Class ModelDeploymentMonitoringJob.Builder (3.34.0)

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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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`

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.

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.

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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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:

Training data logging predict request/response
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()

bool enable_monitoring_pipeline_logs = 22;

Returns
Type	Description
`boolean`	The enableMonitoringPipelineLogs.

getEncryptionSpec()

public EncryptionSpec getEncryptionSpec()

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

Returns
Type	Description
`EncryptionSpec`	The encryptionSpec.

getEncryptionSpecBuilder()

public EncryptionSpec.Builder getEncryptionSpecBuilder()

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

Returns
Type	Description
`EncryptionSpec.Builder`

getEncryptionSpecOrBuilder()

public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()

.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()

string predict_instance_schema_uri = 9;

Returns
Type	Description
`String`	The predictInstanceSchemaUri.

getPredictInstanceSchemaUriBytes()

public ByteString getPredictInstanceSchemaUriBytes()

string predict_instance_schema_uri = 9;

Returns
Type	Description
`ByteString`	The bytes for predictInstanceSchemaUri.

getSamplePredictInstance()

public Value getSamplePredictInstance()

.google.protobuf.Value sample_predict_instance = 19;

Returns
Type	Description
`Value`	The samplePredictInstance.

getSamplePredictInstanceBuilder()

public Value.Builder getSamplePredictInstanceBuilder()

.google.protobuf.Value sample_predict_instance = 19;

Returns
Type	Description
`Builder`

getSamplePredictInstanceOrBuilder()

public ValueOrBuilder getSamplePredictInstanceOrBuilder()

.google.protobuf.Value sample_predict_instance = 19;

Returns
Type	Description
`ValueOrBuilder`

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()

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

Returns
Type	Description
`JobState`	The state.

getStateValue()

public int getStateValue()

.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()

.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()

.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()

internalGetMapField(int number)

protected MapField internalGetMapField(int number)

Parameter
Name	Description
`number`	`int`

Returns
Type	Description
`MapField`

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetMapField(int fieldNumber)

internalGetMutableMapField(int number)

protected MapField internalGetMutableMapField(int number)

Parameter
Name	Description
`number`	`int`

Returns
Type	Description
`MapField`

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetMutableMapField(int fieldNumber)

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)

.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)

.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:

Training data logging predict request/response
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.

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.

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:

Training data logging predict request/response
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:

Training data logging predict request/response
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)

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)

.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)

.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)

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)

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)

.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)

.google.protobuf.Value sample_predict_instance = 19;

Parameter
Name	Description
`builderForValue`	`Builder`

Returns
Type	Description
`ModelDeploymentMonitoringJob.Builder`

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)

.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)

.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`