Class ModelDeploymentMonitoringJob.Builder (3.50.0)

Version 3.50.0

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public static final class ModelDeploymentMonitoringJob.Builder extends GeneratedMessageV3.Builder<ModelDeploymentMonitoringJob.Builder> implements ModelDeploymentMonitoringJobOrBuilder

Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.

Protobuf type google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ModelDeploymentMonitoringJob.Builder

Implements

ModelDeploymentMonitoringJobOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

Methods

addAllBigqueryTables(Iterable<? extends ModelDeploymentMonitoringBigQueryTable> values)

public ModelDeploymentMonitoringJob.Builder addAllBigqueryTables(Iterable<? extends ModelDeploymentMonitoringBigQueryTable> values)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
values	Iterable<? extends com.google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable>

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addAllModelDeploymentMonitoringObjectiveConfigs(Iterable<? extends ModelDeploymentMonitoringObjectiveConfig> values)

public ModelDeploymentMonitoringJob.Builder addAllModelDeploymentMonitoringObjectiveConfigs(Iterable<? extends ModelDeploymentMonitoringObjectiveConfig> values)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
values	Iterable<? extends com.google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig>

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addBigqueryTables(ModelDeploymentMonitoringBigQueryTable value)

public ModelDeploymentMonitoringJob.Builder addBigqueryTables(ModelDeploymentMonitoringBigQueryTable value)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	ModelDeploymentMonitoringBigQueryTable

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addBigqueryTables(ModelDeploymentMonitoringBigQueryTable.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder addBigqueryTables(ModelDeploymentMonitoringBigQueryTable.Builder builderForValue)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
builderForValue	ModelDeploymentMonitoringBigQueryTable.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable value)

public ModelDeploymentMonitoringJob.Builder addBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable value)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameters
Name	Description
index	int
value	ModelDeploymentMonitoringBigQueryTable

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder addBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable.Builder builderForValue)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameters
Name	Description
index	int
builderForValue	ModelDeploymentMonitoringBigQueryTable.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addBigqueryTablesBuilder()

public ModelDeploymentMonitoringBigQueryTable.Builder addBigqueryTablesBuilder()

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringBigQueryTable.Builder

addBigqueryTablesBuilder(int index)

public ModelDeploymentMonitoringBigQueryTable.Builder addBigqueryTablesBuilder(int index)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringBigQueryTable.Builder

addModelDeploymentMonitoringObjectiveConfigs(ModelDeploymentMonitoringObjectiveConfig value)

public ModelDeploymentMonitoringJob.Builder addModelDeploymentMonitoringObjectiveConfigs(ModelDeploymentMonitoringObjectiveConfig value)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	ModelDeploymentMonitoringObjectiveConfig

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addModelDeploymentMonitoringObjectiveConfigs(ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder addModelDeploymentMonitoringObjectiveConfigs(ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
builderForValue	ModelDeploymentMonitoringObjectiveConfig.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig value)

public ModelDeploymentMonitoringJob.Builder addModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig value)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
index	int
value	ModelDeploymentMonitoringObjectiveConfig

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder addModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
index	int
builderForValue	ModelDeploymentMonitoringObjectiveConfig.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

addModelDeploymentMonitoringObjectiveConfigsBuilder()

public ModelDeploymentMonitoringObjectiveConfig.Builder addModelDeploymentMonitoringObjectiveConfigsBuilder()

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ModelDeploymentMonitoringObjectiveConfig.Builder

addModelDeploymentMonitoringObjectiveConfigsBuilder(int index)

public ModelDeploymentMonitoringObjectiveConfig.Builder addModelDeploymentMonitoringObjectiveConfigsBuilder(int index)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringObjectiveConfig.Builder

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ModelDeploymentMonitoringJob.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public ModelDeploymentMonitoringJob build()

Returns
Type	Description
ModelDeploymentMonitoringJob

buildPartial()

public ModelDeploymentMonitoringJob buildPartial()

Returns
Type	Description
ModelDeploymentMonitoringJob

clear()

public ModelDeploymentMonitoringJob.Builder clear()

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearAnalysisInstanceSchemaUri()

public ModelDeploymentMonitoringJob.Builder clearAnalysisInstanceSchemaUri()

YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze.

If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.

string analysis_instance_schema_uri = 16;

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearBigqueryTables()

public ModelDeploymentMonitoringJob.Builder clearBigqueryTables()

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearCreateTime()

public ModelDeploymentMonitoringJob.Builder clearCreateTime()

Output only. Timestamp when this ModelDeploymentMonitoringJob was created.

.google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearDisplayName()

public ModelDeploymentMonitoringJob.Builder clearDisplayName()

Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearEnableMonitoringPipelineLogs()

public ModelDeploymentMonitoringJob.Builder clearEnableMonitoringPipelineLogs()

If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to Cloud Logging pricing.

bool enable_monitoring_pipeline_logs = 22;

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearEncryptionSpec()

public ModelDeploymentMonitoringJob.Builder clearEncryptionSpec()

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearEndpoint()

public ModelDeploymentMonitoringJob.Builder clearEndpoint()

Required. Endpoint resource name. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearError()

public ModelDeploymentMonitoringJob.Builder clearError()

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

.google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearField(Descriptors.FieldDescriptor field)

public ModelDeploymentMonitoringJob.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
field	FieldDescriptor

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearLabels()

public ModelDeploymentMonitoringJob.Builder clearLabels()

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearLatestMonitoringPipelineMetadata()

public ModelDeploymentMonitoringJob.Builder clearLatestMonitoringPipelineMetadata()

Output only. Latest triggered monitoring pipeline metadata.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearLogTtl()

public ModelDeploymentMonitoringJob.Builder clearLogTtl()

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

.google.protobuf.Duration log_ttl = 17;

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearLoggingSamplingStrategy()

public ModelDeploymentMonitoringJob.Builder clearLoggingSamplingStrategy()

Required. Sample Strategy for logging.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearModelDeploymentMonitoringObjectiveConfigs()

public ModelDeploymentMonitoringJob.Builder clearModelDeploymentMonitoringObjectiveConfigs()

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearModelDeploymentMonitoringScheduleConfig()

public ModelDeploymentMonitoringJob.Builder clearModelDeploymentMonitoringScheduleConfig()

Required. Schedule config for running the monitoring job.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearModelMonitoringAlertConfig()

public ModelDeploymentMonitoringJob.Builder clearModelMonitoringAlertConfig()

Alert config for model monitoring.

.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearName()

public ModelDeploymentMonitoringJob.Builder clearName()

Output only. Resource name of a ModelDeploymentMonitoringJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearNextScheduleTime()

public ModelDeploymentMonitoringJob.Builder clearNextScheduleTime()

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.

.google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

public ModelDeploymentMonitoringJob.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
oneof	OneofDescriptor

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearPredictInstanceSchemaUri()

public ModelDeploymentMonitoringJob.Builder clearPredictInstanceSchemaUri()

YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.

string predict_instance_schema_uri = 9;

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearSamplePredictInstance()

public ModelDeploymentMonitoringJob.Builder clearSamplePredictInstance()

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

.google.protobuf.Value sample_predict_instance = 19;

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearSatisfiesPzi()

public ModelDeploymentMonitoringJob.Builder clearSatisfiesPzi()

Output only. Reserved for future use.

bool satisfies_pzi = 27 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearSatisfiesPzs()

public ModelDeploymentMonitoringJob.Builder clearSatisfiesPzs()

Output only. Reserved for future use.

bool satisfies_pzs = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearScheduleState()

public ModelDeploymentMonitoringJob.Builder clearScheduleState()

Output only. Schedule state when the monitoring job is in Running state.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearState()

public ModelDeploymentMonitoringJob.Builder clearState()

Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.

.google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

clearStatsAnomaliesBaseDirectory()

public ModelDeploymentMonitoringJob.Builder clearStatsAnomaliesBaseDirectory()

Stats anomalies base folder path.

.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clearUpdateTime()

public ModelDeploymentMonitoringJob.Builder clearUpdateTime()

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

.google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

clone()

public ModelDeploymentMonitoringJob.Builder clone()

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

containsLabels(String key)

public boolean containsLabels(String key)

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

map<string, string> labels = 11;

Parameter
Name	Description
key	String

Returns
Type	Description
boolean

getAnalysisInstanceSchemaUri()

public String getAnalysisInstanceSchemaUri()

YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze.

If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.

string analysis_instance_schema_uri = 16;

Returns
Type	Description
String	The analysisInstanceSchemaUri.

getAnalysisInstanceSchemaUriBytes()

public ByteString getAnalysisInstanceSchemaUriBytes()

YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze.

If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.

string analysis_instance_schema_uri = 16;

Returns
Type	Description
ByteString	The bytes for analysisInstanceSchemaUri.

getBigqueryTables(int index)

public ModelDeploymentMonitoringBigQueryTable getBigqueryTables(int index)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringBigQueryTable

getBigqueryTablesBuilder(int index)

public ModelDeploymentMonitoringBigQueryTable.Builder getBigqueryTablesBuilder(int index)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringBigQueryTable.Builder

getBigqueryTablesBuilderList()

public List<ModelDeploymentMonitoringBigQueryTable.Builder> getBigqueryTablesBuilderList()

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
List<Builder>

getBigqueryTablesCount()

public int getBigqueryTablesCount()

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
int

getBigqueryTablesList()

public List<ModelDeploymentMonitoringBigQueryTable> getBigqueryTablesList()

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
List<ModelDeploymentMonitoringBigQueryTable>

getBigqueryTablesOrBuilder(int index)

public ModelDeploymentMonitoringBigQueryTableOrBuilder getBigqueryTablesOrBuilder(int index)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringBigQueryTableOrBuilder

getBigqueryTablesOrBuilderList()

public List<? extends ModelDeploymentMonitoringBigQueryTableOrBuilder> getBigqueryTablesOrBuilderList()

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
List<? extends com.google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTableOrBuilder>

getCreateTime()

public Timestamp getCreateTime()

Output only. Timestamp when this ModelDeploymentMonitoringJob was created.

.google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
Timestamp	The createTime.

getCreateTimeBuilder()

public Timestamp.Builder getCreateTimeBuilder()

Output only. Timestamp when this ModelDeploymentMonitoringJob was created.

.google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
Builder

getCreateTimeOrBuilder()

public TimestampOrBuilder getCreateTimeOrBuilder()

Output only. Timestamp when this ModelDeploymentMonitoringJob was created.

.google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
TimestampOrBuilder

getDefaultInstanceForType()

public ModelDeploymentMonitoringJob getDefaultInstanceForType()

Returns
Type	Description
ModelDeploymentMonitoringJob

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getDisplayName()

public String getDisplayName()

Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
String	The displayName.

getDisplayNameBytes()

public ByteString getDisplayNameBytes()

Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ByteString	The bytes for displayName.

getEnableMonitoringPipelineLogs()

public boolean getEnableMonitoringPipelineLogs()

If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to Cloud Logging pricing.

bool enable_monitoring_pipeline_logs = 22;

Returns
Type	Description
boolean	The enableMonitoringPipelineLogs.

getEncryptionSpec()

public EncryptionSpec getEncryptionSpec()

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;

Returns
Type	Description
EncryptionSpec	The encryptionSpec.

getEncryptionSpecBuilder()

public EncryptionSpec.Builder getEncryptionSpecBuilder()

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;

Returns
Type	Description
EncryptionSpec.Builder

getEncryptionSpecOrBuilder()

public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;

Returns
Type	Description
EncryptionSpecOrBuilder

getEndpoint()

public String getEndpoint()

Required. Endpoint resource name. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type	Description
String	The endpoint.

getEndpointBytes()

public ByteString getEndpointBytes()

Required. Endpoint resource name. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type	Description
ByteString	The bytes for endpoint.

getError()

public Status getError()

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

.google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
com.google.rpc.Status	The error.

getErrorBuilder()

public Status.Builder getErrorBuilder()

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

.google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
com.google.rpc.Status.Builder

getErrorOrBuilder()

public StatusOrBuilder getErrorOrBuilder()

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

.google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
com.google.rpc.StatusOrBuilder

getLabels() (deprecated)

public Map<String,String> getLabels()

Use #getLabelsMap() instead.

Returns
Type	Description
Map<String,String>

getLabelsCount()

public int getLabelsCount()

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

map<string, string> labels = 11;

Returns
Type	Description
int

getLabelsMap()

public Map<String,String> getLabelsMap()

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

map<string, string> labels = 11;

Returns
Type	Description
Map<String,String>

getLabelsOrDefault(String key, String defaultValue)

public String getLabelsOrDefault(String key, String defaultValue)

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

map<string, string> labels = 11;

Parameters
Name	Description
key	String
defaultValue	String

Returns
Type	Description
String

getLabelsOrThrow(String key)

public String getLabelsOrThrow(String key)

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

map<string, string> labels = 11;

Parameter
Name	Description
key	String

Returns
Type	Description
String

getLatestMonitoringPipelineMetadata()

public ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata getLatestMonitoringPipelineMetadata()

Output only. Latest triggered monitoring pipeline metadata.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata	The latestMonitoringPipelineMetadata.

getLatestMonitoringPipelineMetadataBuilder()

public ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata.Builder getLatestMonitoringPipelineMetadataBuilder()

Output only. Latest triggered monitoring pipeline metadata.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata.Builder

getLatestMonitoringPipelineMetadataOrBuilder()

public ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadataOrBuilder getLatestMonitoringPipelineMetadataOrBuilder()

Output only. Latest triggered monitoring pipeline metadata.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadataOrBuilder

getLogTtl()

public Duration getLogTtl()

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

.google.protobuf.Duration log_ttl = 17;

Returns
Type	Description
Duration	The logTtl.

getLogTtlBuilder()

public Duration.Builder getLogTtlBuilder()

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

.google.protobuf.Duration log_ttl = 17;

Returns
Type	Description
Builder

getLogTtlOrBuilder()

public DurationOrBuilder getLogTtlOrBuilder()

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

.google.protobuf.Duration log_ttl = 17;

Returns
Type	Description
DurationOrBuilder

getLoggingSamplingStrategy()

public SamplingStrategy getLoggingSamplingStrategy()

Required. Sample Strategy for logging.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
SamplingStrategy	The loggingSamplingStrategy.

getLoggingSamplingStrategyBuilder()

public SamplingStrategy.Builder getLoggingSamplingStrategyBuilder()

Required. Sample Strategy for logging.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
SamplingStrategy.Builder

getLoggingSamplingStrategyOrBuilder()

public SamplingStrategyOrBuilder getLoggingSamplingStrategyOrBuilder()

Required. Sample Strategy for logging.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
SamplingStrategyOrBuilder

getModelDeploymentMonitoringObjectiveConfigs(int index)

public ModelDeploymentMonitoringObjectiveConfig getModelDeploymentMonitoringObjectiveConfigs(int index)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringObjectiveConfig

getModelDeploymentMonitoringObjectiveConfigsBuilder(int index)

public ModelDeploymentMonitoringObjectiveConfig.Builder getModelDeploymentMonitoringObjectiveConfigsBuilder(int index)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringObjectiveConfig.Builder

getModelDeploymentMonitoringObjectiveConfigsBuilderList()

public List<ModelDeploymentMonitoringObjectiveConfig.Builder> getModelDeploymentMonitoringObjectiveConfigsBuilderList()

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
List<Builder>

getModelDeploymentMonitoringObjectiveConfigsCount()

public int getModelDeploymentMonitoringObjectiveConfigsCount()

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
int

getModelDeploymentMonitoringObjectiveConfigsList()

public List<ModelDeploymentMonitoringObjectiveConfig> getModelDeploymentMonitoringObjectiveConfigsList()

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
List<ModelDeploymentMonitoringObjectiveConfig>

getModelDeploymentMonitoringObjectiveConfigsOrBuilder(int index)

public ModelDeploymentMonitoringObjectiveConfigOrBuilder getModelDeploymentMonitoringObjectiveConfigsOrBuilder(int index)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringObjectiveConfigOrBuilder

getModelDeploymentMonitoringObjectiveConfigsOrBuilderList()

public List<? extends ModelDeploymentMonitoringObjectiveConfigOrBuilder> getModelDeploymentMonitoringObjectiveConfigsOrBuilderList()

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
List<? extends com.google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfigOrBuilder>

getModelDeploymentMonitoringScheduleConfig()

public ModelDeploymentMonitoringScheduleConfig getModelDeploymentMonitoringScheduleConfig()

Required. Schedule config for running the monitoring job.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ModelDeploymentMonitoringScheduleConfig	The modelDeploymentMonitoringScheduleConfig.

getModelDeploymentMonitoringScheduleConfigBuilder()

public ModelDeploymentMonitoringScheduleConfig.Builder getModelDeploymentMonitoringScheduleConfigBuilder()

Required. Schedule config for running the monitoring job.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ModelDeploymentMonitoringScheduleConfig.Builder

getModelDeploymentMonitoringScheduleConfigOrBuilder()

public ModelDeploymentMonitoringScheduleConfigOrBuilder getModelDeploymentMonitoringScheduleConfigOrBuilder()

Required. Schedule config for running the monitoring job.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
ModelDeploymentMonitoringScheduleConfigOrBuilder

getModelMonitoringAlertConfig()

public ModelMonitoringAlertConfig getModelMonitoringAlertConfig()

Alert config for model monitoring.

.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;

Returns
Type	Description
ModelMonitoringAlertConfig	The modelMonitoringAlertConfig.

getModelMonitoringAlertConfigBuilder()

public ModelMonitoringAlertConfig.Builder getModelMonitoringAlertConfigBuilder()

Alert config for model monitoring.

.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;

Returns
Type	Description
ModelMonitoringAlertConfig.Builder

getModelMonitoringAlertConfigOrBuilder()

public ModelMonitoringAlertConfigOrBuilder getModelMonitoringAlertConfigOrBuilder()

Alert config for model monitoring.

.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;

Returns
Type	Description
ModelMonitoringAlertConfigOrBuilder

getMutableLabels() (deprecated)

public Map<String,String> getMutableLabels()

Use alternate mutation accessors instead.

Returns
Type	Description
Map<String,String>

getName()

public String getName()

Output only. Resource name of a ModelDeploymentMonitoringJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
String	The name.

getNameBytes()

public ByteString getNameBytes()

Output only. Resource name of a ModelDeploymentMonitoringJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ByteString	The bytes for name.

getNextScheduleTime()

public Timestamp getNextScheduleTime()

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.

.google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
Timestamp	The nextScheduleTime.

getNextScheduleTimeBuilder()

public Timestamp.Builder getNextScheduleTimeBuilder()

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.

.google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
Builder

getNextScheduleTimeOrBuilder()

public TimestampOrBuilder getNextScheduleTimeOrBuilder()

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.

.google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
TimestampOrBuilder

getPredictInstanceSchemaUri()

public String getPredictInstanceSchemaUri()

YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.

string predict_instance_schema_uri = 9;

Returns
Type	Description
String	The predictInstanceSchemaUri.

getPredictInstanceSchemaUriBytes()

public ByteString getPredictInstanceSchemaUriBytes()

YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.

string predict_instance_schema_uri = 9;

Returns
Type	Description
ByteString	The bytes for predictInstanceSchemaUri.

getSamplePredictInstance()

public Value getSamplePredictInstance()

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

.google.protobuf.Value sample_predict_instance = 19;

Returns
Type	Description
Value	The samplePredictInstance.

getSamplePredictInstanceBuilder()

public Value.Builder getSamplePredictInstanceBuilder()

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

.google.protobuf.Value sample_predict_instance = 19;

Returns
Type	Description
Builder

getSamplePredictInstanceOrBuilder()

public ValueOrBuilder getSamplePredictInstanceOrBuilder()

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

.google.protobuf.Value sample_predict_instance = 19;

Returns
Type	Description
ValueOrBuilder

getSatisfiesPzi()

public boolean getSatisfiesPzi()

Output only. Reserved for future use.

bool satisfies_pzi = 27 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
boolean	The satisfiesPzi.

getSatisfiesPzs()

public boolean getSatisfiesPzs()

Output only. Reserved for future use.

bool satisfies_pzs = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
boolean	The satisfiesPzs.

getScheduleState()

public ModelDeploymentMonitoringJob.MonitoringScheduleState getScheduleState()

Output only. Schedule state when the monitoring job is in Running state.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
ModelDeploymentMonitoringJob.MonitoringScheduleState	The scheduleState.

getScheduleStateValue()

public int getScheduleStateValue()

Output only. Schedule state when the monitoring job is in Running state.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
int	The enum numeric value on the wire for scheduleState.

getState()

public JobState getState()

Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.

.google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
JobState	The state.

getStateValue()

public int getStateValue()

Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.

.google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
int	The enum numeric value on the wire for state.

getStatsAnomaliesBaseDirectory()

public GcsDestination getStatsAnomaliesBaseDirectory()

Stats anomalies base folder path.

.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;

Returns
Type	Description
GcsDestination	The statsAnomaliesBaseDirectory.

getStatsAnomaliesBaseDirectoryBuilder()

public GcsDestination.Builder getStatsAnomaliesBaseDirectoryBuilder()

Stats anomalies base folder path.

.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;

Returns
Type	Description
GcsDestination.Builder

getStatsAnomaliesBaseDirectoryOrBuilder()

public GcsDestinationOrBuilder getStatsAnomaliesBaseDirectoryOrBuilder()

Stats anomalies base folder path.

.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;

Returns
Type	Description
GcsDestinationOrBuilder

getUpdateTime()

public Timestamp getUpdateTime()

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

.google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
Timestamp	The updateTime.

getUpdateTimeBuilder()

public Timestamp.Builder getUpdateTimeBuilder()

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

.google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
Builder

getUpdateTimeOrBuilder()

public TimestampOrBuilder getUpdateTimeOrBuilder()

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

.google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
TimestampOrBuilder

hasCreateTime()

public boolean hasCreateTime()

Output only. Timestamp when this ModelDeploymentMonitoringJob was created.

.google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
boolean	Whether the createTime field is set.

hasEncryptionSpec()

public boolean hasEncryptionSpec()

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;

Returns
Type	Description
boolean	Whether the encryptionSpec field is set.

hasError()

public boolean hasError()

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

.google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
boolean	Whether the error field is set.

hasLatestMonitoringPipelineMetadata()

public boolean hasLatestMonitoringPipelineMetadata()

Output only. Latest triggered monitoring pipeline metadata.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
boolean	Whether the latestMonitoringPipelineMetadata field is set.

hasLogTtl()

public boolean hasLogTtl()

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

.google.protobuf.Duration log_ttl = 17;

Returns
Type	Description
boolean	Whether the logTtl field is set.

hasLoggingSamplingStrategy()

public boolean hasLoggingSamplingStrategy()

Required. Sample Strategy for logging.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
boolean	Whether the loggingSamplingStrategy field is set.

hasModelDeploymentMonitoringScheduleConfig()

public boolean hasModelDeploymentMonitoringScheduleConfig()

Required. Schedule config for running the monitoring job.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
boolean	Whether the modelDeploymentMonitoringScheduleConfig field is set.

hasModelMonitoringAlertConfig()

public boolean hasModelMonitoringAlertConfig()

Alert config for model monitoring.

.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;

Returns
Type	Description
boolean	Whether the modelMonitoringAlertConfig field is set.

hasNextScheduleTime()

public boolean hasNextScheduleTime()

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.

.google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
boolean	Whether the nextScheduleTime field is set.

hasSamplePredictInstance()

public boolean hasSamplePredictInstance()

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

.google.protobuf.Value sample_predict_instance = 19;

Returns
Type	Description
boolean	Whether the samplePredictInstance field is set.

hasStatsAnomaliesBaseDirectory()

public boolean hasStatsAnomaliesBaseDirectory()

Stats anomalies base folder path.

.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;

Returns
Type	Description
boolean	Whether the statsAnomaliesBaseDirectory field is set.

hasUpdateTime()

public boolean hasUpdateTime()

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

.google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
boolean	Whether the updateTime field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

internalGetMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)

Parameter
Name	Description
number	int

Returns
Type	Description
com.google.protobuf.MapFieldReflectionAccessor

Overrides

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

internalGetMutableMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)

Parameter
Name	Description
number	int

Returns
Type	Description
com.google.protobuf.MapFieldReflectionAccessor

Overrides

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeCreateTime(Timestamp value)

public ModelDeploymentMonitoringJob.Builder mergeCreateTime(Timestamp value)

Output only. Timestamp when this ModelDeploymentMonitoringJob was created.

.google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	Timestamp

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeEncryptionSpec(EncryptionSpec value)

public ModelDeploymentMonitoringJob.Builder mergeEncryptionSpec(EncryptionSpec value)

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;

Parameter
Name	Description
value	EncryptionSpec

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeError(Status value)

public ModelDeploymentMonitoringJob.Builder mergeError(Status value)

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

.google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	com.google.rpc.Status

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeFrom(ModelDeploymentMonitoringJob other)

public ModelDeploymentMonitoringJob.Builder mergeFrom(ModelDeploymentMonitoringJob other)

Parameter
Name	Description
other	ModelDeploymentMonitoringJob

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ModelDeploymentMonitoringJob.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public ModelDeploymentMonitoringJob.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeLatestMonitoringPipelineMetadata(ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata value)

public ModelDeploymentMonitoringJob.Builder mergeLatestMonitoringPipelineMetadata(ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata value)

Output only. Latest triggered monitoring pipeline metadata.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeLogTtl(Duration value)

public ModelDeploymentMonitoringJob.Builder mergeLogTtl(Duration value)

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

.google.protobuf.Duration log_ttl = 17;

Parameter
Name	Description
value	Duration

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeLoggingSamplingStrategy(SamplingStrategy value)

public ModelDeploymentMonitoringJob.Builder mergeLoggingSamplingStrategy(SamplingStrategy value)

Required. Sample Strategy for logging.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	SamplingStrategy

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig value)

public ModelDeploymentMonitoringJob.Builder mergeModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig value)

Required. Schedule config for running the monitoring job.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	ModelDeploymentMonitoringScheduleConfig

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeModelMonitoringAlertConfig(ModelMonitoringAlertConfig value)

public ModelDeploymentMonitoringJob.Builder mergeModelMonitoringAlertConfig(ModelMonitoringAlertConfig value)

Alert config for model monitoring.

.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;

Parameter
Name	Description
value	ModelMonitoringAlertConfig

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeNextScheduleTime(Timestamp value)

public ModelDeploymentMonitoringJob.Builder mergeNextScheduleTime(Timestamp value)

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.

.google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	Timestamp

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeSamplePredictInstance(Value value)

public ModelDeploymentMonitoringJob.Builder mergeSamplePredictInstance(Value value)

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

.google.protobuf.Value sample_predict_instance = 19;

Parameter
Name	Description
value	Value

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeStatsAnomaliesBaseDirectory(GcsDestination value)

public ModelDeploymentMonitoringJob.Builder mergeStatsAnomaliesBaseDirectory(GcsDestination value)

Stats anomalies base folder path.

.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;

Parameter
Name	Description
value	GcsDestination

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ModelDeploymentMonitoringJob.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

mergeUpdateTime(Timestamp value)

public ModelDeploymentMonitoringJob.Builder mergeUpdateTime(Timestamp value)

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

.google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	Timestamp

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

putAllLabels(Map<String,String> values)

public ModelDeploymentMonitoringJob.Builder putAllLabels(Map<String,String> values)

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

map<string, string> labels = 11;

Parameter
Name	Description
values	Map<String,String>

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

putLabels(String key, String value)

public ModelDeploymentMonitoringJob.Builder putLabels(String key, String value)

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

map<string, string> labels = 11;

Parameters
Name	Description
key	String
value	String

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

removeBigqueryTables(int index)

public ModelDeploymentMonitoringJob.Builder removeBigqueryTables(int index)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

removeLabels(String key)

public ModelDeploymentMonitoringJob.Builder removeLabels(String key)

The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

map<string, string> labels = 11;

Parameter
Name	Description
key	String

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

removeModelDeploymentMonitoringObjectiveConfigs(int index)

public ModelDeploymentMonitoringJob.Builder removeModelDeploymentMonitoringObjectiveConfigs(int index)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
index	int

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setAnalysisInstanceSchemaUri(String value)

public ModelDeploymentMonitoringJob.Builder setAnalysisInstanceSchemaUri(String value)

YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze.

If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.

string analysis_instance_schema_uri = 16;

Parameter
Name	Description
value	String The analysisInstanceSchemaUri to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setAnalysisInstanceSchemaUriBytes(ByteString value)

public ModelDeploymentMonitoringJob.Builder setAnalysisInstanceSchemaUriBytes(ByteString value)

YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze.

If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.

string analysis_instance_schema_uri = 16;

Parameter
Name	Description
value	ByteString The bytes for analysisInstanceSchemaUri to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable value)

public ModelDeploymentMonitoringJob.Builder setBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable value)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameters
Name	Description
index	int
value	ModelDeploymentMonitoringBigQueryTable

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setBigqueryTables(int index, ModelDeploymentMonitoringBigQueryTable.Builder builderForValue)

Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum:

1. Training data logging predict request/response
2. Serving data logging predict request/response

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringBigQueryTable bigquery_tables = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameters
Name	Description
index	int
builderForValue	ModelDeploymentMonitoringBigQueryTable.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setCreateTime(Timestamp value)

public ModelDeploymentMonitoringJob.Builder setCreateTime(Timestamp value)

Output only. Timestamp when this ModelDeploymentMonitoringJob was created.

.google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	Timestamp

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setCreateTime(Timestamp.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setCreateTime(Timestamp.Builder builderForValue)

Output only. Timestamp when this ModelDeploymentMonitoringJob was created.

.google.protobuf.Timestamp create_time = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
builderForValue	Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setDisplayName(String value)

public ModelDeploymentMonitoringJob.Builder setDisplayName(String value)

Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	String The displayName to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setDisplayNameBytes(ByteString value)

public ModelDeploymentMonitoringJob.Builder setDisplayNameBytes(ByteString value)

Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.

string display_name = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	ByteString The bytes for displayName to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setEnableMonitoringPipelineLogs(boolean value)

public ModelDeploymentMonitoringJob.Builder setEnableMonitoringPipelineLogs(boolean value)

If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to Cloud Logging pricing.

bool enable_monitoring_pipeline_logs = 22;

Parameter
Name	Description
value	boolean The enableMonitoringPipelineLogs to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setEncryptionSpec(EncryptionSpec value)

public ModelDeploymentMonitoringJob.Builder setEncryptionSpec(EncryptionSpec value)

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;

Parameter
Name	Description
value	EncryptionSpec

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setEncryptionSpec(EncryptionSpec.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setEncryptionSpec(EncryptionSpec.Builder builderForValue)

Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.

.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;

Parameter
Name	Description
builderForValue	EncryptionSpec.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setEndpoint(String value)

public ModelDeploymentMonitoringJob.Builder setEndpoint(String value)

Required. Endpoint resource name. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Parameter
Name	Description
value	String The endpoint to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setEndpointBytes(ByteString value)

public ModelDeploymentMonitoringJob.Builder setEndpointBytes(ByteString value)

Required. Endpoint resource name. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

string endpoint = 3 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Parameter
Name	Description
value	ByteString The bytes for endpoint to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setError(Status value)

public ModelDeploymentMonitoringJob.Builder setError(Status value)

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

.google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	com.google.rpc.Status

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setError(Status.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setError(Status.Builder builderForValue)

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

.google.rpc.Status error = 23 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
builderForValue	com.google.rpc.Status.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public ModelDeploymentMonitoringJob.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setLatestMonitoringPipelineMetadata(ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata value)

public ModelDeploymentMonitoringJob.Builder setLatestMonitoringPipelineMetadata(ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata value)

Output only. Latest triggered monitoring pipeline metadata.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setLatestMonitoringPipelineMetadata(ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setLatestMonitoringPipelineMetadata(ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata.Builder builderForValue)

Output only. Latest triggered monitoring pipeline metadata.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata latest_monitoring_pipeline_metadata = 25 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
builderForValue	ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setLogTtl(Duration value)

public ModelDeploymentMonitoringJob.Builder setLogTtl(Duration value)

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

.google.protobuf.Duration log_ttl = 17;

Parameter
Name	Description
value	Duration

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setLogTtl(Duration.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setLogTtl(Duration.Builder builderForValue)

The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day.

.google.protobuf.Duration log_ttl = 17;

Parameter
Name	Description
builderForValue	Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setLoggingSamplingStrategy(SamplingStrategy value)

public ModelDeploymentMonitoringJob.Builder setLoggingSamplingStrategy(SamplingStrategy value)

Required. Sample Strategy for logging.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	SamplingStrategy

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setLoggingSamplingStrategy(SamplingStrategy.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setLoggingSamplingStrategy(SamplingStrategy.Builder builderForValue)

Required. Sample Strategy for logging.

.google.cloud.aiplatform.v1.SamplingStrategy logging_sampling_strategy = 8 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
builderForValue	SamplingStrategy.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig value)

public ModelDeploymentMonitoringJob.Builder setModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig value)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
index	int
value	ModelDeploymentMonitoringObjectiveConfig

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setModelDeploymentMonitoringObjectiveConfigs(int index, ModelDeploymentMonitoringObjectiveConfig.Builder builderForValue)

Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately.

repeated .google.cloud.aiplatform.v1.ModelDeploymentMonitoringObjectiveConfig model_deployment_monitoring_objective_configs = 6 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
index	int
builderForValue	ModelDeploymentMonitoringObjectiveConfig.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig value)

public ModelDeploymentMonitoringJob.Builder setModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig value)

Required. Schedule config for running the monitoring job.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
value	ModelDeploymentMonitoringScheduleConfig

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig.Builder builderForValue)

Required. Schedule config for running the monitoring job.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringScheduleConfig model_deployment_monitoring_schedule_config = 7 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
builderForValue	ModelDeploymentMonitoringScheduleConfig.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setModelMonitoringAlertConfig(ModelMonitoringAlertConfig value)

public ModelDeploymentMonitoringJob.Builder setModelMonitoringAlertConfig(ModelMonitoringAlertConfig value)

Alert config for model monitoring.

.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;

Parameter
Name	Description
value	ModelMonitoringAlertConfig

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setModelMonitoringAlertConfig(ModelMonitoringAlertConfig.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setModelMonitoringAlertConfig(ModelMonitoringAlertConfig.Builder builderForValue)

Alert config for model monitoring.

.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;

Parameter
Name	Description
builderForValue	ModelMonitoringAlertConfig.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setName(String value)

public ModelDeploymentMonitoringJob.Builder setName(String value)

Output only. Resource name of a ModelDeploymentMonitoringJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	String The name to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setNameBytes(ByteString value)

public ModelDeploymentMonitoringJob.Builder setNameBytes(ByteString value)

Output only. Resource name of a ModelDeploymentMonitoringJob.

string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	ByteString The bytes for name to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setNextScheduleTime(Timestamp value)

public ModelDeploymentMonitoringJob.Builder setNextScheduleTime(Timestamp value)

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.

.google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	Timestamp

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setNextScheduleTime(Timestamp.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setNextScheduleTime(Timestamp.Builder builderForValue)

Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round.

.google.protobuf.Timestamp next_schedule_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
builderForValue	Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setPredictInstanceSchemaUri(String value)

public ModelDeploymentMonitoringJob.Builder setPredictInstanceSchemaUri(String value)

YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.

string predict_instance_schema_uri = 9;

Parameter
Name	Description
value	String The predictInstanceSchemaUri to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setPredictInstanceSchemaUriBytes(ByteString value)

public ModelDeploymentMonitoringJob.Builder setPredictInstanceSchemaUriBytes(ByteString value)

YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.

string predict_instance_schema_uri = 9;

Parameter
Name	Description
value	ByteString The bytes for predictInstanceSchemaUri to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public ModelDeploymentMonitoringJob.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters
Name	Description
field	FieldDescriptor
index	int
value	Object

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setSamplePredictInstance(Value value)

public ModelDeploymentMonitoringJob.Builder setSamplePredictInstance(Value value)

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

.google.protobuf.Value sample_predict_instance = 19;

Parameter
Name	Description
value	Value

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setSamplePredictInstance(Value.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setSamplePredictInstance(Value.Builder builderForValue)

Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.

.google.protobuf.Value sample_predict_instance = 19;

Parameter
Name	Description
builderForValue	Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setSatisfiesPzi(boolean value)

public ModelDeploymentMonitoringJob.Builder setSatisfiesPzi(boolean value)

Output only. Reserved for future use.

bool satisfies_pzi = 27 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	boolean The satisfiesPzi to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setSatisfiesPzs(boolean value)

public ModelDeploymentMonitoringJob.Builder setSatisfiesPzs(boolean value)

Output only. Reserved for future use.

bool satisfies_pzs = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	boolean The satisfiesPzs to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setScheduleState(ModelDeploymentMonitoringJob.MonitoringScheduleState value)

public ModelDeploymentMonitoringJob.Builder setScheduleState(ModelDeploymentMonitoringJob.MonitoringScheduleState value)

Output only. Schedule state when the monitoring job is in Running state.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	ModelDeploymentMonitoringJob.MonitoringScheduleState The scheduleState to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setScheduleStateValue(int value)

public ModelDeploymentMonitoringJob.Builder setScheduleStateValue(int value)

Output only. Schedule state when the monitoring job is in Running state.

.google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob.MonitoringScheduleState schedule_state = 5 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	int The enum numeric value on the wire for scheduleState to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setState(JobState value)

public ModelDeploymentMonitoringJob.Builder setState(JobState value)

Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.

.google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	JobState The state to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setStateValue(int value)

public ModelDeploymentMonitoringJob.Builder setStateValue(int value)

Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.

.google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	int The enum numeric value on the wire for state to set.

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder	This builder for chaining.

setStatsAnomaliesBaseDirectory(GcsDestination value)

public ModelDeploymentMonitoringJob.Builder setStatsAnomaliesBaseDirectory(GcsDestination value)

Stats anomalies base folder path.

.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;

Parameter
Name	Description
value	GcsDestination

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setStatsAnomaliesBaseDirectory(GcsDestination.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setStatsAnomaliesBaseDirectory(GcsDestination.Builder builderForValue)

Stats anomalies base folder path.

.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;

Parameter
Name	Description
builderForValue	GcsDestination.Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final ModelDeploymentMonitoringJob.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)

setUpdateTime(Timestamp value)

public ModelDeploymentMonitoringJob.Builder setUpdateTime(Timestamp value)

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

.google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
value	Timestamp

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder

setUpdateTime(Timestamp.Builder builderForValue)

public ModelDeploymentMonitoringJob.Builder setUpdateTime(Timestamp.Builder builderForValue)

Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently.

.google.protobuf.Timestamp update_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];

Parameter
Name	Description
builderForValue	Builder

Returns
Type	Description
ModelDeploymentMonitoringJob.Builder