Class ModelDeploymentMonitoringJob (3.24.0)

public final class ModelDeploymentMonitoringJob extends GeneratedMessageV3 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

Static Fields

ANALYSIS_INSTANCE_SCHEMA_URI_FIELD_NUMBER

public static final int ANALYSIS_INSTANCE_SCHEMA_URI_FIELD_NUMBER
Field Value
TypeDescription
int

BIGQUERY_TABLES_FIELD_NUMBER

public static final int BIGQUERY_TABLES_FIELD_NUMBER
Field Value
TypeDescription
int

CREATE_TIME_FIELD_NUMBER

public static final int CREATE_TIME_FIELD_NUMBER
Field Value
TypeDescription
int

DISPLAY_NAME_FIELD_NUMBER

public static final int DISPLAY_NAME_FIELD_NUMBER
Field Value
TypeDescription
int

ENABLE_MONITORING_PIPELINE_LOGS_FIELD_NUMBER

public static final int ENABLE_MONITORING_PIPELINE_LOGS_FIELD_NUMBER
Field Value
TypeDescription
int

ENCRYPTION_SPEC_FIELD_NUMBER

public static final int ENCRYPTION_SPEC_FIELD_NUMBER
Field Value
TypeDescription
int

ENDPOINT_FIELD_NUMBER

public static final int ENDPOINT_FIELD_NUMBER
Field Value
TypeDescription
int

ERROR_FIELD_NUMBER

public static final int ERROR_FIELD_NUMBER
Field Value
TypeDescription
int

LABELS_FIELD_NUMBER

public static final int LABELS_FIELD_NUMBER
Field Value
TypeDescription
int

LATEST_MONITORING_PIPELINE_METADATA_FIELD_NUMBER

public static final int LATEST_MONITORING_PIPELINE_METADATA_FIELD_NUMBER
Field Value
TypeDescription
int

LOGGING_SAMPLING_STRATEGY_FIELD_NUMBER

public static final int LOGGING_SAMPLING_STRATEGY_FIELD_NUMBER
Field Value
TypeDescription
int

LOG_TTL_FIELD_NUMBER

public static final int LOG_TTL_FIELD_NUMBER
Field Value
TypeDescription
int

MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_CONFIGS_FIELD_NUMBER

public static final int MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_CONFIGS_FIELD_NUMBER
Field Value
TypeDescription
int

MODEL_DEPLOYMENT_MONITORING_SCHEDULE_CONFIG_FIELD_NUMBER

public static final int MODEL_DEPLOYMENT_MONITORING_SCHEDULE_CONFIG_FIELD_NUMBER
Field Value
TypeDescription
int

MODEL_MONITORING_ALERT_CONFIG_FIELD_NUMBER

public static final int MODEL_MONITORING_ALERT_CONFIG_FIELD_NUMBER
Field Value
TypeDescription
int

NAME_FIELD_NUMBER

public static final int NAME_FIELD_NUMBER
Field Value
TypeDescription
int

NEXT_SCHEDULE_TIME_FIELD_NUMBER

public static final int NEXT_SCHEDULE_TIME_FIELD_NUMBER
Field Value
TypeDescription
int

PREDICT_INSTANCE_SCHEMA_URI_FIELD_NUMBER

public static final int PREDICT_INSTANCE_SCHEMA_URI_FIELD_NUMBER
Field Value
TypeDescription
int

SAMPLE_PREDICT_INSTANCE_FIELD_NUMBER

public static final int SAMPLE_PREDICT_INSTANCE_FIELD_NUMBER
Field Value
TypeDescription
int

SCHEDULE_STATE_FIELD_NUMBER

public static final int SCHEDULE_STATE_FIELD_NUMBER
Field Value
TypeDescription
int

STATE_FIELD_NUMBER

public static final int STATE_FIELD_NUMBER
Field Value
TypeDescription
int

STATS_ANOMALIES_BASE_DIRECTORY_FIELD_NUMBER

public static final int STATS_ANOMALIES_BASE_DIRECTORY_FIELD_NUMBER
Field Value
TypeDescription
int

UPDATE_TIME_FIELD_NUMBER

public static final int UPDATE_TIME_FIELD_NUMBER
Field Value
TypeDescription
int

Static Methods

getDefaultInstance()

public static ModelDeploymentMonitoringJob getDefaultInstance()
Returns
TypeDescription
ModelDeploymentMonitoringJob

getDescriptor()

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

newBuilder()

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

newBuilder(ModelDeploymentMonitoringJob prototype)

public static ModelDeploymentMonitoringJob.Builder newBuilder(ModelDeploymentMonitoringJob prototype)
Parameter
NameDescription
prototypeModelDeploymentMonitoringJob
Returns
TypeDescription
ModelDeploymentMonitoringJob.Builder

parseDelimitedFrom(InputStream input)

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

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(byte[] data)

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

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

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

parseFrom(ByteString data)

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

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

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

parseFrom(CodedInputStream input)

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

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(InputStream input)

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

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

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

parseFrom(ByteBuffer data)

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

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

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

parser()

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

Methods

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
NameDescription
keyString
Returns
TypeDescription
boolean

equals(Object obj)

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

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
TypeDescription
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
TypeDescription
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
NameDescription
indexint
Returns
TypeDescription
ModelDeploymentMonitoringBigQueryTable

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
TypeDescription
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
TypeDescription
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
NameDescription
indexint
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
Timestamp

The createTime.

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
TypeDescription
TimestampOrBuilder

getDefaultInstanceForType()

public ModelDeploymentMonitoringJob getDefaultInstanceForType()
Returns
TypeDescription
ModelDeploymentMonitoringJob

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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
EncryptionSpec

The encryptionSpec.

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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
com.google.rpc.Status

The error.

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
TypeDescription
com.google.rpc.StatusOrBuilder

getLabels()

public Map<String,String> getLabels()

Use #getLabelsMap() instead.

Returns
TypeDescription
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
TypeDescription
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
TypeDescription
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
NameDescription
keyString
defaultValueString
Returns
TypeDescription
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
NameDescription
keyString
Returns
TypeDescription
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
TypeDescription
ModelDeploymentMonitoringJob.LatestMonitoringPipelineMetadata

The latestMonitoringPipelineMetadata.

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
TypeDescription
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
TypeDescription
Duration

The logTtl.

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
TypeDescription
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
TypeDescription
SamplingStrategy

The loggingSamplingStrategy.

getLoggingSamplingStrategyOrBuilder()

public SamplingStrategyOrBuilder getLoggingSamplingStrategyOrBuilder()

Required. Sample Strategy for logging.

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

Returns
TypeDescription
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
NameDescription
indexint
Returns
TypeDescription
ModelDeploymentMonitoringObjectiveConfig

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
TypeDescription
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
TypeDescription
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
NameDescription
indexint
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
ModelDeploymentMonitoringScheduleConfig

The modelDeploymentMonitoringScheduleConfig.

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
TypeDescription
ModelDeploymentMonitoringScheduleConfigOrBuilder

getModelMonitoringAlertConfig()

public ModelMonitoringAlertConfig getModelMonitoringAlertConfig()

Alert config for model monitoring.

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

Returns
TypeDescription
ModelMonitoringAlertConfig

The modelMonitoringAlertConfig.

getModelMonitoringAlertConfigOrBuilder()

public ModelMonitoringAlertConfigOrBuilder getModelMonitoringAlertConfigOrBuilder()

Alert config for model monitoring.

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

Returns
TypeDescription
ModelMonitoringAlertConfigOrBuilder

getName()

public String getName()

Output only. Resource name of a ModelDeploymentMonitoringJob.

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

Returns
TypeDescription
String

The name.

getNameBytes()

public ByteString getNameBytes()

Output only. Resource name of a ModelDeploymentMonitoringJob.

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

Returns
TypeDescription
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
TypeDescription
Timestamp

The nextScheduleTime.

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
TypeDescription
TimestampOrBuilder

getParserForType()

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

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
TypeDescription
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
TypeDescription
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
TypeDescription
Value

The samplePredictInstance.

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
TypeDescription
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
TypeDescription
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
TypeDescription
int

The enum numeric value on the wire for scheduleState.

getSerializedSize()

public int getSerializedSize()
Returns
TypeDescription
int
Overrides

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
TypeDescription
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
TypeDescription
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
TypeDescription
GcsDestination

The statsAnomaliesBaseDirectory.

getStatsAnomaliesBaseDirectoryOrBuilder()

public GcsDestinationOrBuilder getStatsAnomaliesBaseDirectoryOrBuilder()

Stats anomalies base folder path.

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

Returns
TypeDescription
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
TypeDescription
Timestamp

The updateTime.

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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
boolean

Whether the updateTime field is set.

hashCode()

public int hashCode()
Returns
TypeDescription
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

internalGetMapField(int number)

protected MapField internalGetMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

newBuilderForType()

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

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

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

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

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

toBuilder()

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

writeTo(CodedOutputStream output)

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