Retrieves a forecast for how much Amazon Web Services predicts that you will use over the forecast time period that you select, based on your past usage.
See https://www.paws-r-sdk.com/docs/costexplorer_get_usage_forecast/ for full documentation.
costexplorer_get_usage_forecast(
TimePeriod,
Metric,
Granularity,
Filter = NULL,
BillingViewArn = NULL,
PredictionIntervalLevel = NULL
)
[required] The start and end dates of the period that you want to retrieve usage
forecast for. The start date is included in the period, but the end date
isn't included in the period. For example, if start
is 2017-01-01
and end
is 2017-05-01
, then the cost and usage data is retrieved
from 2017-01-01
up to and including 2017-04-30
but not including
2017-05-01
. The start date must be equal to or later than the current
date to avoid a validation error.
[required] Which metric Cost Explorer uses to create your forecast.
Valid values for a
get_usage_forecast
call are the
following:
USAGE_QUANTITY
NORMALIZED_USAGE_AMOUNT
[required] How granular you want the forecast to be. You can get 3 months of
DAILY
forecasts or 12 months of MONTHLY
forecasts.
The get_usage_forecast
operation
supports only DAILY
and MONTHLY
granularities.
The filters that you want to use to filter your forecast. The
get_usage_forecast
API supports
filtering by the following dimensions:
AZ
INSTANCE_TYPE
LINKED_ACCOUNT
LINKED_ACCOUNT_NAME
OPERATION
PURCHASE_TYPE
REGION
SERVICE
USAGE_TYPE
USAGE_TYPE_GROUP
RECORD_TYPE
OPERATING_SYSTEM
TENANCY
SCOPE
PLATFORM
SUBSCRIPTION_ID
LEGAL_ENTITY_NAME
DEPLOYMENT_OPTION
DATABASE_ENGINE
INSTANCE_TYPE_FAMILY
BILLING_ENTITY
RESERVATION_ID
SAVINGS_PLAN_ARN
The Amazon Resource Name (ARN) that uniquely identifies a specific billing view. The ARN is used to specify which particular billing view you want to interact with or retrieve information from when making API calls related to Amazon Web Services Billing and Cost Management features. The BillingViewArn can be retrieved by calling the ListBillingViews API.
Amazon Web Services Cost Explorer always returns the mean forecast as a single point. You can request a prediction interval around the mean by specifying a confidence level. The higher the confidence level, the more confident Cost Explorer is about the actual value falling in the prediction interval. Higher confidence levels result in wider prediction intervals.