==1.4.8 cython==0.29.0 aiohttp grpcio psutil setproctitle
    - cd ray/python; pip install -e . --verbose

# Custom commands that will be run on the head node after common setup.
head_setup_commands: []

# Custom commands that will be run on worker nodes after common setup.
worker_setup_commands: []

# 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
