Package com.google.cloud.aiplatform.v1beta1

Interface DedicatedResourcesOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    DedicatedResources, DedicatedResources.Builder
    public interface DedicatedResourcesOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Detail

      • hasMachineSpec

        boolean hasMachineSpec()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1beta1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Returns:
        Whether the machineSpec field is set.

      • getMachineSpec

        MachineSpec getMachineSpec()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1beta1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Returns:
        The machineSpec.

      • getMachineSpecOrBuilder

        MachineSpecOrBuilder getMachineSpecOrBuilder()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .google.cloud.aiplatform.v1beta1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

      • getMinReplicaCount

        int getMinReplicaCount()
         Required. Immutable. The minimum number of machine replicas this
 DeployedModel will be always deployed on. This value must be greater than
 or equal to 1.

 If traffic against the DeployedModel increases, it may dynamically be
 deployed onto more replicas, and as traffic decreases, some of these extra
 replicas may be freed.
        int32 min_replica_count = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];
        Returns:
        The minReplicaCount.

      • getMaxReplicaCount

        int getMaxReplicaCount()
         Immutable. The maximum number of replicas this DeployedModel may be
 deployed on when the traffic against it increases. If the requested value
 is too large, the deployment will error, but if deployment succeeds then
 the ability to scale the model to that many replicas is guaranteed (barring
 service outages). If traffic against the DeployedModel increases beyond
 what its replicas at maximum may handle, a portion of the traffic will be
 dropped. If this value is not provided, will use
 [min_replica_count][google.cloud.aiplatform.v1beta1.DedicatedResources.min_replica_count]
 as the default value.

 The value of this field impacts the charge against Vertex CPU and GPU
 quotas. Specifically, you will be charged for (max_replica_count *
 number of cores in the selected machine type) and (max_replica_count *
 number of GPUs per replica in the selected machine type).
        int32 max_replica_count = 3 [(.google.api.field_behavior) = IMMUTABLE];
        Returns:
        The maxReplicaCount.

      • getAutoscalingMetricSpecsList

        List<AutoscalingMetricSpec> getAutoscalingMetricSpecsList()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getAutoscalingMetricSpecs

        AutoscalingMetricSpec getAutoscalingMetricSpecs​(int index)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getAutoscalingMetricSpecsCount

        int getAutoscalingMetricSpecsCount()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getAutoscalingMetricSpecsOrBuilderList

        List<? extends AutoscalingMetricSpecOrBuilder> getAutoscalingMetricSpecsOrBuilderList()
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

      • getAutoscalingMetricSpecsOrBuilder

        AutoscalingMetricSpecOrBuilder getAutoscalingMetricSpecsOrBuilder​(int index)
         Immutable. The metric specifications that overrides a resource
 utilization metric (CPU utilization, accelerator's duty cycle, and so on)
 target value (default to 60 if not set). At most one entry is allowed per
 metric.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is above 0, the autoscaling will be based on both CPU utilization and
 accelerator's duty cycle metrics and scale up when either metrics exceeds
 its target value while scale down if both metrics are under their target
 value. The default target value is 60 for both metrics.

 If
 [machine_spec.accelerator_count][google.cloud.aiplatform.v1beta1.MachineSpec.accelerator_count]
 is 0, the autoscaling will be based on CPU utilization metric only with
 default target value 60 if not explicitly set.

 For example, in the case of Online Prediction, if you want to override
 target CPU utilization to 80, you should set
 [autoscaling_metric_specs.metric_name][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec.target]
 to `80`.
        repeated .google.cloud.aiplatform.v1beta1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];