/AWS1/CL_SGMMONJOBDEFINITION¶
Defines the monitoring job.
CONSTRUCTOR¶
IMPORTING¶
Required arguments:¶
it_monitoringinputs TYPE /AWS1/CL_SGMMONITORINGINPUT=>TT_MONITORINGINPUTS TT_MONITORINGINPUTS¶
The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker AI Endpoint.
io_monitoringoutputconfig TYPE REF TO /AWS1/CL_SGMMONOUTPUTCONFIG /AWS1/CL_SGMMONOUTPUTCONFIG¶
The array of outputs from the monitoring job to be uploaded to Amazon S3.
io_monitoringresources TYPE REF TO /AWS1/CL_SGMMONRESOURCES /AWS1/CL_SGMMONRESOURCES¶
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
io_monitoringappspec TYPE REF TO /AWS1/CL_SGMMONITORINGAPPSPEC /AWS1/CL_SGMMONITORINGAPPSPEC¶
Configures the monitoring job to run a specified Docker container image.
iv_rolearn TYPE /AWS1/SGMROLEARN /AWS1/SGMROLEARN¶
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
Optional arguments:¶
io_baselineconfig TYPE REF TO /AWS1/CL_SGMMONBASELINECONFIG /AWS1/CL_SGMMONBASELINECONFIG¶
Baseline configuration used to validate that the data conforms to the specified constraints and statistics
io_stoppingcondition TYPE REF TO /AWS1/CL_SGMMONSTOPPINGCOND /AWS1/CL_SGMMONSTOPPINGCOND¶
Specifies a time limit for how long the monitoring job is allowed to run.
it_environment TYPE /AWS1/CL_SGMMONENVIRONMENTMA00=>TT_MONITORINGENVIRONMENTMAP TT_MONITORINGENVIRONMENTMAP¶
Sets the environment variables in the Docker container.
io_networkconfig TYPE REF TO /AWS1/CL_SGMNETWORKCONFIG /AWS1/CL_SGMNETWORKCONFIG¶
Specifies networking options for an monitoring job.
Queryable Attributes¶
BaselineConfig¶
Baseline configuration used to validate that the data conforms to the specified constraints and statistics
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_BASELINECONFIG() |
Getter for BASELINECONFIG |
MonitoringInputs¶
The array of inputs for the monitoring job. Currently we support monitoring an Amazon SageMaker AI Endpoint.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_MONITORINGINPUTS() |
Getter for MONITORINGINPUTS, with configurable default |
ASK_MONITORINGINPUTS() |
Getter for MONITORINGINPUTS w/ exceptions if field has no va |
HAS_MONITORINGINPUTS() |
Determine if MONITORINGINPUTS has a value |
MonitoringOutputConfig¶
The array of outputs from the monitoring job to be uploaded to Amazon S3.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_MONITORINGOUTPUTCONFIG() |
Getter for MONITORINGOUTPUTCONFIG |
MonitoringResources¶
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_MONITORINGRESOURCES() |
Getter for MONITORINGRESOURCES |
MonitoringAppSpecification¶
Configures the monitoring job to run a specified Docker container image.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_MONITORINGAPPSPEC() |
Getter for MONITORINGAPPSPECIFICATION |
StoppingCondition¶
Specifies a time limit for how long the monitoring job is allowed to run.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_STOPPINGCONDITION() |
Getter for STOPPINGCONDITION |
Environment¶
Sets the environment variables in the Docker container.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_ENVIRONMENT() |
Getter for ENVIRONMENT, with configurable default |
ASK_ENVIRONMENT() |
Getter for ENVIRONMENT w/ exceptions if field has no value |
HAS_ENVIRONMENT() |
Determine if ENVIRONMENT has a value |
NetworkConfig¶
Specifies networking options for an monitoring job.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_NETWORKCONFIG() |
Getter for NETWORKCONFIG |
RoleArn¶
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_ROLEARN() |
Getter for ROLEARN, with configurable default |
ASK_ROLEARN() |
Getter for ROLEARN w/ exceptions if field has no value |
HAS_ROLEARN() |
Determine if ROLEARN has a value |