- 3.55.0 (latest)
- 3.54.0
- 3.53.0
- 3.52.0
- 3.50.0
- 3.49.0
- 3.48.0
- 3.47.0
- 3.46.0
- 3.45.0
- 3.44.0
- 3.43.0
- 3.42.0
- 3.41.0
- 3.40.0
- 3.38.0
- 3.37.0
- 3.36.0
- 3.35.0
- 3.34.0
- 3.33.0
- 3.32.0
- 3.31.0
- 3.30.0
- 3.29.0
- 3.28.0
- 3.25.0
- 3.24.0
- 3.23.0
- 3.22.0
- 3.21.0
- 3.20.0
- 3.19.0
- 3.18.0
- 3.17.0
- 3.16.0
- 3.15.0
- 3.14.0
- 3.13.0
- 3.12.0
- 3.11.0
- 3.10.0
- 3.9.0
- 3.8.0
- 3.7.0
- 3.6.0
- 3.5.0
- 3.4.2
- 3.3.0
- 3.2.0
- 3.0.0
- 2.9.8
- 2.8.9
- 2.7.4
- 2.5.3
- 2.4.0
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
Inheritance
Object > AbstractMessageLite<MessageType,BuilderType> > AbstractMessage > GeneratedMessageV3 > ModelDeploymentMonitoringJobImplements
ModelDeploymentMonitoringJobOrBuilderStatic Fields
ANALYSIS_INSTANCE_SCHEMA_URI_FIELD_NUMBER
public static final int ANALYSIS_INSTANCE_SCHEMA_URI_FIELD_NUMBER
Type | Description |
int |
BIGQUERY_TABLES_FIELD_NUMBER
public static final int BIGQUERY_TABLES_FIELD_NUMBER
Type | Description |
int |
CREATE_TIME_FIELD_NUMBER
public static final int CREATE_TIME_FIELD_NUMBER
Type | Description |
int |
DISPLAY_NAME_FIELD_NUMBER
public static final int DISPLAY_NAME_FIELD_NUMBER
Type | Description |
int |
ENABLE_MONITORING_PIPELINE_LOGS_FIELD_NUMBER
public static final int ENABLE_MONITORING_PIPELINE_LOGS_FIELD_NUMBER
Type | Description |
int |
ENCRYPTION_SPEC_FIELD_NUMBER
public static final int ENCRYPTION_SPEC_FIELD_NUMBER
Type | Description |
int |
ENDPOINT_FIELD_NUMBER
public static final int ENDPOINT_FIELD_NUMBER
Type | Description |
int |
ERROR_FIELD_NUMBER
public static final int ERROR_FIELD_NUMBER
Type | Description |
int |
LABELS_FIELD_NUMBER
public static final int LABELS_FIELD_NUMBER
Type | Description |
int |
LATEST_MONITORING_PIPELINE_METADATA_FIELD_NUMBER
public static final int LATEST_MONITORING_PIPELINE_METADATA_FIELD_NUMBER
Type | Description |
int |
LOGGING_SAMPLING_STRATEGY_FIELD_NUMBER
public static final int LOGGING_SAMPLING_STRATEGY_FIELD_NUMBER
Type | Description |
int |
LOG_TTL_FIELD_NUMBER
public static final int LOG_TTL_FIELD_NUMBER
Type | Description |
int |
MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_CONFIGS_FIELD_NUMBER
public static final int MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_CONFIGS_FIELD_NUMBER
Type | Description |
int |
MODEL_DEPLOYMENT_MONITORING_SCHEDULE_CONFIG_FIELD_NUMBER
public static final int MODEL_DEPLOYMENT_MONITORING_SCHEDULE_CONFIG_FIELD_NUMBER
Type | Description |
int |
MODEL_MONITORING_ALERT_CONFIG_FIELD_NUMBER
public static final int MODEL_MONITORING_ALERT_CONFIG_FIELD_NUMBER
Type | Description |
int |
NAME_FIELD_NUMBER
public static final int NAME_FIELD_NUMBER
Type | Description |
int |
NEXT_SCHEDULE_TIME_FIELD_NUMBER
public static final int NEXT_SCHEDULE_TIME_FIELD_NUMBER
Type | Description |
int |
PREDICT_INSTANCE_SCHEMA_URI_FIELD_NUMBER
public static final int PREDICT_INSTANCE_SCHEMA_URI_FIELD_NUMBER
Type | Description |
int |
SAMPLE_PREDICT_INSTANCE_FIELD_NUMBER
public static final int SAMPLE_PREDICT_INSTANCE_FIELD_NUMBER
Type | Description |
int |
SCHEDULE_STATE_FIELD_NUMBER
public static final int SCHEDULE_STATE_FIELD_NUMBER
Type | Description |
int |
STATE_FIELD_NUMBER
public static final int STATE_FIELD_NUMBER
Type | Description |
int |
STATS_ANOMALIES_BASE_DIRECTORY_FIELD_NUMBER
public static final int STATS_ANOMALIES_BASE_DIRECTORY_FIELD_NUMBER
Type | Description |
int |
UPDATE_TIME_FIELD_NUMBER
public static final int UPDATE_TIME_FIELD_NUMBER
Type | Description |
int |
Static Methods
getDefaultInstance()
public static ModelDeploymentMonitoringJob getDefaultInstance()
Type | Description |
ModelDeploymentMonitoringJob |
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
newBuilder()
public static ModelDeploymentMonitoringJob.Builder newBuilder()
Type | Description |
ModelDeploymentMonitoringJob.Builder |
newBuilder(ModelDeploymentMonitoringJob prototype)
public static ModelDeploymentMonitoringJob.Builder newBuilder(ModelDeploymentMonitoringJob prototype)
Name | Description |
prototype | ModelDeploymentMonitoringJob |
Type | Description |
ModelDeploymentMonitoringJob.Builder |
parseDelimitedFrom(InputStream input)
public static ModelDeploymentMonitoringJob parseDelimitedFrom(InputStream input)
Name | Description |
input | InputStream |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
IOException |
parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ModelDeploymentMonitoringJob parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | InputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
IOException |
parseFrom(byte[] data)
public static ModelDeploymentMonitoringJob parseFrom(byte[] data)
Name | Description |
data | byte[] |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
InvalidProtocolBufferException |
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ModelDeploymentMonitoringJob parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Name | Description |
data | byte[] |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteString data)
public static ModelDeploymentMonitoringJob parseFrom(ByteString data)
Name | Description |
data | ByteString |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ModelDeploymentMonitoringJob parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Name | Description |
data | ByteString |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
InvalidProtocolBufferException |
parseFrom(CodedInputStream input)
public static ModelDeploymentMonitoringJob parseFrom(CodedInputStream input)
Name | Description |
input | CodedInputStream |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
IOException |
parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ModelDeploymentMonitoringJob parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
IOException |
parseFrom(InputStream input)
public static ModelDeploymentMonitoringJob parseFrom(InputStream input)
Name | Description |
input | InputStream |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
IOException |
parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ModelDeploymentMonitoringJob parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | InputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
IOException |
parseFrom(ByteBuffer data)
public static ModelDeploymentMonitoringJob parseFrom(ByteBuffer data)
Name | Description |
data | ByteBuffer |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
InvalidProtocolBufferException |
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static ModelDeploymentMonitoringJob parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Name | Description |
data | ByteBuffer |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
ModelDeploymentMonitoringJob |
Type | Description |
InvalidProtocolBufferException |
parser()
public static Parser<ModelDeploymentMonitoringJob> parser()
Type | Description |
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;
Name | Description |
key | String |
Type | Description |
boolean |
equals(Object obj)
public boolean equals(Object obj)
Name | Description |
obj | Object |
Type | Description |
boolean |
getAnalysisInstanceSchemaUri()
public String getAnalysisInstanceSchemaUri()
YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.
string analysis_instance_schema_uri = 16;
Type | Description |
String | The analysisInstanceSchemaUri. |
getAnalysisInstanceSchemaUriBytes()
public ByteString getAnalysisInstanceSchemaUriBytes()
YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string.
string analysis_instance_schema_uri = 16;
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];
Name | Description |
index | int |
Type | Description |
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:
- 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];
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];
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];
Name | Description |
index | int |
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];
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];
Type | Description |
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];
Type | Description |
TimestampOrBuilder |
getDefaultInstanceForType()
public ModelDeploymentMonitoringJob getDefaultInstanceForType()
Type | Description |
ModelDeploymentMonitoringJob |
getDisplayName()
public String getDisplayName()
Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can be consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
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 be consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];
Type | Description |
ByteString | The bytes for displayName. |
getEnableMonitoringPipelineLogs()
public boolean getEnableMonitoringPipelineLogs()
If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to Cloud Logging pricing.
bool enable_monitoring_pipeline_logs = 22;
Type | Description |
boolean | The enableMonitoringPipelineLogs. |
getEncryptionSpec()
public EncryptionSpec getEncryptionSpec()
Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
Type | Description |
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;
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) = { ... }
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) = { ... }
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];
Type | Description |
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];
Type | Description |
com.google.rpc.StatusOrBuilder |
getLabels()
public Map<String,String> getLabels()
Use #getLabelsMap() instead.
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;
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;
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;
Name | Description |
key | String |
defaultValue | String |
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;
Name | Description |
key | String |
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];
Type | Description |
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];
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;
Type | Description |
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;
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];
Type | Description |
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];
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];
Name | Description |
index | int |
Type | Description |
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];
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];
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];
Name | Description |
index | int |
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];
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];
Type | Description |
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];
Type | Description |
ModelDeploymentMonitoringScheduleConfigOrBuilder |
getModelMonitoringAlertConfig()
public ModelMonitoringAlertConfig getModelMonitoringAlertConfig()
Alert config for model monitoring.
.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
Type | Description |
ModelMonitoringAlertConfig | The modelMonitoringAlertConfig. |
getModelMonitoringAlertConfigOrBuilder()
public ModelMonitoringAlertConfigOrBuilder getModelMonitoringAlertConfigOrBuilder()
Alert config for model monitoring.
.google.cloud.aiplatform.v1.ModelMonitoringAlertConfig model_monitoring_alert_config = 15;
Type | Description |
ModelMonitoringAlertConfigOrBuilder |
getName()
public String getName()
Output only. Resource name of a ModelDeploymentMonitoringJob.
string name = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
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];
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];
Type | Description |
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];
Type | Description |
TimestampOrBuilder |
getParserForType()
public Parser<ModelDeploymentMonitoringJob> getParserForType()
Type | Description |
Parser<ModelDeploymentMonitoringJob> |
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;
Type | Description |
String | The predictInstanceSchemaUri. |
getPredictInstanceSchemaUriBytes()
public ByteString getPredictInstanceSchemaUriBytes()
YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests.
string predict_instance_schema_uri = 9;
Type | Description |
ByteString | The bytes for predictInstanceSchemaUri. |
getSamplePredictInstance()
public Value getSamplePredictInstance()
Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.
.google.protobuf.Value sample_predict_instance = 19;
Type | Description |
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;
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];
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];
Type | Description |
int | The enum numeric value on the wire for scheduleState. |
getSerializedSize()
public int getSerializedSize()
Type | Description |
int |
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];
Type | Description |
JobState | The state. |
getStateValue()
public int getStateValue()
Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'.
.google.cloud.aiplatform.v1.JobState state = 4 [(.google.api.field_behavior) = OUTPUT_ONLY];
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;
Type | Description |
GcsDestination | The statsAnomaliesBaseDirectory. |
getStatsAnomaliesBaseDirectoryOrBuilder()
public GcsDestinationOrBuilder getStatsAnomaliesBaseDirectoryOrBuilder()
Stats anomalies base folder path.
.google.cloud.aiplatform.v1.GcsDestination stats_anomalies_base_directory = 20;
Type | Description |
GcsDestinationOrBuilder |
getUnknownFields()
public final UnknownFieldSet getUnknownFields()
Type | Description |
UnknownFieldSet |
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];
Type | Description |
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];
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];
Type | Description |
boolean | Whether the createTime field is set. |
hasEncryptionSpec()
public boolean hasEncryptionSpec()
Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key.
.google.cloud.aiplatform.v1.EncryptionSpec encryption_spec = 21;
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];
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];
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;
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];
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];
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;
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];
Type | Description |
boolean | Whether the nextScheduleTime field is set. |
hasSamplePredictInstance()
public boolean hasSamplePredictInstance()
Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests.
.google.protobuf.Value sample_predict_instance = 19;
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;
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];
Type | Description |
boolean | Whether the updateTime field is set. |
hashCode()
public int hashCode()
Type | Description |
int |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
internalGetMapField(int number)
protected MapField internalGetMapField(int number)
Name | Description |
number | int |
Type | Description |
MapField |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
newBuilderForType()
public ModelDeploymentMonitoringJob.Builder newBuilderForType()
Type | Description |
ModelDeploymentMonitoringJob.Builder |
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected ModelDeploymentMonitoringJob.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Name | Description |
parent | BuilderParent |
Type | Description |
ModelDeploymentMonitoringJob.Builder |
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Name | Description |
unused | UnusedPrivateParameter |
Type | Description |
Object |
toBuilder()
public ModelDeploymentMonitoringJob.Builder toBuilder()
Type | Description |
ModelDeploymentMonitoringJob.Builder |
writeTo(CodedOutputStream output)
public void writeTo(CodedOutputStream output)
Name | Description |
output | CodedOutputStream |
Type | Description |
IOException |