Amazon Lookout for Equipment

2022/12/20 - Amazon Lookout for Equipment - 1 updated api methods

Changes  This release adds support for listing inference schedulers by status.

ListInferenceSchedulers (updated) Link ΒΆ
Changes (request)
{'Status': 'PENDING | RUNNING | STOPPING | STOPPED'}

Retrieves a list of all inference schedulers currently available for your account.

See also: AWS API Documentation

Request Syntax

client.list_inference_schedulers(
    NextToken='string',
    MaxResults=123,
    InferenceSchedulerNameBeginsWith='string',
    ModelName='string',
    Status='PENDING'|'RUNNING'|'STOPPING'|'STOPPED'
)
type NextToken:

string

param NextToken:

An opaque pagination token indicating where to continue the listing of inference schedulers.

type MaxResults:

integer

param MaxResults:

Specifies the maximum number of inference schedulers to list.

type InferenceSchedulerNameBeginsWith:

string

param InferenceSchedulerNameBeginsWith:

The beginning of the name of the inference schedulers to be listed.

type ModelName:

string

param ModelName:

The name of the ML model used by the inference scheduler to be listed.

type Status:

string

param Status:

Specifies the current status of the inference schedulers to list.

rtype:

dict

returns:

Response Syntax

{
    'NextToken': 'string',
    'InferenceSchedulerSummaries': [
        {
            'ModelName': 'string',
            'ModelArn': 'string',
            'InferenceSchedulerName': 'string',
            'InferenceSchedulerArn': 'string',
            'Status': 'PENDING'|'RUNNING'|'STOPPING'|'STOPPED',
            'DataDelayOffsetInMinutes': 123,
            'DataUploadFrequency': 'PT5M'|'PT10M'|'PT15M'|'PT30M'|'PT1H',
            'LatestInferenceResult': 'ANOMALOUS'|'NORMAL'
        },
    ]
}

Response Structure

  • (dict) --

    • NextToken (string) --

      An opaque pagination token indicating where to continue the listing of inference schedulers.

    • InferenceSchedulerSummaries (list) --

      Provides information about the specified inference scheduler, including data upload frequency, model name and ARN, and status.

      • (dict) --

        Contains information about the specific inference scheduler, including data delay offset, model name and ARN, status, and so on.

        • ModelName (string) --

          The name of the ML model used for the inference scheduler.

        • ModelArn (string) --

          The Amazon Resource Name (ARN) of the ML model used by the inference scheduler.

        • InferenceSchedulerName (string) --

          The name of the inference scheduler.

        • InferenceSchedulerArn (string) --

          The Amazon Resource Name (ARN) of the inference scheduler.

        • Status (string) --

          Indicates the status of the inference scheduler.

        • DataDelayOffsetInMinutes (integer) --

          A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if an offset delay time of five minutes was selected, inference will not begin on the data until the first data measurement after the five minute mark. For example, if five minutes is selected, the inference scheduler will wake up at the configured frequency with the additional five minute delay time to check the customer S3 bucket. The customer can upload data at the same frequency and they don't need to stop and restart the scheduler when uploading new data.

        • DataUploadFrequency (string) --

          How often data is uploaded to the source S3 bucket for the input data. This value is the length of time between data uploads. For instance, if you select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to the source bucket once every 5 minutes. This frequency also determines how often Amazon Lookout for Equipment starts a scheduled inference on your data. In this example, it starts once every 5 minutes.

        • LatestInferenceResult (string) --

          Indicates whether the latest execution for the inference scheduler was Anomalous (anomalous events found) or Normal (no anomalous events found).