Package com.google.cloud.aiplatform.v1

Class DedicatedResources

  • All Implemented Interfaces:
    DedicatedResourcesOrBuilder, com.google.protobuf.Message, com.google.protobuf.MessageLite, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Serializable
    public final class DedicatedResources
extends com.google.protobuf.GeneratedMessageV3
implements DedicatedResourcesOrBuilder
     A description of resources that are dedicated to a DeployedModel, and
 that need a higher degree of manual configuration.
    Protobuf type google.cloud.aiplatform.v1.DedicatedResources
    See Also:
    Serialized Form

    • Field Detail

      • MACHINE_SPEC_FIELD_NUMBER

        public static final int MACHINE_SPEC_FIELD_NUMBER
        See Also:
        Constant Field Values

      • MIN_REPLICA_COUNT_FIELD_NUMBER

        public static final int MIN_REPLICA_COUNT_FIELD_NUMBER
        See Also:
        Constant Field Values

      • MAX_REPLICA_COUNT_FIELD_NUMBER

        public static final int MAX_REPLICA_COUNT_FIELD_NUMBER
        See Also:
        Constant Field Values

      • AUTOSCALING_METRIC_SPECS_FIELD_NUMBER

        public static final int AUTOSCALING_METRIC_SPECS_FIELD_NUMBER
        See Also:
        Constant Field Values

    • Method Detail

      • newInstance

        protected Object newInstance​(com.google.protobuf.GeneratedMessageV3.UnusedPrivateParameter unused)
        Overrides:
        newInstance in class com.google.protobuf.GeneratedMessageV3

      • getDescriptor

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

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3

      • hasMachineSpec

        public boolean hasMachineSpec()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .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 used by the
 prediction.
        .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.

      • getMachineSpecOrBuilder

        public MachineSpecOrBuilder getMachineSpecOrBuilder()
         Required. Immutable. The specification of a single machine used by the
 prediction.
        .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 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];
        Specified by:
        getMinReplicaCount in interface DedicatedResourcesOrBuilder
        Returns:
        The minReplicaCount.

      • getMaxReplicaCount

        public 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.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.

      • 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

      • 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

      • 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

      • 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

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3

      • writeTo

        public void writeTo​(com.google.protobuf.CodedOutputStream output)
             throws IOException
        Specified by:
        writeTo in interface com.google.protobuf.MessageLite
        Overrides:
        writeTo in class com.google.protobuf.GeneratedMessageV3
        Throws:
        IOException

      • getSerializedSize

        public int getSerializedSize()
        Specified by:
        getSerializedSize in interface com.google.protobuf.MessageLite
        Overrides:
        getSerializedSize in class com.google.protobuf.GeneratedMessageV3

      • equals

        public boolean equals​(Object obj)
        Specified by:
        equals in interface com.google.protobuf.Message
        Overrides:
        equals in class com.google.protobuf.AbstractMessage

      • hashCode

        public int hashCode()
        Specified by:
        hashCode in interface com.google.protobuf.Message
        Overrides:
        hashCode in class com.google.protobuf.AbstractMessage

      • parseFrom

        public static DedicatedResources parseFrom​(ByteBuffer data)
                                    throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static DedicatedResources parseFrom​(ByteBuffer data,
                                           com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                    throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static DedicatedResources parseFrom​(com.google.protobuf.ByteString data)
                                    throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static DedicatedResources parseFrom​(com.google.protobuf.ByteString data,
                                           com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                    throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static DedicatedResources parseFrom​(byte[] data)
                                    throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static DedicatedResources parseFrom​(byte[] data,
                                           com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                    throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static DedicatedResources parseFrom​(com.google.protobuf.CodedInputStream input,
                                           com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                    throws IOException
        Throws:
        IOException

      • newBuilderForType

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

      • toBuilder

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

      • newBuilderForType

        protected DedicatedResources.Builder newBuilderForType​(com.google.protobuf.GeneratedMessageV3.BuilderParent parent)
        Specified by:
        newBuilderForType in class com.google.protobuf.GeneratedMessageV3

      • getParserForType

        public com.google.protobuf.Parser<DedicatedResources> getParserForType()
        Specified by:
        getParserForType in interface com.google.protobuf.Message
        Specified by:
        getParserForType in interface com.google.protobuf.MessageLite
        Overrides:
        getParserForType in class com.google.protobuf.GeneratedMessageV3

      • getDefaultInstanceForType

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