Package com.google.cloud.aiplatform.v1

Interface DedicatedResourcesOrBuilder

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

  • Method Details

    • hasMachineSpec

      boolean hasMachineSpec()
       Required. Immutable. The specification of a single machine being used.
      .google.cloud.aiplatform.v1.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 being used.
      .google.cloud.aiplatform.v1.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 being used.
      .google.cloud.aiplatform.v1.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 that will be
 always deployed on. This value must be greater than or equal to 1.

 If traffic 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 that 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
 to that many replicas is guaranteed (barring service outages). If traffic
 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.v1.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.

    • getRequiredReplicaCount

      int getRequiredReplicaCount()
       Optional. Number of required available replicas for the deployment to
 succeed. This field is only needed when partial deployment/mutation is
 desired. If set, the deploy/mutate operation will succeed once
 available_replica_count reaches required_replica_count, and the rest of
 the replicas will be retried. If not set, the default
 required_replica_count will be min_replica_count.
      int32 required_replica_count = 9 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The requiredReplicaCount.

    • 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.v1.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.v1.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.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
      repeated .google.cloud.aiplatform.v1.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.v1.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.v1.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.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
      repeated .google.cloud.aiplatform.v1.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.v1.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.v1.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.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
      repeated .google.cloud.aiplatform.v1.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.v1.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.v1.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.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
      repeated .google.cloud.aiplatform.v1.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.v1.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.v1.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.v1.AutoscalingMetricSpec.metric_name]
 to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and
 [autoscaling_metric_specs.target][google.cloud.aiplatform.v1.AutoscalingMetricSpec.target]
 to `80`.
      repeated .google.cloud.aiplatform.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

    • getSpot

      boolean getSpot()
       Optional. If true, schedule the deployment workload on [spot
 VMs](https://cloud.google.com/kubernetes-engine/docs/concepts/spot-vms).
      bool spot = 5 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The spot.