Package com.google.cloud.aiplatform.v1

Class DedicatedResources.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<DedicatedResources.Builder>
com.google.cloud.aiplatform.v1.DedicatedResources.Builder
All Implemented Interfaces:
DedicatedResourcesOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
DedicatedResources
public static final class DedicatedResources.Builder extends com.google.protobuf.GeneratedMessage.Builder<DedicatedResources.Builder> implements DedicatedResourcesOrBuilder
 A description of resources that are dedicated to a DeployedModel or
 DeployedIndex, and that need a higher degree of manual configuration.
Protobuf type google.cloud.aiplatform.v1.DedicatedResources

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<DedicatedResources.Builder>

    • clear

      public DedicatedResources.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<DedicatedResources.Builder>

    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<DedicatedResources.Builder>

    • getDefaultInstanceForType

      public DedicatedResources getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public DedicatedResources build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

      public DedicatedResources buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder

    • mergeFrom

      public DedicatedResources.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<DedicatedResources.Builder>

    • mergeFrom

      public DedicatedResources.Builder mergeFrom(DedicatedResources other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<DedicatedResources.Builder>

    • mergeFrom

      public DedicatedResources.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<DedicatedResources.Builder>
      Throws:
      IOException

    • hasMachineSpec

      public 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];
      Specified by:
      hasMachineSpec in interface DedicatedResourcesOrBuilder
      Returns:
      Whether the machineSpec field is set.

    • getMachineSpec

      public 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];
      Specified by:
      getMachineSpec in interface DedicatedResourcesOrBuilder
      Returns:
      The machineSpec.

    • setMachineSpec

      public DedicatedResources.Builder setMachineSpec(MachineSpec value)
       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];

    • setMachineSpec

      public DedicatedResources.Builder setMachineSpec(MachineSpec.Builder builderForValue)
       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];

    • mergeMachineSpec

      public DedicatedResources.Builder mergeMachineSpec(MachineSpec value)
       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];

    • clearMachineSpec

      public DedicatedResources.Builder clearMachineSpec()
       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];

    • getMachineSpecBuilder

      public MachineSpec.Builder getMachineSpecBuilder()
       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];

    • getMachineSpecOrBuilder

      public 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];
      Specified by:
      getMachineSpecOrBuilder in interface DedicatedResourcesOrBuilder

    • getMinReplicaCount

      public 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];
      Specified by:
      getMinReplicaCount in interface DedicatedResourcesOrBuilder
      Returns:
      The minReplicaCount.

    • setMinReplicaCount

      public DedicatedResources.Builder setMinReplicaCount(int value)
       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];
      Parameters:
      value - The minReplicaCount to set.
      Returns:
      This builder for chaining.

    • clearMinReplicaCount

      public DedicatedResources.Builder clearMinReplicaCount()
       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:
      This builder for chaining.

    • getMaxReplicaCount

      public 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];
      Specified by:
      getMaxReplicaCount in interface DedicatedResourcesOrBuilder
      Returns:
      The maxReplicaCount.

    • setMaxReplicaCount

      public DedicatedResources.Builder setMaxReplicaCount(int value)
       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];
      Parameters:
      value - The maxReplicaCount to set.
      Returns:
      This builder for chaining.

    • clearMaxReplicaCount

      public DedicatedResources.Builder clearMaxReplicaCount()
       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:
      This builder for chaining.

    • getRequiredReplicaCount

      public 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];
      Specified by:
      getRequiredReplicaCount in interface DedicatedResourcesOrBuilder
      Returns:
      The requiredReplicaCount.

    • setRequiredReplicaCount

      public DedicatedResources.Builder setRequiredReplicaCount(int value)
       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];
      Parameters:
      value - The requiredReplicaCount to set.
      Returns:
      This builder for chaining.

    • clearRequiredReplicaCount

      public DedicatedResources.Builder clearRequiredReplicaCount()
       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:
      This builder for chaining.

    • getAutoscalingMetricSpecsList

      public 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];
      Specified by:
      getAutoscalingMetricSpecsList in interface DedicatedResourcesOrBuilder

    • getAutoscalingMetricSpecsCount

      public 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];
      Specified by:
      getAutoscalingMetricSpecsCount in interface DedicatedResourcesOrBuilder

    • getAutoscalingMetricSpecs

      public 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];
      Specified by:
      getAutoscalingMetricSpecs in interface DedicatedResourcesOrBuilder

    • setAutoscalingMetricSpecs

      public DedicatedResources.Builder setAutoscalingMetricSpecs(int index, AutoscalingMetricSpec value)
       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];

    • setAutoscalingMetricSpecs

      public DedicatedResources.Builder setAutoscalingMetricSpecs(int index, AutoscalingMetricSpec.Builder builderForValue)
       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];

    • addAutoscalingMetricSpecs

      public DedicatedResources.Builder addAutoscalingMetricSpecs(AutoscalingMetricSpec value)
       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];

    • addAutoscalingMetricSpecs

      public DedicatedResources.Builder addAutoscalingMetricSpecs(int index, AutoscalingMetricSpec value)
       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];

    • addAutoscalingMetricSpecs

      public DedicatedResources.Builder addAutoscalingMetricSpecs(AutoscalingMetricSpec.Builder builderForValue)
       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];

    • addAutoscalingMetricSpecs

      public DedicatedResources.Builder addAutoscalingMetricSpecs(int index, AutoscalingMetricSpec.Builder builderForValue)
       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];

    • addAllAutoscalingMetricSpecs

      public DedicatedResources.Builder addAllAutoscalingMetricSpecs(Iterable<? extends AutoscalingMetricSpec> values)
       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];

    • clearAutoscalingMetricSpecs

      public DedicatedResources.Builder clearAutoscalingMetricSpecs()
       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];

    • removeAutoscalingMetricSpecs

      public DedicatedResources.Builder removeAutoscalingMetricSpecs(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];

    • getAutoscalingMetricSpecsBuilder

      public AutoscalingMetricSpec.Builder getAutoscalingMetricSpecsBuilder(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];

    • getAutoscalingMetricSpecsOrBuilder

      public 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];
      Specified by:
      getAutoscalingMetricSpecsOrBuilder in interface DedicatedResourcesOrBuilder

    • getAutoscalingMetricSpecsOrBuilderList

      public 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];
      Specified by:
      getAutoscalingMetricSpecsOrBuilderList in interface DedicatedResourcesOrBuilder

    • addAutoscalingMetricSpecsBuilder

      public AutoscalingMetricSpec.Builder addAutoscalingMetricSpecsBuilder()
       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];

    • addAutoscalingMetricSpecsBuilder

      public AutoscalingMetricSpec.Builder addAutoscalingMetricSpecsBuilder(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];

    • getAutoscalingMetricSpecsBuilderList

      public List<AutoscalingMetricSpec.Builder> getAutoscalingMetricSpecsBuilderList()
       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

      public 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];
      Specified by:
      getSpot in interface DedicatedResourcesOrBuilder
      Returns:
      The spot.

    • setSpot

      public DedicatedResources.Builder setSpot(boolean value)
       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];
      Parameters:
      value - The spot to set.
      Returns:
      This builder for chaining.

    • clearSpot

      public DedicatedResources.Builder clearSpot()
       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:
      This builder for chaining.