[ aws . lookoutequipment ]

list-inference-schedulers

Description

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

See also: AWS API Documentation

See ‘aws help’ for descriptions of global parameters.

Synopsis

  list-inference-schedulers
[--next-token <value>]
[--max-results <value>]
[--inference-scheduler-name-begins-with <value>]
[--model-name <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options

--next-token (string)

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

--max-results (integer)

Specifies the maximum number of inference schedulers to list.

--inference-scheduler-name-begins-with (string)

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

--model-name (string)

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

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

See ‘aws help’ for descriptions of global parameters.

Output

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.

(structure)

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 -> (long)

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.