ray.serve.schema.ScalingDecision

class ray.serve.schema.ScalingDecision

One autoscaling decision with minimal provenance.

PublicAPI (alpha): This API is in alpha and may change before becoming stable.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'curr_num_replicas': FieldInfo(annotation=int, required=True, description='Replica count after the decision.', metadata=[Ge(ge=0)]), 'policy': FieldInfo(annotation=Union[str, NoneType], required=False, description='Policy name or identifier (if applicable).'), 'prev_num_replicas': FieldInfo(annotation=int, required=True, description='Replica count before the decision.', metadata=[Ge(ge=0)]), 'reason': FieldInfo(annotation=str, required=True, description='Short, human-readable reason for the decision.'), 'timestamp_s': FieldInfo(annotation=float, required=True, description='Unix time (seconds) when the decision was made.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.