wehub-resource-sync
49 lines
2.5 KiB
YAML
49 lines
2.5 KiB
YAML
# An unique identifier for the head node and workers of this cluster.
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cluster_name: aws-example-minimal
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# Cloud-provider specific configuration.
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provider:
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type: aws
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region: us-west-2
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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: 3
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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 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 AWS 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: {}
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# Provider-specific config for this node type, e.g., instance type. By default
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# Ray auto-configures unspecified fields such as SubnetId and KeyName.
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# For more documentation on available fields, see
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# http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances
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node_config:
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InstanceType: m5.large
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ray.worker.default:
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# The minimum number of worker nodes of this type to launch.
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# This number should be >= 0.
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min_workers: 3
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# The maximum number of worker nodes of this type to launch.
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# This parameter takes precedence over min_workers.
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max_workers: 3
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# The node type's CPU and GPU resources are auto-detected based on AWS 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: {}
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# Provider-specific config for this node type, e.g., instance type. By default
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# Ray auto-configures unspecified fields such as SubnetId and KeyName.
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# For more documentation on available fields, see
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# http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances
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node_config:
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InstanceType: m5.large
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