wehub-resource-sync
159 lines
6.6 KiB
YAML
159 lines
6.6 KiB
YAML
# An unique identifier for the head node and workers of this cluster.
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cluster_name: default
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# The maximum number of workers nodes to launch in addition to the head
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# node.
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max_workers: 2
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# The autoscaler will scale up the cluster faster with higher upscaling speed.
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# E.g., if the task requires adding more nodes then autoscaler will gradually
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# scale up the cluster in chunks of upscaling_speed*currently_running_nodes.
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# This number should be > 0.
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upscaling_speed: 1.0
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# This executes all commands on all nodes in the docker container,
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# and opens all the necessary ports to support the Ray cluster.
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# Empty string means disabled.
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docker: {}
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# If a node is idle for this many minutes, it will be removed.
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idle_timeout_minutes: 5
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# Cloud-provider specific configuration.
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provider:
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type: aliyun
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region: cn-hangzhou
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zone_id: cn-hangzhou-b
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cidr_block: 172.16.0.0/24
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# Whether to allow node reuse. If set to False, nodes will be terminated
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# instead of stopped.
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cache_stopped_nodes: True # If not present, the default is True.
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access_key:
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access_key_secret:
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# KeyPair Name on aliyun. If not set, the default value is "ray"
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key_name: ray
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security_group_rule:
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- port_range: "22/22"
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source_cidr_ip: "0.0.0.0/0"
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ip_protocol: "tcp"
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- port_range: "8265/8265"
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source_cidr_ip: "0.0.0.0/0"
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ip_protocol: "tcp"
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# How Ray will authenticate with newly launched nodes.
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auth:
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ssh_user: root
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# By default Ray creates a new private keypair, but you can also use your own.
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# If you do so, make sure to also set "key_name".
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# ssh_private_key: ~/.ssh/ray
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# Tell the autoscaler the allowed node types and the resources they provide.
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# The key is the name of the node type, which is just for debugging purposes.
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# The node config specifies the launch config and physical instance type.
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available_node_types:
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ray.head.default:
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# The node type's CPU and GPU resources are auto-detected based on aliyun instance type.
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# If desired, you can override the autodetected CPU and GPU resources advertised to the autoscaler.
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# You can also set custom resources.
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# For example, to mark a node type as having 1 CPU, 1 GPU, and 5 units of a resource called "custom", set
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# resources: {"CPU": 1, "GPU": 1, "custom": 5}
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resources: {"CPU": 2}
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# Provider-specific config for this node type, e.g. instance type. By default
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node_config:
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InstanceType: ecs.n4.large
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ImageId: ubuntu_20_04_x64_20G_alibase_20210420.vhd
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# You can provision additional disk space with a conf as follows
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BlockDeviceMappings:
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- DeviceName: /dev/sda1
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Ebs:
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VolumeSize: 140
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# Additional options in the boto docs.
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ray.worker.default:
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# The minimum number of nodes of this type to launch.
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# This number should be >= 0.
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min_workers: 1
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# The node type's CPU and GPU resources are auto-detected based on aliyun instance type.
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# If desired, you can override the autodetected CPU and GPU resources advertised to the autoscaler.
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# You can also set custom resources.
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# For example, to mark a node type as having 1 CPU, 1 GPU, and 5 units of a resource called "custom", set
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# resources: {"CPU": 1, "GPU": 1, "custom": 5}
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resources: {"CPU": 8}
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# Provider-specific config for this node type, e.g. instance type. By default
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# Ray will auto-configure unspecified fields such as SubnetId.
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node_config:
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InstanceType: ecs.n4.2xlarge
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ImageId: ubuntu_20_04_x64_20G_alibase_20210420.vhd
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# KeyPairName: id_rsa.pub
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# Run workers on spot by default. Comment this out to use on-demand.
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InstanceMarketOptions:
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MarketType: spot
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# Additional options can be found in the boto docs, e.g.
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# SpotOptions:
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# MaxPrice: MAX_HOURLY_PRICE
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# Specify the node type of the head node (as configured above).
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head_node_type: ray.head.default
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# Files or directories to copy to the head and worker nodes. The format is a
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# dictionary from REMOTE_PATH: LOCAL_PATH, e.g.
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file_mounts: {
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# "~/dist":"~/alipay/ray/python/dist",
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# "/path2/on/remote/machine": "/path2/on/local/machine",
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}
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# Files or directories to copy from the head node to the worker nodes. The format is a
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# list of paths. The same path on the head node will be copied to the worker node.
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# This behavior is a subset of the file_mounts behavior. In the vast majority of cases
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# you should just use file_mounts. Only use this if you know what you're doing!
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cluster_synced_files: []
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# Whether changes to directories in file_mounts or cluster_synced_files in the head node
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# should sync to the worker node continuously
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file_mounts_sync_continuously: False
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# Patterns for files to exclude when running rsync up or rsync down
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rsync_exclude: []
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# Pattern files to use for filtering out files when running rsync up or rsync down. The file is searched for
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# in the source directory and recursively through all subdirectories. For example, if .gitignore is provided
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# as a value, the behavior will match git's behavior for finding and using .gitignore files.
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rsync_filter: []
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# List of commands that will be run before `setup_commands`. If docker is
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# enabled, these commands will run outside the container and before docker
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# is setup.
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initialization_commands: []
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# List of shell commands to run to set up nodes.
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setup_commands:
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- sudo apt-get update
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# Install Anaconda.
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- wget https://repo.continuum.io/archive/Anaconda3-2020.11-Linux-x86_64.sh || true
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- bash Anaconda3-2020.11-Linux-x86_64.sh -b -p $HOME/anaconda3 || true
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- echo 'export PATH="$HOME/anaconda3/bin:$PATH"' >> ~/.bashrc
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# Install Ray
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- pip install pytest-runner
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- pip install -U ray
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# Custom commands that will be run on the head node after common setup.
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head_setup_commands:
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# Install Aliyun skd
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- pip install aliyun-python-sdk-core
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- pip install aliyun-python-sdk-ecs
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# Custom commands that will be run on worker nodes after common setup.
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worker_setup_commands: []
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# Command to start ray on the head node. You don't need to change this.
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head_start_ray_commands:
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- ray stop
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- ulimit -n 65536; ray start --head --port=6379 --object-manager-port=8076 --dashboard-host=0.0.0.0 --autoscaling-config=~/ray_bootstrap_config.yaml
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# Command to start ray on worker nodes. You don't need to change this.
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worker_start_ray_commands:
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- ray stop
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- ulimit -n 65536; ray start --address=$RAY_HEAD_IP:6379 --object-manager-port=8076
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