Class DedicatedResources (0.3.0)

public final class DedicatedResources extends 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.vertexai.v1.DedicatedResources

Static Fields

AUTOSCALING_METRIC_SPECS_FIELD_NUMBER

public static final int AUTOSCALING_METRIC_SPECS_FIELD_NUMBER
Field Value
TypeDescription
int

MACHINE_SPEC_FIELD_NUMBER

public static final int MACHINE_SPEC_FIELD_NUMBER
Field Value
TypeDescription
int

MAX_REPLICA_COUNT_FIELD_NUMBER

public static final int MAX_REPLICA_COUNT_FIELD_NUMBER
Field Value
TypeDescription
int

MIN_REPLICA_COUNT_FIELD_NUMBER

public static final int MIN_REPLICA_COUNT_FIELD_NUMBER
Field Value
TypeDescription
int

Static Methods

getDefaultInstance()

public static DedicatedResources getDefaultInstance()
Returns
TypeDescription
DedicatedResources

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

newBuilder()

public static DedicatedResources.Builder newBuilder()
Returns
TypeDescription
DedicatedResources.Builder

newBuilder(DedicatedResources prototype)

public static DedicatedResources.Builder newBuilder(DedicatedResources prototype)
Parameter
NameDescription
prototypeDedicatedResources
Returns
TypeDescription
DedicatedResources.Builder

parseDelimitedFrom(InputStream input)

public static DedicatedResources parseDelimitedFrom(InputStream input)
Parameter
NameDescription
inputInputStream
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static DedicatedResources parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
IOException

parseFrom(byte[] data)

public static DedicatedResources parseFrom(byte[] data)
Parameter
NameDescription
databyte[]
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static DedicatedResources parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
databyte[]
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteString data)

public static DedicatedResources parseFrom(ByteString data)
Parameter
NameDescription
dataByteString
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static DedicatedResources parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
dataByteString
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static DedicatedResources parseFrom(CodedInputStream input)
Parameter
NameDescription
inputCodedInputStream
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static DedicatedResources parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
IOException

parseFrom(InputStream input)

public static DedicatedResources parseFrom(InputStream input)
Parameter
NameDescription
inputInputStream
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static DedicatedResources parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
IOException

parseFrom(ByteBuffer data)

public static DedicatedResources parseFrom(ByteBuffer data)
Parameter
NameDescription
dataByteBuffer
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static DedicatedResources parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
dataByteBuffer
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
DedicatedResources
Exceptions
TypeDescription
InvalidProtocolBufferException

parser()

public static Parser<DedicatedResources> parser()
Returns
TypeDescription
Parser<DedicatedResources>

Methods

equals(Object obj)

public boolean equals(Object obj)
Parameter
NameDescription
objObject
Returns
TypeDescription
boolean
Overrides

getAutoscalingMetricSpecs(int index)

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 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 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 to aiplatform.googleapis.com/prediction/online/cpu/utilization and autoscaling_metric_specs.target to 80.

repeated .google.cloud.vertexai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

Parameter
NameDescription
indexint
Returns
TypeDescription
AutoscalingMetricSpec

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 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 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 to aiplatform.googleapis.com/prediction/online/cpu/utilization and autoscaling_metric_specs.target to 80.

repeated .google.cloud.vertexai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

Returns
TypeDescription
int

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 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 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 to aiplatform.googleapis.com/prediction/online/cpu/utilization and autoscaling_metric_specs.target to 80.

repeated .google.cloud.vertexai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

Returns
TypeDescription
List<AutoscalingMetricSpec>

getAutoscalingMetricSpecsOrBuilder(int index)

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 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 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 to aiplatform.googleapis.com/prediction/online/cpu/utilization and autoscaling_metric_specs.target to 80.

repeated .google.cloud.vertexai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

Parameter
NameDescription
indexint
Returns
TypeDescription
AutoscalingMetricSpecOrBuilder

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 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 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 to aiplatform.googleapis.com/prediction/online/cpu/utilization and autoscaling_metric_specs.target to 80.

repeated .google.cloud.vertexai.v1.AutoscalingMetricSpec autoscaling_metric_specs = 4 [(.google.api.field_behavior) = IMMUTABLE];

Returns
TypeDescription
List<? extends com.google.cloud.vertexai.api.AutoscalingMetricSpecOrBuilder>

getDefaultInstanceForType()

public DedicatedResources getDefaultInstanceForType()
Returns
TypeDescription
DedicatedResources

getMachineSpec()

public MachineSpec getMachineSpec()

Required. Immutable. The specification of a single machine used by the prediction.

.google.cloud.vertexai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

Returns
TypeDescription
MachineSpec

The machineSpec.

getMachineSpecOrBuilder()

public MachineSpecOrBuilder getMachineSpecOrBuilder()

Required. Immutable. The specification of a single machine used by the prediction.

.google.cloud.vertexai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

Returns
TypeDescription
MachineSpecOrBuilder

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 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
TypeDescription
int

The maxReplicaCount.

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];

Returns
TypeDescription
int

The minReplicaCount.

getParserForType()

public Parser<DedicatedResources> getParserForType()
Returns
TypeDescription
Parser<DedicatedResources>
Overrides

getSerializedSize()

public int getSerializedSize()
Returns
TypeDescription
int
Overrides

hasMachineSpec()

public boolean hasMachineSpec()

Required. Immutable. The specification of a single machine used by the prediction.

.google.cloud.vertexai.v1.MachineSpec machine_spec = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.field_behavior) = IMMUTABLE];

Returns
TypeDescription
boolean

Whether the machineSpec field is set.

hashCode()

public int hashCode()
Returns
TypeDescription
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

newBuilderForType()

public DedicatedResources.Builder newBuilderForType()
Returns
TypeDescription
DedicatedResources.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected DedicatedResources.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
NameDescription
parentBuilderParent
Returns
TypeDescription
DedicatedResources.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
NameDescription
unusedUnusedPrivateParameter
Returns
TypeDescription
Object
Overrides

toBuilder()

public DedicatedResources.Builder toBuilder()
Returns
TypeDescription
DedicatedResources.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
NameDescription
outputCodedOutputStream
Overrides
Exceptions
TypeDescription
IOException