CostExplorer / Client / get_usage_forecast
get_usage_forecast#
- CostExplorer.Client.get_usage_forecast(**kwargs)#
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 also: AWS API Documentation
Request Syntax
response = client.get_usage_forecast( TimePeriod={ 'Start': 'string', 'End': 'string' }, Metric='BLENDED_COST'|'UNBLENDED_COST'|'AMORTIZED_COST'|'NET_UNBLENDED_COST'|'NET_AMORTIZED_COST'|'USAGE_QUANTITY'|'NORMALIZED_USAGE_AMOUNT', Granularity='DAILY'|'MONTHLY'|'HOURLY', Filter={ 'Or': [ {'... recursive ...'}, ], 'And': [ {'... recursive ...'}, ], 'Not': {'... recursive ...'}, 'Dimensions': { 'Key': 'AZ'|'INSTANCE_TYPE'|'LINKED_ACCOUNT'|'LINKED_ACCOUNT_NAME'|'OPERATION'|'PURCHASE_TYPE'|'REGION'|'SERVICE'|'SERVICE_CODE'|'USAGE_TYPE'|'USAGE_TYPE_GROUP'|'RECORD_TYPE'|'OPERATING_SYSTEM'|'TENANCY'|'SCOPE'|'PLATFORM'|'SUBSCRIPTION_ID'|'LEGAL_ENTITY_NAME'|'DEPLOYMENT_OPTION'|'DATABASE_ENGINE'|'CACHE_ENGINE'|'INSTANCE_TYPE_FAMILY'|'BILLING_ENTITY'|'RESERVATION_ID'|'RESOURCE_ID'|'RIGHTSIZING_TYPE'|'SAVINGS_PLANS_TYPE'|'SAVINGS_PLAN_ARN'|'PAYMENT_OPTION'|'AGREEMENT_END_DATE_TIME_AFTER'|'AGREEMENT_END_DATE_TIME_BEFORE'|'INVOICING_ENTITY'|'ANOMALY_TOTAL_IMPACT_ABSOLUTE'|'ANOMALY_TOTAL_IMPACT_PERCENTAGE', 'Values': [ 'string', ], 'MatchOptions': [ 'EQUALS'|'ABSENT'|'STARTS_WITH'|'ENDS_WITH'|'CONTAINS'|'CASE_SENSITIVE'|'CASE_INSENSITIVE'|'GREATER_THAN_OR_EQUAL', ] }, 'Tags': { 'Key': 'string', 'Values': [ 'string', ], 'MatchOptions': [ 'EQUALS'|'ABSENT'|'STARTS_WITH'|'ENDS_WITH'|'CONTAINS'|'CASE_SENSITIVE'|'CASE_INSENSITIVE'|'GREATER_THAN_OR_EQUAL', ] }, 'CostCategories': { 'Key': 'string', 'Values': [ 'string', ], 'MatchOptions': [ 'EQUALS'|'ABSENT'|'STARTS_WITH'|'ENDS_WITH'|'CONTAINS'|'CASE_SENSITIVE'|'CASE_INSENSITIVE'|'GREATER_THAN_OR_EQUAL', ] } }, PredictionIntervalLevel=123 )
- Parameters:
TimePeriod (dict) –
[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
is2017-01-01
andend
is2017-05-01
, then the cost and usage data is retrieved from2017-01-01
up to and including2017-04-30
but not including2017-05-01
. The start date must be equal to or later than the current date to avoid a validation error.Start (string) – [REQUIRED]
The beginning of the time period. The start date is inclusive. For example, if
start
is2017-01-01
, Amazon Web Services retrieves cost and usage data starting at2017-01-01
up to the end date. The start date must be equal to or no later than the current date to avoid a validation error.End (string) – [REQUIRED]
The end of the time period. The end date is exclusive. For example, if
end
is2017-05-01
, Amazon Web Services retrieves cost and usage data from the start date up to, but not including,2017-05-01
.
Metric (string) –
[REQUIRED]
Which metric Cost Explorer uses to create your forecast.
Valid values for a
GetUsageForecast
call are the following:USAGE_QUANTITY
NORMALIZED_USAGE_AMOUNT
Granularity (string) –
[REQUIRED]
How granular you want the forecast to be. You can get 3 months of
DAILY
forecasts or 12 months ofMONTHLY
forecasts.The
GetUsageForecast
operation supports onlyDAILY
andMONTHLY
granularities.Filter (dict) –
The filters that you want to use to filter your forecast. The
GetUsageForecast
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
Or (list) –
Return results that match either
Dimension
object.(dict) –
Use
Expression
to filter in various Cost Explorer APIs.Not all
Expression
types are supported in each API. Refer to the documentation for each specific API to see what is supported.There are two patterns:
Simple dimension values.
There are three types of simple dimension values:
CostCategories
,Tags
, andDimensions
.Specify the
CostCategories
field to define a filter that acts on Cost Categories.Specify the
Tags
field to define a filter that acts on Cost Allocation Tags.Specify the
Dimensions
field to define a filter that acts on the DimensionValues.
For each filter type, you can set the dimension name and values for the filters that you plan to use.
For example, you can filter for
REGION==us-east-1 OR REGION==us-west-1
. ForGetRightsizingRecommendation
, the Region is a full name (for example,REGION==US East (N. Virginia)
.The corresponding
Expression
for this example is as follows:{ "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } }
As shown in the previous example, lists of dimension values are combined with
OR
when applying the filter.
You can also set different match options to further control how the filter behaves. Not all APIs support match options. Refer to the documentation for each specific API to see what is supported.
For example, you can filter for linked account names that start with “a”.
The corresponding
Expression
for this example is as follows:{ "Dimensions": { "Key": "LINKED_ACCOUNT_NAME", "MatchOptions": [ "STARTS_WITH" ], "Values": [ "a" ] } }
Compound
Expression
types with logical operations.You can use multiple
Expression
types and the logical operatorsAND/OR/NOT
to create a list of one or moreExpression
objects. By doing this, you can filter by more advanced options.For example, you can filter by
((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer)
.The corresponding
Expression
for this example is as follows:{ "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Note
Because each
Expression
can have only one operator, the service returns an error if more than one is specified. The following example shows anExpression
object that creates an error:{ "And": [ ... ], "Dimensions": { "Key": "USAGE_TYPE", "Values": [ "DataTransfer" ] } }
The following is an example of the corresponding error message:
"Expression has more than one roots. Only one root operator is allowed for each expression: And, Or, Not, Dimensions, Tags, CostCategories"
Note
For the
GetRightsizingRecommendation
action, a combination of OR and NOT isn’t supported. OR isn’t supported between different dimensions, or dimensions and tags. NOT operators aren’t supported. Dimensions are also limited toLINKED_ACCOUNT
,REGION
, orRIGHTSIZING_TYPE
.For the
GetReservationPurchaseRecommendation
action, only NOT is supported. AND and OR aren’t supported. Dimensions are limited toLINKED_ACCOUNT
.
And (list) –
Return results that match both
Dimension
objects.(dict) –
Use
Expression
to filter in various Cost Explorer APIs.Not all
Expression
types are supported in each API. Refer to the documentation for each specific API to see what is supported.There are two patterns:
Simple dimension values.
There are three types of simple dimension values:
CostCategories
,Tags
, andDimensions
.Specify the
CostCategories
field to define a filter that acts on Cost Categories.Specify the
Tags
field to define a filter that acts on Cost Allocation Tags.Specify the
Dimensions
field to define a filter that acts on the DimensionValues.
For each filter type, you can set the dimension name and values for the filters that you plan to use.
For example, you can filter for
REGION==us-east-1 OR REGION==us-west-1
. ForGetRightsizingRecommendation
, the Region is a full name (for example,REGION==US East (N. Virginia)
.The corresponding
Expression
for this example is as follows:{ "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } }
As shown in the previous example, lists of dimension values are combined with
OR
when applying the filter.
You can also set different match options to further control how the filter behaves. Not all APIs support match options. Refer to the documentation for each specific API to see what is supported.
For example, you can filter for linked account names that start with “a”.
The corresponding
Expression
for this example is as follows:{ "Dimensions": { "Key": "LINKED_ACCOUNT_NAME", "MatchOptions": [ "STARTS_WITH" ], "Values": [ "a" ] } }
Compound
Expression
types with logical operations.You can use multiple
Expression
types and the logical operatorsAND/OR/NOT
to create a list of one or moreExpression
objects. By doing this, you can filter by more advanced options.For example, you can filter by
((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer)
.The corresponding
Expression
for this example is as follows:{ "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Note
Because each
Expression
can have only one operator, the service returns an error if more than one is specified. The following example shows anExpression
object that creates an error:{ "And": [ ... ], "Dimensions": { "Key": "USAGE_TYPE", "Values": [ "DataTransfer" ] } }
The following is an example of the corresponding error message:
"Expression has more than one roots. Only one root operator is allowed for each expression: And, Or, Not, Dimensions, Tags, CostCategories"
Note
For the
GetRightsizingRecommendation
action, a combination of OR and NOT isn’t supported. OR isn’t supported between different dimensions, or dimensions and tags. NOT operators aren’t supported. Dimensions are also limited toLINKED_ACCOUNT
,REGION
, orRIGHTSIZING_TYPE
.For the
GetReservationPurchaseRecommendation
action, only NOT is supported. AND and OR aren’t supported. Dimensions are limited toLINKED_ACCOUNT
.
Not (dict) –
Return results that don’t match a
Dimension
object.Dimensions (dict) –
The specific
Dimension
to use forExpression
.Key (string) –
The names of the metadata types that you can use to filter and group your results. For example,
AZ
returns a list of Availability Zones.Not all dimensions are supported in each API. Refer to the documentation for each specific API to see what is supported.
LINK_ACCOUNT_NAME
andSERVICE_CODE
can only be used in CostCategoryRule.ANOMALY_TOTAL_IMPACT_ABSOLUTE
andANOMALY_TOTAL_IMPACT_PERCENTAGE
can only be used in AnomalySubscriptions.Values (list) –
The metadata values that you can use to filter and group your results. You can use
GetDimensionValues
to find specific values.(string) –
MatchOptions (list) –
The match options that you can use to filter your results.
MatchOptions
is only applicable for actions related to Cost Category and Anomaly Subscriptions. Refer to the documentation for each specific API to see what is supported.The default values for
MatchOptions
areEQUALS
andCASE_SENSITIVE
.(string) –
Tags (dict) –
The specific
Tag
to use forExpression
.Key (string) –
The key for the tag.
Values (list) –
The specific value of the tag.
(string) –
MatchOptions (list) –
The match options that you can use to filter your results.
MatchOptions
is only applicable for actions related to Cost Category. The default values forMatchOptions
areEQUALS
andCASE_SENSITIVE
.(string) –
CostCategories (dict) –
The filter that’s based on
CostCategory
values.Key (string) –
The unique name of the Cost Category.
Values (list) –
The specific value of the Cost Category.
(string) –
MatchOptions (list) –
The match options that you can use to filter your results. MatchOptions is only applicable for actions related to cost category. The default values for
MatchOptions
isEQUALS
andCASE_SENSITIVE
.(string) –
PredictionIntervalLevel (integer) – 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.
- Return type:
dict
- Returns:
Response Syntax
{ 'Total': { 'Amount': 'string', 'Unit': 'string' }, 'ForecastResultsByTime': [ { 'TimePeriod': { 'Start': 'string', 'End': 'string' }, 'MeanValue': 'string', 'PredictionIntervalLowerBound': 'string', 'PredictionIntervalUpperBound': 'string' }, ] }
Response Structure
(dict) –
Total (dict) –
How much you’re forecasted to use over the forecast period.
Amount (string) –
The actual number that represents the metric.
Unit (string) –
The unit that the metric is given in.
ForecastResultsByTime (list) –
The forecasts for your query, in order. For
DAILY
forecasts, this is a list of days. ForMONTHLY
forecasts, this is a list of months.(dict) –
The forecast that’s created for your query.
TimePeriod (dict) –
The period of time that the forecast covers.
Start (string) –
The beginning of the time period. The start date is inclusive. For example, if
start
is2017-01-01
, Amazon Web Services retrieves cost and usage data starting at2017-01-01
up to the end date. The start date must be equal to or no later than the current date to avoid a validation error.End (string) –
The end of the time period. The end date is exclusive. For example, if
end
is2017-05-01
, Amazon Web Services retrieves cost and usage data from the start date up to, but not including,2017-05-01
.
MeanValue (string) –
The mean value of the forecast.
PredictionIntervalLowerBound (string) –
The lower limit for the prediction interval.
PredictionIntervalUpperBound (string) –
The upper limit for the prediction interval.
Exceptions
CostExplorer.Client.exceptions.LimitExceededException
CostExplorer.Client.exceptions.DataUnavailableException
CostExplorer.Client.exceptions.UnresolvableUsageUnitException