ray.serve.schema.DeploymentAutoscalingDetail

class ray.serve.schema.DeploymentAutoscalingDetail

Deployment-level autoscaler observability.

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]] = {'decisions': FieldInfo(annotation=List[ScalingDecision], required=False, default_factory=list, description='Recent scaling decisions.'), 'errors': FieldInfo(annotation=List[str], required=False, default_factory=list, description='Recent errors/abnormal events.'), 'metrics': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, description='Aggregated metrics for this deployment.'), 'metrics_health': FieldInfo(annotation=AutoscalingMetricsHealth, required=False, default=<AutoscalingMetricsHealth.HEALTHY: 'healthy'>, description='Health of metrics collection pipeline.'), 'scaling_status': FieldInfo(annotation=AutoscalingStatus, required=True, description='Current scaling direction or stability.')}

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

This replaces Model.__fields__ from Pydantic V1.