2019/07/26 - AWS Cost Explorer Service - 1 new6 updated api methods
Changes Update ce client to latest version
Creates recommendations that helps you save cost by identifying idle and underutilized Amazon EC2 instances.
Recommendations are generated to either downsize or terminate instances, along with providing savings detail and metrics. For details on calculation and function, see Optimizing Your Cost with Rightsizing Recommendations.
See also: AWS API Documentation
Request Syntax
client.get_rightsizing_recommendation(
Filter={
'Or': [
{'... recursive ...'},
],
'And': [
{'... recursive ...'},
],
'Not': {'... recursive ...'},
'Dimensions': {
'Key': 'AZ'|'INSTANCE_TYPE'|'LINKED_ACCOUNT'|'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'|'CACHE_ENGINE'|'INSTANCE_TYPE_FAMILY'|'BILLING_ENTITY'|'RESERVATION_ID'|'RIGHTSIZING_TYPE',
'Values': [
'string',
]
},
'Tags': {
'Key': 'string',
'Values': [
'string',
]
}
},
Service='string',
PageSize=123,
NextPageToken='string'
)
dict
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Or (list) --
Return results that match either Dimension object.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
And (list) --
Return results that match both Dimension objects.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Not (dict) --
Return results that don't match a Dimension object.
Dimensions (dict) --
The specific Dimension to use for Expression.
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.
Values (list) --
The metadata values that you can use to filter and group your results. You can use GetDimensionValues to find specific values.
Valid values for the SERVICE dimension are Amazon Elastic Compute Cloud - Compute, Amazon Elasticsearch Service, Amazon ElastiCache, Amazon Redshift, and Amazon Relational Database Service.
(string) --
Tags (dict) --
The specific Tag to use for Expression.
Key (string) --
The key for the tag.
Values (list) --
The specific value of the tag.
(string) --
string
[REQUIRED]
The specific service that you want recommendations for.
integer
The number of recommendations that you want returned in a single response object.
string
The pagination token that indicates the next set of results that you want to retrieve.
dict
Response Syntax
{
'Metadata': {
'RecommendationId': 'string',
'GenerationTimestamp': 'string',
'LookbackPeriodInDays': 'SEVEN_DAYS'|'THIRTY_DAYS'|'SIXTY_DAYS'
},
'Summary': {
'TotalRecommendationCount': 'string',
'EstimatedTotalMonthlySavingsAmount': 'string',
'SavingsCurrencyCode': 'string',
'SavingsPercentage': 'string'
},
'RightsizingRecommendations': [
{
'AccountId': 'string',
'CurrentInstance': {
'ResourceId': 'string',
'Tags': [
{
'Key': 'string',
'Values': [
'string',
]
},
],
'ResourceDetails': {
'EC2ResourceDetails': {
'HourlyOnDemandRate': 'string',
'InstanceType': 'string',
'Platform': 'string',
'Region': 'string',
'Sku': 'string',
'Memory': 'string',
'NetworkPerformance': 'string',
'Storage': 'string',
'Vcpu': 'string'
}
},
'ResourceUtilization': {
'EC2ResourceUtilization': {
'MaxCpuUtilizationPercentage': 'string',
'MaxMemoryUtilizationPercentage': 'string',
'MaxStorageUtilizationPercentage': 'string'
}
},
'ReservationCoveredHoursInLookbackPeriod': 'string',
'OnDemandHoursInLookbackPeriod': 'string',
'TotalRunningHoursInLookbackPeriod': 'string',
'MonthlyCost': 'string',
'CurrencyCode': 'string'
},
'RightsizingType': 'TERMINATE'|'MODIFY',
'ModifyRecommendationDetail': {
'TargetInstances': [
{
'EstimatedMonthlyCost': 'string',
'EstimatedMonthlySavings': 'string',
'CurrencyCode': 'string',
'DefaultTargetInstance': True|False,
'ResourceDetails': {
'EC2ResourceDetails': {
'HourlyOnDemandRate': 'string',
'InstanceType': 'string',
'Platform': 'string',
'Region': 'string',
'Sku': 'string',
'Memory': 'string',
'NetworkPerformance': 'string',
'Storage': 'string',
'Vcpu': 'string'
}
},
'ExpectedResourceUtilization': {
'EC2ResourceUtilization': {
'MaxCpuUtilizationPercentage': 'string',
'MaxMemoryUtilizationPercentage': 'string',
'MaxStorageUtilizationPercentage': 'string'
}
}
},
]
},
'TerminateRecommendationDetail': {
'EstimatedMonthlySavings': 'string',
'CurrencyCode': 'string'
}
},
],
'NextPageToken': 'string'
}
Response Structure
(dict) --
Metadata (dict) --
Information regarding this specific recommendation set.
RecommendationId (string) --
The ID for this specific recommendation.
GenerationTimestamp (string) --
The time stamp for when Amazon Web Services made this recommendation.
LookbackPeriodInDays (string) --
How many days of previous usage that Amazon Web Services considers when making this recommendation.
Summary (dict) --
Summary of this recommendation set.
TotalRecommendationCount (string) --
Total number of instance recommendations.
EstimatedTotalMonthlySavingsAmount (string) --
Estimated total savings resulting from modifications, on a monthly basis.
SavingsCurrencyCode (string) --
The currency code that Amazon Web Services used to calculate the savings.
SavingsPercentage (string) --
Savings percentage based on the recommended modifications, relative to the total On Demand costs associated with these instances.
RightsizingRecommendations (list) --
Recommendations to rightsize resources.
(dict) --
Recommendations to rightsize resources.
AccountId (string) --
The account that this recommendation is for.
CurrentInstance (dict) --
Context regarding the current instance.
ResourceId (string) --
Resource ID of the current instance.
Tags (list) --
Cost allocation resource tags applied to the instance.
(dict) --
The values that are available for a tag.
Key (string) --
The key for the tag.
Values (list) --
The specific value of the tag.
(string) --
ResourceDetails (dict) --
Details about the resource and utilization.
EC2ResourceDetails (dict) --
Details on the Amazon EC2 resource.
HourlyOnDemandRate (string) --
Hourly public On Demand rate for the instance type.
InstanceType (string) --
The type of Amazon Web Services instance.
Platform (string) --
The platform of the Amazon Web Services instance. The platform is the specific combination of operating system, license model, and software on an instance.
Region (string) --
The Amazon Web Services Region of the instance.
Sku (string) --
The SKU of the product.
Memory (string) --
Memory capacity of Amazon Web Services instance.
NetworkPerformance (string) --
Network performance capacity of the Amazon Web Services instance.
Storage (string) --
The disk storage of the Amazon Web Services instance (Not EBS storage).
Vcpu (string) --
Number of VCPU cores in the Amazon Web Services instance type.
ResourceUtilization (dict) --
Utilization information of the current instance during the lookback period.
EC2ResourceUtilization (dict) --
Utilization of current Amazon EC2 Instance
MaxCpuUtilizationPercentage (string) --
Maximum observed or expected CPU utilization of the instance.
MaxMemoryUtilizationPercentage (string) --
Maximum observed or expected memory utilization of the instance.
MaxStorageUtilizationPercentage (string) --
Maximum observed or expected storage utilization of the instance (does not measure EBS storage).
ReservationCoveredHoursInLookbackPeriod (string) --
Number of hours during the lookback period covered by reservations.
OnDemandHoursInLookbackPeriod (string) --
Number of hours during the lookback period billed at On Demand rates.
TotalRunningHoursInLookbackPeriod (string) --
The total number of hours the instance ran during the lookback period.
MonthlyCost (string) --
Current On Demand cost of operating this instance on a monthly basis.
CurrencyCode (string) --
The currency code that Amazon Web Services used to calculate the costs for this instance.
RightsizingType (string) --
Recommendation to either terminate or modify the resource.
ModifyRecommendationDetail (dict) --
Details for modification recommendations.
TargetInstances (list) --
Identifies whether this instance type is the Amazon Web Services default recommendation.
(dict) --
Details on recommended instance.
EstimatedMonthlyCost (string) --
Expected cost to operate this instance type on a monthly basis.
EstimatedMonthlySavings (string) --
Estimated savings resulting from modification, on a monthly basis.
CurrencyCode (string) --
The currency code that Amazon Web Services used to calculate the costs for this instance.
DefaultTargetInstance (boolean) --
Indicates whether or not this recommendation is the defaulted Amazon Web Services recommendation.
ResourceDetails (dict) --
Details on the target instance type.
EC2ResourceDetails (dict) --
Details on the Amazon EC2 resource.
HourlyOnDemandRate (string) --
Hourly public On Demand rate for the instance type.
InstanceType (string) --
The type of Amazon Web Services instance.
Platform (string) --
The platform of the Amazon Web Services instance. The platform is the specific combination of operating system, license model, and software on an instance.
Region (string) --
The Amazon Web Services Region of the instance.
Sku (string) --
The SKU of the product.
Memory (string) --
Memory capacity of Amazon Web Services instance.
NetworkPerformance (string) --
Network performance capacity of the Amazon Web Services instance.
Storage (string) --
The disk storage of the Amazon Web Services instance (Not EBS storage).
Vcpu (string) --
Number of VCPU cores in the Amazon Web Services instance type.
ExpectedResourceUtilization (dict) --
Expected utilization metrics for target instance type.
EC2ResourceUtilization (dict) --
Utilization of current Amazon EC2 Instance
MaxCpuUtilizationPercentage (string) --
Maximum observed or expected CPU utilization of the instance.
MaxMemoryUtilizationPercentage (string) --
Maximum observed or expected memory utilization of the instance.
MaxStorageUtilizationPercentage (string) --
Maximum observed or expected storage utilization of the instance (does not measure EBS storage).
TerminateRecommendationDetail (dict) --
Details for termination recommendations.
EstimatedMonthlySavings (string) --
Estimated savings resulting from modification, on a monthly basis.
CurrencyCode (string) --
The currency code that Amazon Web Services used to calculate the costs for this instance.
NextPageToken (string) --
The token to retrieve the next set of results.
{'Filter': {'Dimensions': {'Key': {'RIGHTSIZING_TYPE'}}}}
Retrieves cost and usage metrics for your account. You can specify which cost and usage-related metric, such as BlendedCosts or UsageQuantity, that you want the request to return. You can also filter and group your data by various dimensions, such as SERVICE or AZ, in a specific time range. For a complete list of valid dimensions, see the GetDimensionValues operation. Master accounts in an organization in AWS Organizations have access to all member accounts.
See also: AWS API Documentation
Request Syntax
client.get_cost_and_usage(
TimePeriod={
'Start': 'string',
'End': 'string'
},
Granularity='DAILY'|'MONTHLY'|'HOURLY',
Filter={
'Or': [
{'... recursive ...'},
],
'And': [
{'... recursive ...'},
],
'Not': {'... recursive ...'},
'Dimensions': {
'Key': 'AZ'|'INSTANCE_TYPE'|'LINKED_ACCOUNT'|'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'|'CACHE_ENGINE'|'INSTANCE_TYPE_FAMILY'|'BILLING_ENTITY'|'RESERVATION_ID'|'RIGHTSIZING_TYPE',
'Values': [
'string',
]
},
'Tags': {
'Key': 'string',
'Values': [
'string',
]
}
},
Metrics=[
'string',
],
GroupBy=[
{
'Type': 'DIMENSION'|'TAG',
'Key': 'string'
},
],
NextPageToken='string'
)
dict
[REQUIRED]
Sets the start and end dates for retrieving AWS costs. The start date is inclusive, but the end date is exclusive. 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.
Start (string) -- [REQUIRED]
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) -- [REQUIRED]
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
string
Sets the AWS cost granularity to MONTHLY or DAILY. If Granularity isn't set, the response object doesn't include the Granularity, either MONTHLY or DAILY.
The GetCostAndUsageRequest operation supports only DAILY and MONTHLY granularities.
dict
Filters AWS costs by different dimensions. For example, you can specify SERVICE and LINKED_ACCOUNT and get the costs that are associated with that account's usage of that service. You can nest Expression objects to define any combination of dimension filters. For more information, see Expression.
Or (list) --
Return results that match either Dimension object.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
And (list) --
Return results that match both Dimension objects.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Not (dict) --
Return results that don't match a Dimension object.
Dimensions (dict) --
The specific Dimension to use for Expression.
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.
Values (list) --
The metadata values that you can use to filter and group your results. You can use GetDimensionValues to find specific values.
Valid values for the SERVICE dimension are Amazon Elastic Compute Cloud - Compute, Amazon Elasticsearch Service, Amazon ElastiCache, Amazon Redshift, and Amazon Relational Database Service.
(string) --
Tags (dict) --
The specific Tag to use for Expression.
Key (string) --
The key for the tag.
Values (list) --
The specific value of the tag.
(string) --
list
Which metrics are returned in the query. For more information about blended and unblended rates, see Why does the "blended" annotation appear on some line items in my bill?.
Valid values are AmortizedCost, BlendedCost, NetAmortizedCost, NetUnblendedCost, NormalizedUsageAmount, UnblendedCost, and UsageQuantity.
Metrics is required for GetCostAndUsage requests.
(string) --
list
You can group AWS costs using up to two different groups, either dimensions, tag keys, or both.
When you group by tag key, you get all tag values, including empty strings.
Valid values are AZ, INSTANCE_TYPE, LEGAL_ENTITY_NAME, LINKED_ACCOUNT, OPERATION, PLATFORM, PURCHASE_TYPE, SERVICE, TAGS, TENANCY, and USAGE_TYPE.
(dict) --
Represents a group when you specify a group by criteria or in the response to a query with a specific grouping.
Type (string) --
The string that represents the type of group.
Key (string) --
The string that represents a key for a specified group.
string
The token to retrieve the next set of results. AWS provides the token when the response from a previous call has more results than the maximum page size.
dict
Response Syntax
{
'NextPageToken': 'string',
'GroupDefinitions': [
{
'Type': 'DIMENSION'|'TAG',
'Key': 'string'
},
],
'ResultsByTime': [
{
'TimePeriod': {
'Start': 'string',
'End': 'string'
},
'Total': {
'string': {
'Amount': 'string',
'Unit': 'string'
}
},
'Groups': [
{
'Keys': [
'string',
],
'Metrics': {
'string': {
'Amount': 'string',
'Unit': 'string'
}
}
},
],
'Estimated': True|False
},
]
}
Response Structure
(dict) --
NextPageToken (string) --
The token for the next set of retrievable results. AWS provides the token when the response from a previous call has more results than the maximum page size.
GroupDefinitions (list) --
The groups that are specified by the Filter or GroupBy parameters in the request.
(dict) --
Represents a group when you specify a group by criteria or in the response to a query with a specific grouping.
Type (string) --
The string that represents the type of group.
Key (string) --
The string that represents a key for a specified group.
ResultsByTime (list) --
The time period that is covered by the results in the response.
(dict) --
The result that is associated with a time period.
TimePeriod (dict) --
The time period that the result covers.
Start (string) --
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) --
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
Total (dict) --
The total amount of cost or usage accrued during the time period.
(string) --
(dict) --
The aggregated value for a metric.
Amount (string) --
The actual number that represents the metric.
Unit (string) --
The unit that the metric is given in.
Groups (list) --
The groups that this time period includes.
(dict) --
One level of grouped data in the results.
Keys (list) --
The keys that are included in this group.
(string) --
Metrics (dict) --
The metrics that are included in this group.
(string) --
(dict) --
The aggregated value for a metric.
Amount (string) --
The actual number that represents the metric.
Unit (string) --
The unit that the metric is given in.
Estimated (boolean) --
Whether the result is estimated.
{'Filter': {'Dimensions': {'Key': {'RIGHTSIZING_TYPE'}}}}
Retrieves a forecast for how much Amazon Web Services predicts that you will spend over the forecast time period that you select, based on your past costs.
See also: AWS API Documentation
Request Syntax
client.get_cost_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'|'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'|'CACHE_ENGINE'|'INSTANCE_TYPE_FAMILY'|'BILLING_ENTITY'|'RESERVATION_ID'|'RIGHTSIZING_TYPE',
'Values': [
'string',
]
},
'Tags': {
'Key': 'string',
'Values': [
'string',
]
}
},
PredictionIntervalLevel=123
)
dict
[REQUIRED]
The period of time that you want the forecast to cover.
Start (string) -- [REQUIRED]
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) -- [REQUIRED]
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
string
[REQUIRED]
Which metric Cost Explorer uses to create your forecast. For more information about blended and unblended rates, see Why does the "blended" annotation appear on some line items in my bill?.
Valid values for a GetCostForecast call are the following:
AMORTIZED_COST
BLENDED_COST
NET_AMORTIZED_COST
NET_UNBLENDED_COST
UNBLENDED_COST
string
[REQUIRED]
How granular you want the forecast to be. You can get 3 months of DAILY forecasts or 12 months of MONTHLY forecasts.
The GetCostForecast operation supports only DAILY and MONTHLY granularities.
dict
The filters that you want to use to filter your forecast. Cost Explorer API supports all of the Cost Explorer filters.
Or (list) --
Return results that match either Dimension object.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
And (list) --
Return results that match both Dimension objects.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Not (dict) --
Return results that don't match a Dimension object.
Dimensions (dict) --
The specific Dimension to use for Expression.
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.
Values (list) --
The metadata values that you can use to filter and group your results. You can use GetDimensionValues to find specific values.
Valid values for the SERVICE dimension are Amazon Elastic Compute Cloud - Compute, Amazon Elasticsearch Service, Amazon ElastiCache, Amazon Redshift, and Amazon Relational Database Service.
(string) --
Tags (dict) --
The specific Tag to use for Expression.
Key (string) --
The key for the tag.
Values (list) --
The specific value of the tag.
(string) --
integer
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.
dict
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 are forecasted to spend over the forecast period, in USD.
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. For MONTHLY forecasts, this is a list of months.
(dict) --
The forecast created for your query.
TimePeriod (dict) --
The period of time that the forecast covers.
Start (string) --
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) --
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS 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.
{'Dimension': {'RIGHTSIZING_TYPE'}}
Retrieves all available filter values for a specified filter over a period of time. You can search the dimension values for an arbitrary string.
See also: AWS API Documentation
Request Syntax
client.get_dimension_values(
SearchString='string',
TimePeriod={
'Start': 'string',
'End': 'string'
},
Dimension='AZ'|'INSTANCE_TYPE'|'LINKED_ACCOUNT'|'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'|'CACHE_ENGINE'|'INSTANCE_TYPE_FAMILY'|'BILLING_ENTITY'|'RESERVATION_ID'|'RIGHTSIZING_TYPE',
Context='COST_AND_USAGE'|'RESERVATIONS',
NextPageToken='string'
)
string
The value that you want to search the filter values for.
dict
[REQUIRED]
The start and end dates for retrieving the dimension values. The start date is inclusive, but the end date is exclusive. 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.
Start (string) -- [REQUIRED]
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) -- [REQUIRED]
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
string
[REQUIRED]
The name of the dimension. Each Dimension is available for a different Context. For more information, see Context.
string
The context for the call to GetDimensionValues. This can be RESERVATIONS or COST_AND_USAGE. The default value is COST_AND_USAGE. If the context is set to RESERVATIONS, the resulting dimension values can be used in the GetReservationUtilization operation. If the context is set to COST_AND_USAGE, the resulting dimension values can be used in the GetCostAndUsage operation.
If you set the context to COST_AND_USAGE, you can use the following dimensions for searching:
AZ - The Availability Zone. An example is us-east-1a.
DATABASE_ENGINE - The Amazon Relational Database Service database. Examples are Aurora or MySQL.
INSTANCE_TYPE - The type of Amazon EC2 instance. An example is m4.xlarge.
LEGAL_ENTITY_NAME - The name of the organization that sells you AWS services, such as Amazon Web Services.
LINKED_ACCOUNT - The description in the attribute map that includes the full name of the member account. The value field contains the AWS ID of the member account.
OPERATING_SYSTEM - The operating system. Examples are Windows or Linux.
OPERATION - The action performed. Examples include RunInstance and CreateBucket.
PLATFORM - The Amazon EC2 operating system. Examples are Windows or Linux.
PURCHASE_TYPE - The reservation type of the purchase to which this usage is related. Examples include On-Demand Instances and Standard Reserved Instances.
SERVICE - The AWS service such as Amazon DynamoDB.
USAGE_TYPE - The type of usage. An example is DataTransfer-In-Bytes. The response for the GetDimensionValues operation includes a unit attribute. Examples include GB and Hrs.
USAGE_TYPE_GROUP - The grouping of common usage types. An example is Amazon EC2: CloudWatch – Alarms. The response for this operation includes a unit attribute.
RECORD_TYPE - The different types of charges such as RI fees, usage costs, tax refunds, and credits.
If you set the context to RESERVATIONS, you can use the following dimensions for searching:
AZ - The Availability Zone. An example is us-east-1a.
CACHE_ENGINE - The Amazon ElastiCache operating system. Examples are Windows or Linux.
DEPLOYMENT_OPTION - The scope of Amazon Relational Database Service deployments. Valid values are SingleAZ and MultiAZ.
INSTANCE_TYPE - The type of Amazon EC2 instance. An example is m4.xlarge.
LINKED_ACCOUNT - The description in the attribute map that includes the full name of the member account. The value field contains the AWS ID of the member account.
PLATFORM - The Amazon EC2 operating system. Examples are Windows or Linux.
REGION - The AWS Region.
SCOPE (Utilization only) - The scope of a Reserved Instance (RI). Values are regional or a single Availability Zone.
TAG (Coverage only) - The tags that are associated with a Reserved Instance (RI).
TENANCY - The tenancy of a resource. Examples are shared or dedicated.
string
The token to retrieve the next set of results. AWS provides the token when the response from a previous call has more results than the maximum page size.
dict
Response Syntax
{
'DimensionValues': [
{
'Value': 'string',
'Attributes': {
'string': 'string'
}
},
],
'ReturnSize': 123,
'TotalSize': 123,
'NextPageToken': 'string'
}
Response Structure
(dict) --
DimensionValues (list) --
The filters that you used to filter your request. Some dimensions are available only for a specific context.
If you set the context to COST_AND_USAGE, you can use the following dimensions for searching:
AZ - The Availability Zone. An example is us-east-1a.
DATABASE_ENGINE - The Amazon Relational Database Service database. Examples are Aurora or MySQL.
INSTANCE_TYPE - The type of Amazon EC2 instance. An example is m4.xlarge.
LEGAL_ENTITY_NAME - The name of the organization that sells you AWS services, such as Amazon Web Services.
LINKED_ACCOUNT - The description in the attribute map that includes the full name of the member account. The value field contains the AWS ID of the member account.
OPERATING_SYSTEM - The operating system. Examples are Windows or Linux.
OPERATION - The action performed. Examples include RunInstance and CreateBucket.
PLATFORM - The Amazon EC2 operating system. Examples are Windows or Linux.
PURCHASE_TYPE - The reservation type of the purchase to which this usage is related. Examples include On-Demand Instances and Standard Reserved Instances.
SERVICE - The AWS service such as Amazon DynamoDB.
USAGE_TYPE - The type of usage. An example is DataTransfer-In-Bytes. The response for the GetDimensionValues operation includes a unit attribute. Examples include GB and Hrs.
USAGE_TYPE_GROUP - The grouping of common usage types. An example is Amazon EC2: CloudWatch – Alarms. The response for this operation includes a unit attribute.
RECORD_TYPE - The different types of charges such as RI fees, usage costs, tax refunds, and credits.
If you set the context to RESERVATIONS, you can use the following dimensions for searching:
AZ - The Availability Zone. An example is us-east-1a.
CACHE_ENGINE - The Amazon ElastiCache operating system. Examples are Windows or Linux.
DEPLOYMENT_OPTION - The scope of Amazon Relational Database Service deployments. Valid values are SingleAZ and MultiAZ.
INSTANCE_TYPE - The type of Amazon EC2 instance. An example is m4.xlarge.
LINKED_ACCOUNT - The description in the attribute map that includes the full name of the member account. The value field contains the AWS ID of the member account.
PLATFORM - The Amazon EC2 operating system. Examples are Windows or Linux.
REGION - The AWS Region.
SCOPE (Utilization only) - The scope of a Reserved Instance (RI). Values are regional or a single Availability Zone.
TAG (Coverage only) - The tags that are associated with a Reserved Instance (RI).
TENANCY - The tenancy of a resource. Examples are shared or dedicated.
(dict) --
The metadata of a specific type that you can use to filter and group your results. You can use GetDimensionValues to find specific values.
Value (string) --
The value of a dimension with a specific attribute.
Attributes (dict) --
The attribute that applies to a specific Dimension.
(string) --
(string) --
ReturnSize (integer) --
The number of results that AWS returned at one time.
TotalSize (integer) --
The total number of search results.
NextPageToken (string) --
The token for the next set of retrievable results. AWS provides the token when the response from a previous call has more results than the maximum page size.
{'Filter': {'Dimensions': {'Key': {'RIGHTSIZING_TYPE'}}}}
Retrieves the reservation coverage for your account. This enables you to see how much of your Amazon Elastic Compute Cloud, Amazon ElastiCache, Amazon Relational Database Service, or Amazon Redshift usage is covered by a reservation. An organization's master account can see the coverage of the associated member accounts. For any time period, you can filter data about reservation usage by the following dimensions:
AZ
CACHE_ENGINE
DATABASE_ENGINE
DEPLOYMENT_OPTION
INSTANCE_TYPE
LINKED_ACCOUNT
OPERATING_SYSTEM
PLATFORM
REGION
SERVICE
TAG
TENANCY
To determine valid values for a dimension, use the GetDimensionValues operation.
See also: AWS API Documentation
Request Syntax
client.get_reservation_coverage(
TimePeriod={
'Start': 'string',
'End': 'string'
},
GroupBy=[
{
'Type': 'DIMENSION'|'TAG',
'Key': 'string'
},
],
Granularity='DAILY'|'MONTHLY'|'HOURLY',
Filter={
'Or': [
{'... recursive ...'},
],
'And': [
{'... recursive ...'},
],
'Not': {'... recursive ...'},
'Dimensions': {
'Key': 'AZ'|'INSTANCE_TYPE'|'LINKED_ACCOUNT'|'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'|'CACHE_ENGINE'|'INSTANCE_TYPE_FAMILY'|'BILLING_ENTITY'|'RESERVATION_ID'|'RIGHTSIZING_TYPE',
'Values': [
'string',
]
},
'Tags': {
'Key': 'string',
'Values': [
'string',
]
}
},
Metrics=[
'string',
],
NextPageToken='string'
)
dict
[REQUIRED]
The start and end dates of the period that you want to retrieve data about reservation coverage for. You can retrieve data for a maximum of 13 months: the last 12 months and the current month. The start date is inclusive, but the end date is exclusive. 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.
Start (string) -- [REQUIRED]
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) -- [REQUIRED]
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
list
You can group the data by the following attributes:
AZ
CACHE_ENGINE
DATABASE_ENGINE
DEPLOYMENT_OPTION
INSTANCE_TYPE
LINKED_ACCOUNT
OPERATING_SYSTEM
PLATFORM
REGION
TENANCY
(dict) --
Represents a group when you specify a group by criteria or in the response to a query with a specific grouping.
Type (string) --
The string that represents the type of group.
Key (string) --
The string that represents a key for a specified group.
string
The granularity of the AWS cost data for the reservation. Valid values are MONTHLY and DAILY.
If GroupBy is set, Granularity can't be set. If Granularity isn't set, the response object doesn't include Granularity, either MONTHLY or DAILY.
The GetReservationCoverage operation supports only DAILY and MONTHLY granularities.
dict
Filters utilization data by dimensions. You can filter by the following dimensions:
AZ
CACHE_ENGINE
DATABASE_ENGINE
DEPLOYMENT_OPTION
INSTANCE_TYPE
LINKED_ACCOUNT
OPERATING_SYSTEM
PLATFORM
REGION
SERVICE
TAG
TENANCY
GetReservationCoverage uses the same Expression object as the other operations, but only AND is supported among each dimension. You can nest only one level deep. If there are multiple values for a dimension, they are OR'd together.
If you don't provide a SERVICE filter, Cost Explorer defaults to EC2.
Or (list) --
Return results that match either Dimension object.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
And (list) --
Return results that match both Dimension objects.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Not (dict) --
Return results that don't match a Dimension object.
Dimensions (dict) --
The specific Dimension to use for Expression.
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.
Values (list) --
The metadata values that you can use to filter and group your results. You can use GetDimensionValues to find specific values.
Valid values for the SERVICE dimension are Amazon Elastic Compute Cloud - Compute, Amazon Elasticsearch Service, Amazon ElastiCache, Amazon Redshift, and Amazon Relational Database Service.
(string) --
Tags (dict) --
The specific Tag to use for Expression.
Key (string) --
The key for the tag.
Values (list) --
The specific value of the tag.
(string) --
list
The measurement that you want your reservation coverage reported in.
Valid values are Hour, Unit, and Cost. You can use multiple values in a request.
(string) --
string
The token to retrieve the next set of results. AWS provides the token when the response from a previous call has more results than the maximum page size.
dict
Response Syntax
{
'CoveragesByTime': [
{
'TimePeriod': {
'Start': 'string',
'End': 'string'
},
'Groups': [
{
'Attributes': {
'string': 'string'
},
'Coverage': {
'CoverageHours': {
'OnDemandHours': 'string',
'ReservedHours': 'string',
'TotalRunningHours': 'string',
'CoverageHoursPercentage': 'string'
},
'CoverageNormalizedUnits': {
'OnDemandNormalizedUnits': 'string',
'ReservedNormalizedUnits': 'string',
'TotalRunningNormalizedUnits': 'string',
'CoverageNormalizedUnitsPercentage': 'string'
},
'CoverageCost': {
'OnDemandCost': 'string'
}
}
},
],
'Total': {
'CoverageHours': {
'OnDemandHours': 'string',
'ReservedHours': 'string',
'TotalRunningHours': 'string',
'CoverageHoursPercentage': 'string'
},
'CoverageNormalizedUnits': {
'OnDemandNormalizedUnits': 'string',
'ReservedNormalizedUnits': 'string',
'TotalRunningNormalizedUnits': 'string',
'CoverageNormalizedUnitsPercentage': 'string'
},
'CoverageCost': {
'OnDemandCost': 'string'
}
}
},
],
'Total': {
'CoverageHours': {
'OnDemandHours': 'string',
'ReservedHours': 'string',
'TotalRunningHours': 'string',
'CoverageHoursPercentage': 'string'
},
'CoverageNormalizedUnits': {
'OnDemandNormalizedUnits': 'string',
'ReservedNormalizedUnits': 'string',
'TotalRunningNormalizedUnits': 'string',
'CoverageNormalizedUnitsPercentage': 'string'
},
'CoverageCost': {
'OnDemandCost': 'string'
}
},
'NextPageToken': 'string'
}
Response Structure
(dict) --
CoveragesByTime (list) --
The amount of time that your reservations covered.
(dict) --
Reservation coverage for a specified period, in hours.
TimePeriod (dict) --
The period that this coverage was used over.
Start (string) --
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) --
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
Groups (list) --
The groups of instances that the reservation covered.
(dict) --
A group of reservations that share a set of attributes.
Attributes (dict) --
The attributes for this group of reservations.
(string) --
(string) --
Coverage (dict) --
How much instance usage this group of reservations covered.
CoverageHours (dict) --
The amount of instance usage that the reservation covered, in hours.
OnDemandHours (string) --
The number of instance running hours that On-Demand Instances covered.
ReservedHours (string) --
The number of instance running hours that reservations covered.
TotalRunningHours (string) --
The total instance usage, in hours.
CoverageHoursPercentage (string) --
The percentage of instance hours that a reservation covered.
CoverageNormalizedUnits (dict) --
The amount of instance usage that the reservation covered, in normalized units.
OnDemandNormalizedUnits (string) --
The number of normalized units that are covered by On-Demand Instances instead of a reservation.
ReservedNormalizedUnits (string) --
The number of normalized units that a reservation covers.
TotalRunningNormalizedUnits (string) --
The total number of normalized units that you used.
CoverageNormalizedUnitsPercentage (string) --
The percentage of your used instance normalized units that a reservation covers.
CoverageCost (dict) --
The amount of cost that the reservation covered.
OnDemandCost (string) --
How much an On-Demand instance cost.
Total (dict) --
The total reservation coverage, in hours.
CoverageHours (dict) --
The amount of instance usage that the reservation covered, in hours.
OnDemandHours (string) --
The number of instance running hours that On-Demand Instances covered.
ReservedHours (string) --
The number of instance running hours that reservations covered.
TotalRunningHours (string) --
The total instance usage, in hours.
CoverageHoursPercentage (string) --
The percentage of instance hours that a reservation covered.
CoverageNormalizedUnits (dict) --
The amount of instance usage that the reservation covered, in normalized units.
OnDemandNormalizedUnits (string) --
The number of normalized units that are covered by On-Demand Instances instead of a reservation.
ReservedNormalizedUnits (string) --
The number of normalized units that a reservation covers.
TotalRunningNormalizedUnits (string) --
The total number of normalized units that you used.
CoverageNormalizedUnitsPercentage (string) --
The percentage of your used instance normalized units that a reservation covers.
CoverageCost (dict) --
The amount of cost that the reservation covered.
OnDemandCost (string) --
How much an On-Demand instance cost.
Total (dict) --
The total amount of instance usage that a reservation covered.
CoverageHours (dict) --
The amount of instance usage that the reservation covered, in hours.
OnDemandHours (string) --
The number of instance running hours that On-Demand Instances covered.
ReservedHours (string) --
The number of instance running hours that reservations covered.
TotalRunningHours (string) --
The total instance usage, in hours.
CoverageHoursPercentage (string) --
The percentage of instance hours that a reservation covered.
CoverageNormalizedUnits (dict) --
The amount of instance usage that the reservation covered, in normalized units.
OnDemandNormalizedUnits (string) --
The number of normalized units that are covered by On-Demand Instances instead of a reservation.
ReservedNormalizedUnits (string) --
The number of normalized units that a reservation covers.
TotalRunningNormalizedUnits (string) --
The total number of normalized units that you used.
CoverageNormalizedUnitsPercentage (string) --
The percentage of your used instance normalized units that a reservation covers.
CoverageCost (dict) --
The amount of cost that the reservation covered.
OnDemandCost (string) --
How much an On-Demand instance cost.
NextPageToken (string) --
The token for the next set of retrievable results. AWS provides the token when the response from a previous call has more results than the maximum page size.
{'Filter': {'Dimensions': {'Key': {'RIGHTSIZING_TYPE'}}}}
Retrieves the reservation utilization for your account. Master accounts in an organization have access to member accounts. You can filter data by dimensions in a time period. You can use GetDimensionValues to determine the possible dimension values. Currently, you can group only by SUBSCRIPTION_ID.
See also: AWS API Documentation
Request Syntax
client.get_reservation_utilization(
TimePeriod={
'Start': 'string',
'End': 'string'
},
GroupBy=[
{
'Type': 'DIMENSION'|'TAG',
'Key': 'string'
},
],
Granularity='DAILY'|'MONTHLY'|'HOURLY',
Filter={
'Or': [
{'... recursive ...'},
],
'And': [
{'... recursive ...'},
],
'Not': {'... recursive ...'},
'Dimensions': {
'Key': 'AZ'|'INSTANCE_TYPE'|'LINKED_ACCOUNT'|'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'|'CACHE_ENGINE'|'INSTANCE_TYPE_FAMILY'|'BILLING_ENTITY'|'RESERVATION_ID'|'RIGHTSIZING_TYPE',
'Values': [
'string',
]
},
'Tags': {
'Key': 'string',
'Values': [
'string',
]
}
},
NextPageToken='string'
)
dict
[REQUIRED]
Sets the start and end dates for retrieving RI utilization. The start date is inclusive, but the end date is exclusive. 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.
Start (string) -- [REQUIRED]
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) -- [REQUIRED]
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
list
Groups only by SUBSCRIPTION_ID. Metadata is included.
(dict) --
Represents a group when you specify a group by criteria or in the response to a query with a specific grouping.
Type (string) --
The string that represents the type of group.
Key (string) --
The string that represents a key for a specified group.
string
If GroupBy is set, Granularity can't be set. If Granularity isn't set, the response object doesn't include Granularity, either MONTHLY or DAILY. If both GroupBy and Granularity aren't set, GetReservationUtilization defaults to DAILY.
The GetReservationUtilization operation supports only DAILY and MONTHLY granularities.
dict
Filters utilization data by dimensions. You can filter by the following dimensions:
AZ
CACHE_ENGINE
DATABASE_ENGINE
DEPLOYMENT_OPTION
INSTANCE_TYPE
LINKED_ACCOUNT
OPERATING_SYSTEM
PLATFORM
REGION
SERVICE
SCOPE
TENANCY
GetReservationUtilization uses the same Expression object as the other operations, but only AND is supported among each dimension, and nesting is supported up to only one level deep. If there are multiple values for a dimension, they are OR'd together.
Or (list) --
Return results that match either Dimension object.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
And (list) --
Return results that match both Dimension objects.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Not (dict) --
Return results that don't match a Dimension object.
Dimensions (dict) --
The specific Dimension to use for Expression.
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.
Values (list) --
The metadata values that you can use to filter and group your results. You can use GetDimensionValues to find specific values.
Valid values for the SERVICE dimension are Amazon Elastic Compute Cloud - Compute, Amazon Elasticsearch Service, Amazon ElastiCache, Amazon Redshift, and Amazon Relational Database Service.
(string) --
Tags (dict) --
The specific Tag to use for Expression.
Key (string) --
The key for the tag.
Values (list) --
The specific value of the tag.
(string) --
string
The token to retrieve the next set of results. AWS provides the token when the response from a previous call has more results than the maximum page size.
dict
Response Syntax
{
'UtilizationsByTime': [
{
'TimePeriod': {
'Start': 'string',
'End': 'string'
},
'Groups': [
{
'Key': 'string',
'Value': 'string',
'Attributes': {
'string': 'string'
},
'Utilization': {
'UtilizationPercentage': 'string',
'UtilizationPercentageInUnits': 'string',
'PurchasedHours': 'string',
'PurchasedUnits': 'string',
'TotalActualHours': 'string',
'TotalActualUnits': 'string',
'UnusedHours': 'string',
'UnusedUnits': 'string',
'OnDemandCostOfRIHoursUsed': 'string',
'NetRISavings': 'string',
'TotalPotentialRISavings': 'string',
'AmortizedUpfrontFee': 'string',
'AmortizedRecurringFee': 'string',
'TotalAmortizedFee': 'string'
}
},
],
'Total': {
'UtilizationPercentage': 'string',
'UtilizationPercentageInUnits': 'string',
'PurchasedHours': 'string',
'PurchasedUnits': 'string',
'TotalActualHours': 'string',
'TotalActualUnits': 'string',
'UnusedHours': 'string',
'UnusedUnits': 'string',
'OnDemandCostOfRIHoursUsed': 'string',
'NetRISavings': 'string',
'TotalPotentialRISavings': 'string',
'AmortizedUpfrontFee': 'string',
'AmortizedRecurringFee': 'string',
'TotalAmortizedFee': 'string'
}
},
],
'Total': {
'UtilizationPercentage': 'string',
'UtilizationPercentageInUnits': 'string',
'PurchasedHours': 'string',
'PurchasedUnits': 'string',
'TotalActualHours': 'string',
'TotalActualUnits': 'string',
'UnusedHours': 'string',
'UnusedUnits': 'string',
'OnDemandCostOfRIHoursUsed': 'string',
'NetRISavings': 'string',
'TotalPotentialRISavings': 'string',
'AmortizedUpfrontFee': 'string',
'AmortizedRecurringFee': 'string',
'TotalAmortizedFee': 'string'
},
'NextPageToken': 'string'
}
Response Structure
(dict) --
UtilizationsByTime (list) --
The amount of time that you used your RIs.
(dict) --
The amount of utilization, in hours.
TimePeriod (dict) --
The period of time that this utilization was used for.
Start (string) --
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) --
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
Groups (list) --
The groups that this utilization result uses.
(dict) --
A group of reservations that share a set of attributes.
Key (string) --
The key for a specific reservation attribute.
Value (string) --
The value of a specific reservation attribute.
Attributes (dict) --
The attributes for this group of reservations.
(string) --
(string) --
Utilization (dict) --
How much you used this group of reservations.
UtilizationPercentage (string) --
The percentage of reservation time that you used.
UtilizationPercentageInUnits (string) --
The percentage of Amazon EC2 reservation time that you used, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
PurchasedHours (string) --
How many reservation hours that you purchased.
PurchasedUnits (string) --
How many Amazon EC2 reservation hours that you purchased, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
TotalActualHours (string) --
The total number of reservation hours that you used.
TotalActualUnits (string) --
The total number of Amazon EC2 reservation hours that you used, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
UnusedHours (string) --
The number of reservation hours that you didn't use.
UnusedUnits (string) --
The number of Amazon EC2 reservation hours that you didn't use, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
OnDemandCostOfRIHoursUsed (string) --
How much your reservation would cost if charged On-Demand rates.
NetRISavings (string) --
How much you saved due to purchasing and utilizing reservation. AWS calculates this by subtracting TotalAmortizedFee from OnDemandCostOfRIHoursUsed.
TotalPotentialRISavings (string) --
How much you could save if you use your entire reservation.
AmortizedUpfrontFee (string) --
The upfront cost of your reservation, amortized over the reservation period.
AmortizedRecurringFee (string) --
The monthly cost of your reservation, amortized over the reservation period.
TotalAmortizedFee (string) --
The total cost of your reservation, amortized over the reservation period.
Total (dict) --
The total number of reservation hours that were used.
UtilizationPercentage (string) --
The percentage of reservation time that you used.
UtilizationPercentageInUnits (string) --
The percentage of Amazon EC2 reservation time that you used, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
PurchasedHours (string) --
How many reservation hours that you purchased.
PurchasedUnits (string) --
How many Amazon EC2 reservation hours that you purchased, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
TotalActualHours (string) --
The total number of reservation hours that you used.
TotalActualUnits (string) --
The total number of Amazon EC2 reservation hours that you used, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
UnusedHours (string) --
The number of reservation hours that you didn't use.
UnusedUnits (string) --
The number of Amazon EC2 reservation hours that you didn't use, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
OnDemandCostOfRIHoursUsed (string) --
How much your reservation would cost if charged On-Demand rates.
NetRISavings (string) --
How much you saved due to purchasing and utilizing reservation. AWS calculates this by subtracting TotalAmortizedFee from OnDemandCostOfRIHoursUsed.
TotalPotentialRISavings (string) --
How much you could save if you use your entire reservation.
AmortizedUpfrontFee (string) --
The upfront cost of your reservation, amortized over the reservation period.
AmortizedRecurringFee (string) --
The monthly cost of your reservation, amortized over the reservation period.
TotalAmortizedFee (string) --
The total cost of your reservation, amortized over the reservation period.
Total (dict) --
The total amount of time that you used your RIs.
UtilizationPercentage (string) --
The percentage of reservation time that you used.
UtilizationPercentageInUnits (string) --
The percentage of Amazon EC2 reservation time that you used, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
PurchasedHours (string) --
How many reservation hours that you purchased.
PurchasedUnits (string) --
How many Amazon EC2 reservation hours that you purchased, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
TotalActualHours (string) --
The total number of reservation hours that you used.
TotalActualUnits (string) --
The total number of Amazon EC2 reservation hours that you used, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
UnusedHours (string) --
The number of reservation hours that you didn't use.
UnusedUnits (string) --
The number of Amazon EC2 reservation hours that you didn't use, converted to normalized units. Normalized units are available only for Amazon EC2 usage after November 11, 2017.
OnDemandCostOfRIHoursUsed (string) --
How much your reservation would cost if charged On-Demand rates.
NetRISavings (string) --
How much you saved due to purchasing and utilizing reservation. AWS calculates this by subtracting TotalAmortizedFee from OnDemandCostOfRIHoursUsed.
TotalPotentialRISavings (string) --
How much you could save if you use your entire reservation.
AmortizedUpfrontFee (string) --
The upfront cost of your reservation, amortized over the reservation period.
AmortizedRecurringFee (string) --
The monthly cost of your reservation, amortized over the reservation period.
TotalAmortizedFee (string) --
The total cost of your reservation, amortized over the reservation period.
NextPageToken (string) --
The token for the next set of retrievable results. AWS provides the token when the response from a previous call has more results than the maximum page size.
{'Filter': {'Dimensions': {'Key': {'RIGHTSIZING_TYPE'}}}}
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
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'|'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'|'CACHE_ENGINE'|'INSTANCE_TYPE_FAMILY'|'BILLING_ENTITY'|'RESERVATION_ID'|'RIGHTSIZING_TYPE',
'Values': [
'string',
]
},
'Tags': {
'Key': 'string',
'Values': [
'string',
]
}
},
PredictionIntervalLevel=123
)
dict
[REQUIRED]
The start and end dates of the period that you want to retrieve usage forecast for. The start date is inclusive, but the end date is exclusive. 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.
Start (string) -- [REQUIRED]
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) -- [REQUIRED]
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS retrieves cost and usage data from the start date up to, but not including, 2017-05-01.
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
string
[REQUIRED]
How granular you want the forecast to be. You can get 3 months of DAILY forecasts or 12 months of MONTHLY forecasts.
The GetUsageForecast operation supports only DAILY and MONTHLY granularities.
dict
The filters that you want to use to filter your forecast. Cost Explorer API supports all of the Cost Explorer filters.
Or (list) --
Return results that match either Dimension object.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
And (list) --
Return results that match both Dimension objects.
(dict) --
Use Expression to filter by cost or by usage. There are two patterns:
Simple dimension values - 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. The Expression for that looks like this: { "Dimensions": { "Key": "REGION", "Values": [ "us-east-1", “us-west-1” ] } } The list of dimension values are OR'd together to retrieve cost or usage data. You can create Expression and DimensionValues objects using either with* methods or set* methods in multiple lines.
Compound dimension values with logical operations - You can use multiple Expression types and the logical operators AND/OR/NOT to create a list of one or more Expression objects. This allows you to filter on more advanced options. For example, you can filter on ((REGION == us-east-1 OR REGION == us-west-1) OR (TAG.Type == Type1)) AND (USAGE_TYPE != DataTransfer). The Expression for that looks like this: { "And": [ {"Or": [ {"Dimensions": { "Key": "REGION", "Values": [ "us-east-1", "us-west-1" ] }}, {"Tags": { "Key": "TagName", "Values": ["Value1"] } } ]}, {"Not": {"Dimensions": { "Key": "USAGE_TYPE", "Values": ["DataTransfer"] }}} ] }
Not (dict) --
Return results that don't match a Dimension object.
Dimensions (dict) --
The specific Dimension to use for Expression.
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.
Values (list) --
The metadata values that you can use to filter and group your results. You can use GetDimensionValues to find specific values.
Valid values for the SERVICE dimension are Amazon Elastic Compute Cloud - Compute, Amazon Elasticsearch Service, Amazon ElastiCache, Amazon Redshift, and Amazon Relational Database Service.
(string) --
Tags (dict) --
The specific Tag to use for Expression.
Key (string) --
The key for the tag.
Values (list) --
The specific value of the tag.
(string) --
integer
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.
dict
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. For MONTHLY forecasts, this is a list of months.
(dict) --
The forecast created for your query.
TimePeriod (dict) --
The period of time that the forecast covers.
Start (string) --
The beginning of the time period that you want the usage and costs for. The start date is inclusive. For example, if start is 2017-01-01, AWS retrieves cost and usage data starting at 2017-01-01 up to the end date.
End (string) --
The end of the time period that you want the usage and costs for. The end date is exclusive. For example, if end is 2017-05-01, AWS 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.