monitoring_schedules

Creates, updates, deletes, gets or lists a monitoring_schedules resource.

Overview

Name	monitoring_schedules
Type	Resource
Id	aws.sagemaker.monitoring_schedules

Fields

The following fields are returned by SELECT queries:

describe_monitoring_schedule

Name	Datatype	Description
creation_time	string (date-time)	The time at which the monitoring job was created.
endpoint_name	string	The name of the endpoint for the monitoring job. (pattern: <code>[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}</code>)
failure_reason	string	A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
last_modified_time	string (date-time)	The time at which the monitoring job was last modified.
last_monitoring_execution_summary	object	Describes metadata on the last execution to run, if there was one.
monitoring_schedule_arn	string	The Amazon Resource Name (ARN) of the monitoring schedule. (pattern: <code>.*</code>)
monitoring_schedule_config	object	The configuration object that specifies the monitoring schedule and defines the monitoring job.
monitoring_schedule_name	string	Name of the monitoring schedule. (pattern: <code>[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}</code>)
monitoring_schedule_status	string	The status of an monitoring job. (Pending, Failed, Scheduled, Stopped)
monitoring_type	string	The type of the monitoring job that this schedule runs. This is one of the following values. DATA_QUALITY - The schedule is for a data quality monitoring job. MODEL_QUALITY - The schedule is for a model quality monitoring job. MODEL_BIAS - The schedule is for a bias monitoring job. MODEL_EXPLAINABILITY - The schedule is for an explainability monitoring job. (DataQuality, ModelQuality, ModelBias, ModelExplainability)

list_monitoring_schedules

Name	Datatype	Description
creation_time	string (date-time)	The creation time of the monitoring schedule.
endpoint_name	string	The name of the endpoint using the monitoring schedule. (pattern: <code>[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}</code>)
last_modified_time	string (date-time)	The last time the monitoring schedule was modified.
monitoring_job_definition_name	string	The name of the monitoring job definition that the schedule is for. (pattern: <code>[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}</code>)
monitoring_schedule_arn	string	The Amazon Resource Name (ARN) of the monitoring schedule. (pattern: <code>.*</code>)
monitoring_schedule_name	string	The name of the monitoring schedule. (pattern: <code>[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}</code>)
monitoring_schedule_status	string	The status of the monitoring schedule. (Pending, Failed, Scheduled, Stopped)
monitoring_type	string	The type of the monitoring job definition that the schedule is for. (DataQuality, ModelQuality, ModelBias, ModelExplainability)

Methods

The following methods are available for this resource:

Name	Accessible by	Required Params	Optional Params	Description
describe_monitoring_schedule	select	region		Describes the schedule for a monitoring job.
list_monitoring_schedules	select	region		Returns list of all monitoring schedules.
create_monitoring_schedule	insert	region, MonitoringScheduleName, MonitoringScheduleConfig		Creates a schedule that regularly starts Amazon SageMaker AI Processing Jobs to monitor the data captured for an Amazon SageMaker AI Endpoint.
update_monitoring_schedule	update	region, MonitoringScheduleName, MonitoringScheduleConfig		Updates a previously created schedule.
delete_monitoring_schedule	delete	region		Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.
start_monitoring_schedule	exec	region, MonitoringScheduleName		Starts a previously stopped monitoring schedule. By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled.
stop_monitoring_schedule	exec	region, MonitoringScheduleName		Stops a previously started monitoring schedule.

Parameters

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

Name	Datatype	Description
region	string	AWS region (default: us-east-1)

SELECT examples

describe_monitoring_schedule

Describes the schedule for a monitoring job.

SELECT
creation_time,
endpoint_name,
failure_reason,
last_modified_time,
last_monitoring_execution_summary,
monitoring_schedule_arn,
monitoring_schedule_config,
monitoring_schedule_name,
monitoring_schedule_status,
monitoring_type
FROM aws.sagemaker.monitoring_schedules
WHERE region = '{{ region }}' -- required
;

list_monitoring_schedules

Returns list of all monitoring schedules.

SELECT
creation_time,
endpoint_name,
last_modified_time,
monitoring_job_definition_name,
monitoring_schedule_arn,
monitoring_schedule_name,
monitoring_schedule_status,
monitoring_type
FROM aws.sagemaker.monitoring_schedules
WHERE region = '{{ region }}' -- required
;

INSERT examples

create_monitoring_schedule

Creates a schedule that regularly starts Amazon SageMaker AI Processing Jobs to monitor the data captured for an Amazon SageMaker AI Endpoint.

INSERT INTO aws.sagemaker.monitoring_schedules (
MonitoringScheduleName,
MonitoringScheduleConfig,
Tags,
region
)
SELECT 
'{{ MonitoringScheduleName }}' /* required */,
'{{ MonitoringScheduleConfig }}' /* required */,
'{{ Tags }}',
'{{ region }}'
RETURNING
monitoring_schedule_arn
;

Manifest

# Description fields are for documentation purposes
- name: monitoring_schedules
props:
  - name: region
    value: "{{ region }}"
    description: Required parameter for the monitoring_schedules resource.
  - name: MonitoringScheduleName
    value: "{{ MonitoringScheduleName }}"
    description: |
      The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
  - name: MonitoringScheduleConfig
    description: |
      The configuration object that specifies the monitoring schedule and defines the monitoring job.
    value:
      ScheduleConfig:
        ScheduleExpression: "{{ ScheduleExpression }}"
        DataAnalysisStartTime: "{{ DataAnalysisStartTime }}"
        DataAnalysisEndTime: "{{ DataAnalysisEndTime }}"
      MonitoringJobDefinition:
        BaselineConfig:
          BaseliningJobName: "{{ BaseliningJobName }}"
          ConstraintsResource:
            S3Uri: "{{ S3Uri }}"
          StatisticsResource:
            S3Uri: "{{ S3Uri }}"
        MonitoringInputs:
          - EndpointInput:
              EndpointName: "{{ EndpointName }}"
              LocalPath: "{{ LocalPath }}"
              S3InputMode: "{{ S3InputMode }}"
              S3DataDistributionType: "{{ S3DataDistributionType }}"
              FeaturesAttribute: "{{ FeaturesAttribute }}"
              InferenceAttribute: "{{ InferenceAttribute }}"
              ProbabilityAttribute: "{{ ProbabilityAttribute }}"
              ProbabilityThresholdAttribute: {{ ProbabilityThresholdAttribute }}
              StartTimeOffset: "{{ StartTimeOffset }}"
              EndTimeOffset: "{{ EndTimeOffset }}"
              ExcludeFeaturesAttribute: "{{ ExcludeFeaturesAttribute }}"
            BatchTransformInput:
              DataCapturedDestinationS3Uri: "{{ DataCapturedDestinationS3Uri }}"
              DatasetFormat:
                Csv: "{{ Csv }}"
                Json: "{{ Json }}"
                Parquet: "{{ Parquet }}"
              LocalPath: "{{ LocalPath }}"
              S3InputMode: "{{ S3InputMode }}"
              S3DataDistributionType: "{{ S3DataDistributionType }}"
              FeaturesAttribute: "{{ FeaturesAttribute }}"
              InferenceAttribute: "{{ InferenceAttribute }}"
              ProbabilityAttribute: "{{ ProbabilityAttribute }}"
              ProbabilityThresholdAttribute: {{ ProbabilityThresholdAttribute }}
              StartTimeOffset: "{{ StartTimeOffset }}"
              EndTimeOffset: "{{ EndTimeOffset }}"
              ExcludeFeaturesAttribute: "{{ ExcludeFeaturesAttribute }}"
        MonitoringOutputConfig:
          MonitoringOutputs:
            - S3Output:
                S3Uri: "{{ S3Uri }}"
                LocalPath: "{{ LocalPath }}"
                S3UploadMode: "{{ S3UploadMode }}"
          KmsKeyId: "{{ KmsKeyId }}"
        MonitoringResources:
          ClusterConfig:
            InstanceCount: {{ InstanceCount }}
            InstanceType: "{{ InstanceType }}"
            VolumeSizeInGB: {{ VolumeSizeInGB }}
            VolumeKmsKeyId: "{{ VolumeKmsKeyId }}"
        MonitoringAppSpecification:
          ImageUri: "{{ ImageUri }}"
          ContainerEntrypoint:
            - "{{ ContainerEntrypoint }}"
          ContainerArguments:
            - "{{ ContainerArguments }}"
          RecordPreprocessorSourceUri: "{{ RecordPreprocessorSourceUri }}"
          PostAnalyticsProcessorSourceUri: "{{ PostAnalyticsProcessorSourceUri }}"
        StoppingCondition:
          MaxRuntimeInSeconds: {{ MaxRuntimeInSeconds }}
        Environment: "{{ Environment }}"
        NetworkConfig:
          EnableInterContainerTrafficEncryption: {{ EnableInterContainerTrafficEncryption }}
          EnableNetworkIsolation: {{ EnableNetworkIsolation }}
          VpcConfig:
            SecurityGroupIds:
              - "{{ SecurityGroupIds }}"
            Subnets:
              - "{{ Subnets }}"
        RoleArn: "{{ RoleArn }}"
      MonitoringJobDefinitionName: "{{ MonitoringJobDefinitionName }}"
      MonitoringType: "{{ MonitoringType }}"
  - name: Tags
    description: |
      (Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
    value:
      - Key: "{{ Key }}"
        Value: "{{ Value }}"

UPDATE examples

update_monitoring_schedule

Updates a previously created schedule.

UPDATE aws.sagemaker.monitoring_schedules
SET 
MonitoringScheduleName = '{{ MonitoringScheduleName }}',
MonitoringScheduleConfig = '{{ MonitoringScheduleConfig }}'
WHERE 
region = '{{ region }}' --required
AND MonitoringScheduleName = '{{ MonitoringScheduleName }}' --required
AND MonitoringScheduleConfig = '{{ MonitoringScheduleConfig }}' --required
RETURNING
monitoring_schedule_arn;

DELETE examples

delete_monitoring_schedule

Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.

DELETE FROM aws.sagemaker.monitoring_schedules
WHERE region = '{{ region }}' --required
;

Lifecycle Methods

start_monitoring_schedule

Starts a previously stopped monitoring schedule. By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled.

EXEC aws.sagemaker.monitoring_schedules.start_monitoring_schedule 
@region='{{ region }}' --required 
@@json=
'{
"MonitoringScheduleName": "{{ MonitoringScheduleName }}"
}'
;

stop_monitoring_schedule

Stops a previously started monitoring schedule.

EXEC aws.sagemaker.monitoring_schedules.stop_monitoring_schedule 
@region='{{ region }}' --required 
@@json=
'{
"MonitoringScheduleName": "{{ MonitoringScheduleName }}"
}'
;