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FOCUS is an open specification for billing data. It defines a common
schema for billing data, aligns terminology with the FinOps Framework
and defines a minimum set of requirements for billing data. The
specification provides clear guideline for billing data generators to
produce FinOps-serviceable data. The specification enables FinOps
practitioners to perform common FinOps capabilities such as chargeback,
cost allocation, budgeting and forecasting etc. using a generic set of
instructions, regardless of the origin of the FOCUS compatible
dataset.
Thanks to the following FOCUS Maintainers for their leadership and
contributions to the FOCUS Release v1.2
specification.
Thanks to the following FOCUS members for their contributions to the
FOCUS Release v1.2 specification.
Thanks to the following FOCUS Steering Committee members for their
leadership on the FOCUS specification.
This section is non-normative.
FOCUS is a standards development organization (SDO) formed to
establish an open, consensus-driven standard for billing data. In the
absence of a broadly adopted standard, infrastructure and service providers have relied on
proprietary billing schemas and inconsistent terminology, making cost
data difficult to normalize and act upon across environments. This lack
of conformance has forced FinOps practitioners to develop
best-effort custom normalization schemes for each provider, in order to
perform essential FinOps capabilities such as chargeback, cost
allocation, budgeting and forecasting.
The FOCUS Specification, developed by a global community of
practitioners and vendors, defines a consistent, vendor-neutral approach
to billing data. It is designed to improve interoperability between
providers, reduce operational complexity, and enable greater
transparency in cloud and SaaS cost management.
This project is supported by the FinOps Foundation. This work initially
started under the Open Billing working group under the FinOps
Foundation. The decision was made in Jan 2023 to begin to migrate the
work to a newly formed project under the Linux Foundation called the
FinOps Open Cost and Usage Specification (FOCUS) to better support the
creation of a specification.
This specification is designed to be used by three major groups:
The FOCUS working group will develop an open-source specification for
billing data. The schema will define data dimensions, metrics, a set of attributes about
billing data, and a common lexicon for describing billing data.
The following principles were considered while building the
specification.
The FOCUS Specification is designed to support evolving FinOps needs
across diverse billing models and provider types.
While the initial focus was on billing data from Cloud Service
Providers (CSPs), version 1.2 introduces foundational support for
Software as a Service (SaaS) platforms, including normative columns for
pricing currencies, effective cost, and contracted pricing in
non-monetary units such as credits or tokens.
The specification supports extensibility through structured naming
conventions (e.g., x_ custom columns), conditional requirements, and a
version-aware schema approach.
Future versions of FOCUS will consider including additional FinOps
capabilities such as forecasting, exchange rate modeling, and anomaly
detection, while continuing to support a broader range of billing and
cost datasets — including internal infrastructure platforms and
marketplace offerings.
The keywords “MUST”, “MUST NOT”, “REQUIRED”, “SHALL”, “SHALL NOT”,
“SHOULD”, “SHOULD NOT”, “RECOMMENDED”, “NOT RECOMMENDED”, “MAY”, and
“OPTIONAL” in this specification are to be interpreted as described in
BCP14 [RFC2119][RFC8174] when, and only
when, they appear in all capitals, as shown here.
Under each column defined in the FOCUS specification, there exists a
‘Feature level’ designation that describes the column as ‘Mandatory’,
‘Conditional’, or ‘Optional’. Feature level is designated based on the
following criteria described in the normative requirements in each
column definition:
There are no current resources available to test for specification
conformance or validators to run on sample data. When one becomes
available, this section of the specification will be updated with
details.
The FOCUS specification is designed to meet the needs of FinOps
practitioners in numerous scenarios. The following section contains
features supported by the FOCUS specification. This list does not
represent all possible combinations or use of FOCUS data but does
represent core capabilities that the FOCUS specification supports.
Different providers have different account constructs that FinOps
practitioners use for allocation, reporting, and more. Organizations may
have one or many accounts within one or more providers and FinOps
practitioners may need to review the cost broken down by each account.
FOCUS has two types of accounts: a billing account and a sub
account.
A billing account is the account where invoices are generated. Each
billing account can have one or more sub accounts, which can be used for
deploying and managing resources and services. Billing and sub accounts
are often used to facilitate allocation strategies and FinOps
practitioners must be able to break costs down by billing and sub
account to facilitate FinOps scenarios like chargeback and
budgeting.
SELECT
BillingAccountId,
BillingAccountName,
BillingAccountType,
SubAccountId,
SubAccountName,
SubAccountType,
SUM(BilledCost)
FROM focus_data_table
WHERE BillingPeriodStart >= ? AND BillingPeriodEnd < ?
GROUP BY
BillingAccountId,
SubAccountId
FOCUS data should be consistent with the costs indicated on payable
invoices. This is relevant to the total cost of the invoice, as well as
the period of time the invoice covers.
SELECT
BillingPeriodStart,
BillingPeriodEnd,
InvoiceId,
SUM(BilledCost)
FROM focus_data_table
GROUP BY
BillingPeriodStart,
BillingPeriodEnd,
InvoiceId
FOCUS supports the categorization of charges including purchases,
usage, tax, credits and adjustments. It includes classification on
frequency. It includes classification on correction vs normal
entries
SELECT
MIN(ChargePeriodStart) AS ChargePeriodStart,
MAX(ChargePeriodEnd) AS ChargePeriodEnd,
ProviderName,
BillingAccountId,
CommitmentDiscountId,
CommitmentDiscountType,
CommitmentDiscountUnit,
CommitmentDiscountQuantity,
ChargeFrequency,
SUM(BilledCost) AS TotalBilledCost
FROM focus_data_table
WHERE ChargePeriodStart >= ? AND ChargePeriodEnd < ?
AND ChargeCategory = 'Purchase'
AND CommitmentDiscountId IS NOT NULL
GROUP BY
ProviderName,
BillingAccountId,
CommitmentDiscountId,
CommitmentDiscountType,
CommitmentDiscountUnit,
CommitmentDiscountQuantity,
ChargeFrequency
SELECT
ProviderName,
BillingAccountId,
ChargeCategory,
ServiceCategory,
ServiceName,
SUM(BilledCost) AS TotalBilledCost
FROM focus_data_table
WHERE BillingPeriodStart >= ? AND BillingPeriodEnd < ?
AND ChargeClass = 'Correction'
GROUP BY
ProviderName,
BillingAccountId,
ChargeCategory,
ServiceCategory,
ServiceName
SELECT
BillingPeriodStart,
CommitmentDiscountId,
CommitmentDiscountName,
CommitmentDiscountType,
ChargeFrequency,
SUM(BilledCost) AS TotalBilledCost
FROM focus_data_table
WHERE BillingPeriodStart >= ? AND BillingPeriodStart < ?
AND ChargeFrequency = 'Recurring'
AND CommitmentDiscountId IS NOT NULL
GROUP BY
BillingPeriodStart,
CommitmentDiscountId,
CommitmentDiscountName,
CommitmentDiscountType,
ChargeFrequency
FOCUS supports the tracking of commitment discounts usage and under
usage, which can come in the form of commitment discounts or capacity
reservations.
SELECT
ProviderName,
BillingAccountId,
CommitmentDiscountId,
CommitmentDiscountType,
CommitmentDiscountStatus,
SUM(BilledCost) AS TotalBilledCost,
SUM(EffectiveCost) AS TotalEffectiveCost
FROM focus_data_table
WHERE ChargePeriodStart >= ? AND ChargePeriodEnd < ?
AND CommitmentDiscountStatus = 'Unused'
GROUP BY
ProviderName,
BillingAccountId,
CommitmentDiscountId,
CommitmentDiscountType
SELECT
ProviderName,
BillingAccountId,
CapacityReservationId,
CapacityReservationStatus,
SUM(BilledCost) AS TotalBilledCost,
SUM(EffectiveCost) AS TotalEffectiveCost
FROM focus_data_table
WHERE ChargePeriodStart >= ? AND ChargePeriodEnd < ?
AND CapacityReservationStatus = 'Unused'
GROUP BY
ProviderName,
BillingAccountId,
CapacityReservationId,
CapacityReservationStatus
Many providers have features that allow Finops practitioners to
enrich cost and usage data with metadata, that is addition to provider
defined data, in order to analyze Finops data using organizational,
deployment, or other structures. These features may take the form of
directly applied metadata or inherited metadata. FOCUS facilitates the
inclusion of this metadata at a row level.
SELECT
tags,
ConsumedUnit,
SUM(BilledCost),
SUM(EffectiveCost),
SUM(ConsumedQuantity)
FROM focus_data_table
WHERE BillingPeriodStart >= ? AND BillingPeriodEnd < ?
GROUP BY
tags,
ConsumedUnit
FOCUS supports the comparison of cost columns in order to identify
savings, amortization, or other constructs.
WITH AggregatedData AS (
SELECT
ProviderName,
BillingAccountId,
BillingAccountName,
BillingCurrency,
ServiceName,
SUM(EffectiveCost) AS TotalEffectiveCost,
SUM(BilledCost) AS TotalBilledCost,
SUM(CASE
WHEN ChargeCategory = 'Usage' AND BilledCost = 0 AND EffectiveCost != 0
THEN 0
ELSE ContractedCost
END) AS TotalContractedCost,
SUM(CASE
WHEN ChargeCategory = 'Usage' AND BilledCost = 0 AND EffectiveCost != 0
THEN 0
ELSE ListCost
END) AS TotalListCost
FROM focus_data_table
WHERE BillingPeriodStart >= ?
AND BillingPeriodEnd < ?
AND ChargeClass IS NULL
GROUP BY
ProviderName,
BillingAccountId,
BillingAccountName,
BillingCurrency,
ServiceName
)
SELECT ProviderName,
BillingAccountId,
BillingAccountName,
BillingCurrency,
ServiceName,
TotalEffectiveCost,
TotalBilledCost,
TotalListCost,
1 - (TotalContractedCost / NULLIF(TotalListCost, 0)) * 100 AS ContractedDiscount
1 - (TotalEffectiveCost / NULLIF(TotalListCost, 0)) * 100 AS EffectiveDiscount
FROM AggregatedData
FOCUS supports the inclusion of custom columns to facilitate
reporting capability that is not covered by the columns included in the
specification.
SELECT
BillingPeriodStart,
x_CustomColumn,
SUM(BilledCost) AS TotalBilledCost,
FROM focus_data_table
WHERE ServiceName = ?
AND BillingPeriodStart >= ? AND BillingPeriodStart < ?
GROUP BY
BillingPeriodStart,
x_CustomColumn
ORDER BY MonthlyCost DESC
FOCUS supports multiple levels of cost and usage data granularity.
This includes the ability to report on a daily, hourly, or other time
period basis. FOCUS also supports the ability for cost and usage data to
be provided for high granularity scenarios, such as down to the
individual resources. It also supports high level granularity cost and
usage data, such as account level, or service level charges.
SELECT
ChargePeriodStart,
ChargePeriodEnd,
ResourceId,
SUM(EffectiveCost)
FROM focus_data_table
Group by
ChargePeriodStart,
ChargePeriodEnd,
ResourceId
FOCUS enables practitioners to analyze costs without having to
distribute upfront fees and discounts, taking discounts and the
amortization of upfront fees paid for services into account. The
EffectiveCost column represents cost after negotiated discounts,
commitment discounts, and the applicable portion of relevant, prepaid
purchases (one-time or recurring) that covered this charge.
EffectiveCost is commonly utilized to track and analyze spending
trends.
SELECT
ProviderName,
BillingPeriodStart,
BillingPeriodEnd,
ServiceCategory,
ServiceName,
RegionId,
RegionName,
PricingUnit,
SUM(EffectiveCost) AS TotalEffectiveCost,
SUM(PricingQuantity) AS TotalPricingQuantity
FROM focus_data_table
WHERE BillingPeriodStart >= ? AND BillingPeriodEnd <= ?
GROUP BY
ProviderName,
BillingPeriodStart,
BillingPeriodEnd,
ServiceCategory,
ServiceName,
RegionId,
RegionName,
PricingUnit
FOCUS provides structured location data through region and
availability zone information. By documenting geographic deployment
locations, practitioners can organize and analyze costs based on where
resources and services are deployed. This standardized location data
helps practitioners understand the geographical distribution of
infrastructure across providers.
SELECT
RegionId,
RegionName,
AvailabilityZone,
SUM(BilledCost) AS TotalBilledCost
FROM focus_data_table
WHERE ChargePeriodStart >= ? AND ChargePeriodEnd <= ?
GROUP BY
RegionId,
RegionName,
AvailabilityZone
FOCUS supports the analysis of cost and usage data for marketplace
purchases and their associated costs. It also supports the reporting of
EffectiveCost for usage from the provider.
SELECT
Provider,
InvoiceIssuer,
BillingPeriodStart,
BillingPeriodEnd,
SUM(BilledCost) AS TotalBilledCost
FROM focus_data_table
WHERE Provider = '<Example SaaS Provider>'
AND InvoiceIssuer = '<Example CSP Marketplace>'
GROUP BY
Provider,
InvoiceIssuer,
BillingPeriodStart,
BillingPeriodEnd
SELECT
ChargePeriodStart,
ChargePeriodEnd,
ResourceId,
SUM(EffectiveCost) AS TotalEffectiveCost
FROM focus_data_table
WHERE InvoiceIssuer = '<Example CSP Marketplace>'
GROUP BY
ChargePeriodStart,
ChargePeriodEnd,
ResourceId
FOCUS supports providers specifying the services and product
offerings that they provide their customers that align with the names
practitioners are familiar with. This empowers practitioners to analyze
cost by service, report service costs by subaccount, forecast based on
historical trends by service, and verify accuracy of services charged
across providers.
SELECT
BillingPeriodStart,
ProviderName,
SubAccountId,
SubAccountName,
ServiceName,
SUM(BilledCost) AS TotalBilledCost,
SUM(EffectiveCost) AS TotalEffectiveCost
FROM focus_data_table
WHERE ServiceName = ?
AND BillingPeriodStart >= ? AND BillingPeriodStart < ?
GROUP BY
BillingPeriodStart,
ProviderName,
SubAccountId,
SubAccountName,
ServiceName
ORDER BY MonthlyCost DESC
FOCUS enables tracking of resource consumption by providing
information about which resources were used, in what quantities, and
with what units of measure.
SELECT
ProviderName,
ServiceName,
ResourceId,
SkuId,
ConsumedUnit,
SUM(ConsumedQuantity) AS TotalQuantity
FROM focus_data_table
WHERE ChargeCategory='Usage'
AND ChargePeriodStart >= ? AND ChargePeriodEnd <= ?
GROUP BY
ProviderName,
ServiceName,
ResourceId,
SkuId,
ConsumedUnit
FOCUS’ schema metadata supports communication of important attributes
about the data, facilitating notifications about changing structure and
database table creation between provider and consumer. This includes
column names, data types, and any other relevant information about the
data schema. It also includes information as to the version of FOCUS and
Data Generator versioning that the data uses.
FOCUS provides a structure for categorizing services based on their
core functions. By classifying services into high-level categories and
more granular subcategories, practitioners can organize costs according
to functional areas. This standardized categorization provides data that
practitioners can use in their cost management processes and decision
making.
SELECT
BillingPeriodStart,
BillingPeriodEnd,
ProviderName,
ServiceCategory,
ServiceSubcategory,
ServiceName,
BillingCurrency,
SUM(BilledCost) AS TotalBilledCost
FROM focus_data_table
WHERE BillingPeriodStart >= ? and BillingPeriodEnd < ?
GROUP BY
BillingPeriodStart,
BillingPeriodEnd,
ProviderName,
ServiceCategory,
ServiceSubcategory,
ServiceName,
BillingCurrency
When a provider supports unit pricing concepts, FOCUS allows
practitioners to:
SELECT DISTINCT
SkuId,
SkuPriceId,
SkuPriceDetails,
BillingPeriodId,
ChargePeriodStart,
ChargePeriodEnd,
BillingCurrency,
ListUnitPrice,
ContractedUnitPrice
FROM focus_data_table
WHERE
SkuPriceId = ?
AND ChargePeriodStart >= ?
AND ChargePeriodEnd < ?
1.0
The FOCUS specification defines a group of columns that provide
qualitative values (such as dates, resource, and provider information)
categorized as “dimensions” and quantitative values (numeric values)
categorized as “metrics” that can be used for performing various FinOps
capabilities. Metrics are commonly used for aggregations (sum,
multiplication, averaging etc.) and statistical operations within the
dataset. Dimensions are commonly used to categorize, filter, and reveal
details in your data when combined with metrics. The Columns are
presented in Alphabetical order.
An availability
zone is a provider-assigned identifier for a physically
separated and isolated area within a Region that provides high
availability and fault tolerance. Availability Zone is commonly used for
scenarios like analyzing cross-zone data transfer usage and the
corresponding cost based on where resources are deployed.
The AvailabilityZone column adheres to the following
requirements:
AvailabilityZone
Availability Zone
A provider-assigned identifier for a physically separated and
isolated area within a Region that provides high availability and fault
tolerance.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Recommended |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
The billed cost
represents a charge serving as
the basis for invoicing, inclusive of the impacts of all reduced rates
and discounts while excluding the amortization of relevant
purchases (one-time or recurring) paid to cover future eligible
charges. This cost is denominated in the Billing Currency. The Billed Cost is
commonly used to perform FinOps capabilities that require cash-basis
accounting such as cost allocation, budgeting, and invoice
reconciliation.
The BilledCost column adheres to the following requirements:
BilledCost
Billed Cost
A charge serving as the basis for invoicing, inclusive of
all reduced rates and discounts while excluding the
amortization of upfront charges (one-time or
recurring).
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Mandatory |
Allows nulls | False |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid decimal value |
A Billing Account ID is a provider-assigned identifier for a billing account.
Billing accounts are commonly used for scenarios like grouping
based on organizational constructs, invoice reconciliation and cost
allocation strategies.
The BillingAccountId column adheres to the following
requirements:
See Appendix:
Grouping constructs for resources or services for details and
examples of the different grouping constructs supported by FOCUS.
BillingAccountId
Billing Account ID
The identifier assigned to a billing account by the
provider.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
A Billing Account Name is a display name assigned to a billing account.
Billing accounts are commonly used for scenarios like grouping
based on organizational constructs, invoice reconciliation and cost
allocation strategies.
The BillingAccountName column adheres to the following
requirements:
See Appendix:
Grouping constructs for resources or services for details and
examples of the different grouping constructs supported by FOCUS.
BillingAccountName
Billing Account Name
The display name assigned to a billing account.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
Billing Account Type is a provider-assigned name to identify the type
of billing account.
Billing Account Type is a readable display name and not a code. Billing
Account Type is commonly used for scenarios like mapping FOCUS and
provider constructs, summarizing costs across providers, or invoicing
and chargeback.
The BillingAccountType column adheres to the following
requirements:
BillingAccountType
Billing Account Type
A provider-assigned name to identify the type of billing
account.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
Billing currency is
an identifier that represents the currency that a charge for resources or services was billed in. Billing
Currency is commonly used in scenarios where costs need to be grouped or
aggregated.
The BillingCurrency column adheres to the following requirements:
BillingCurrency
Billing Currency
Represents the currency that a charge was billed in.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | Currency Format |
Billing Period End represents the exclusive end bound of a
billing period. For
example, a time period where Billing
Period Start is ‘2024-01-01T00:00:00Z’ and Billing Period End is
‘2024-02-01T00:00:00Z’ includes charges for January since Billing
Period Start represents the inclusive start bound,
but does not include charges for February since Billing Period
End represents the exclusive end bound.
The BillingPeriodEnd column adheres to the following
requirements:
BillingPeriodEnd
Billing Period End
The exclusive end bound of a billing period.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | Date/Time |
Value format | Date/Time Format |
Billing Period Start represents the inclusive start bound
of a billing period. For
example, a time period where Billing Period Start is
‘2024-01-01T00:00:00Z’ and Billing Period
End is ‘2024-02-01T00:00:00Z’ includes charges for January since Billing
Period Start represents the inclusive start bound, but does not
include charges for February since BillingPeriodEnd represents
the exclusive end
bound.
The BillingPeriodStart column adheres to the following
requirements:
BillingPeriodStart
Billing Period Start
The inclusive start bound of a billing period.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | Date/Time |
Value format | Date/Time Format |
A Capacity Reservation ID is the identifier assigned to a capacity reservation
by the provider. Capacity Reservation ID is commonly used for scenarios
to allocate charges for capacity
reservation usage.
The CapacityReservationId column adheres to the following
requirements:
CapacityReservationId
Capacity Reservation ID
The identifier assigned to a capacity reservation by the
provider.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
Capacity Reservation Status indicates whether the charge represents either the
consumption of the capacity
reservation identified in the CapacityReservationId column or
when the capacity reservation is unused.
The CapacityReservationStatus column adheres to the following
requirements:
CapacityReservationStatus
Capacity Reservation Status
Indicates whether the charge represents either the
consumption of a capacity reservation or when a capacity
reservation is unused.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | Allowed Values |
Allowed values:
Value | Description |
---|---|
Used | Charges that utilized a specific amount of a capacity reservation. |
Unused | Charges that represent the unused portion of a capacity reservation. |
Charge Category represents the highest-level classification of a charge based on the nature of how
it is billed. Charge Category is commonly used to identify and
distinguish between types of charges that may require different
handling.
The ChargeCategory column adheres to the following requirements:
ChargeCategory
Charge Category
Represents the highest-level classification of a charge
based on the nature of how it is billed.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | Allowed values |
Allowed values:
Value | Description |
---|---|
Usage | Positive or negative charges based on the quantity of a service or resource that was consumed over a given period of time including refunds. |
Purchase | Positive or negative charges for the acquisition of a service or resource bought upfront or on a recurring basis including refunds. |
Tax | Positive or negative applicable taxes that are levied by the relevant authorities including refunds. Tax charges may vary depending on factors such as the location, jurisdiction, and local or federal regulations. |
Credit | Positive or negative charges granted by the provider for various scenarios e.g promotional credits or corrections to promotional credits. |
Adjustment | Positive or negative charges the provider applies that do not fall into other category values. |
Charge Class indicates whether the row represents a correction to a
previously invoiced billing
period. Charge Class is commonly used to differentiate *corrections from regularly incurred charges.
The ChargeClass column adheres to the following requirements:
ChargeClass
Charge Class
Indicates whether the row represents a correction to a
previously invoiced billing period.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | True |
Data type | String |
Value format | Allowed values |
Allowed values:
Value | Description |
---|---|
Correction | Correction to a previously invoiced billing period (e.g., refunds and credit modifications). |
A Charge Description provides a high-level context of a row without requiring additional
discovery. This column is a self-contained summary of the charge’s purpose and price. It
typically covers a select group of corresponding details across a
billing dataset or provides information not otherwise available.
The ChargeDescription column adheres to the following
requirements:
ChargeDescription
Charge Description
Self-contained summary of the charge’s purpose and
price.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
Charge Frequency indicates how often a charge will occur. Along with the
charge period related columns, the
Charge Frequency is commonly used to understand recurrence periods
(e.g., monthly, yearly), forecast upcoming charges, and
differentiate between one-time and recurring fees for purchases.
The ChargeFrequency column adheres to the following requirements:
ChargeFrequency
Charge Frequency
Indicates how often a charge will occur.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Recommended |
Allows nulls | False |
Data type | String |
Value format | Allowed values |
Allowed values:
Value | Description |
---|---|
One-Time | Charges that only happen once and will not repeat. One-time charges are typically recorded on the hour or day when the cost was incurred. |
Recurring | Charges that repeat on a periodic cadence (e.g., weekly, monthly) regardless of whether the product or service was used. Recurring charges typically happen on the same day or point within every period. The charge date does not change based on how or when the service is used. |
Usage-Based | Charges that repeat every time the service is used. Usage-based charges are typically recorded hourly or daily, based on the granularity of the cost data for the period when the service was used (referred to as charge period). Usage-based charges are not recorded when the service is not used. |
Charge Period End represents the exclusive end bound of a
charge period. For
example, a time period where Charge Period
Start is ‘2024-01-01T00:00:00Z’ and Charge Period End is
‘2024-01-02T00:00:00Z’ includes charges for January 1 since Charge
Period Start represents the inclusive start bound,
but does not include charges for January 2 since Charge Period
End represents the exclusive end bound.
The ChargePeriodEnd column adheres to the following requirements:
ChargePeriodEnd
Charge Period End
The exclusive end bound of a charge period.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | Date/Time |
Value format | Date/Time Format |
Charge Period Start represents the inclusive start bound
of a charge period. For
example, a time period where Charge Period Start is
‘2024-01-01T00:00:00Z’ and Charge Period
End is ‘2024-01-02T00:00:00Z’ includes charges for January 1 since Charge
Period Start represents the inclusive start bound, but does not
include charges for January 2 since Charge Period End
represents the exclusive end
bound.
The ChargePeriodStart column adheres to the following
requirements:
ChargePeriodStart
Charge Period Start
The inclusive start bound of a charge period.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | Date/Time |
Value format | Date/Time Format |
Commitment Discount Category indicates whether the commitment discount
identified in the CommitmentDiscountId column is based on usage quantity
or cost (aka “spend”). The CommitmentDiscountCategory column is only
applicable to commitment discounts and not negotiated
discounts.
The CommitmentDiscountCategory column adheres to the following
requirements:
CommitmentDiscountCategory
Commitment Discount Category
Indicates whether the commitment discount identified in the
CommitmentDiscountId column is based on usage quantity or cost (aka
“spend”).
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | Allowed Values |
Allowed values:
Value | Description |
---|---|
Spend | Commitment discounts that require a predetermined amount of spend. |
Usage | Commitment discounts that require a predetermined amount of usage. |
A Commitment Discount ID is the identifier assigned to a commitment discount by
the provider. Commitment Discount ID is commonly used for scenarios like
chargeback for commitments and savings per commitment
discount. The CommitmentDiscountId column is only applicable to
commitment discounts and not negotiated
discounts.
The CommitmentDiscountId column adheres to the following
requirements:
CommitmentDiscountId
Commitment Discount ID
The identifier assigned to a commitment discount by the
provider.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
A Commitment Discount Name is the display name assigned to a commitment discount.
The CommitmentDiscountName column is only applicable to commitment
discounts and not negotiated
discounts.
The CommitmentDiscountName column adheres to the following
requirements:
CommitmentDiscountName
Commitment Discount Name
The display name assigned to a commitment discount.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
Commitment Discount Quantity is the amount of a commitment discount
purchased or accounted for in commitment discount related rows that is denominated in Commitment Discount Units. The
aggregated Commitment Discount Quantity across purchase records,
pertaining to a particular Commitment
Discount ID during its term,
represents the total Commitment Discount Units acquired with that
commitment discount. For committed usage, the Commitment Discount
Quantity is either the number of Commitment Discount Units consumed by a
row that is covered by a commitment discount or is the
unused portion of a commitment discount over a charge period. Commitment
Discount Quantity is commonly used in commitment discount
analysis and optimization use cases and only applies to commitment
discounts, not negotiated
discounts.
When CommitmentDiscountCategory is
“Usage” (usage-based commitment discounts), the Commitment
Discount Quantity reflects the predefined amount of usage purchased or
consumed. If commitment discount
flexibility is applicable, this value may be further
transformed based on additional, provider-specific requirements. When
CommitmentDiscountCategory is “Spend” (spend-based commitment
discounts), the Commitment Discount Quantity reflects the
predefined amount of spend purchased or consumed. See Appendix: Commitment Discount
Flexibility for more details around commitment discount
flexibility.
The CommitmentDiscountQuantity column adheres to the following
requirements:
CommitmentDiscountQuantity
Commitment Discount Quantity
The amount of a commitment discount purchased or accounted
for in commitment discount related rows that is
denominated in Commitment Discount Units.
Aggregation: When aggregating Commitment Discount
Quantity for commitment utilization calculations, it’s important to
exclude commitment
discount purchases (i.e. when Charge Category is “Purchase”)
that are paid to cover future eligible charges (e.g., commitment
discount). Otherwise, when accounting for all upfront or accrued
purchases, it’s important to exclude commitment discount usage
(i.e. when Charge Category is “Usage”). This exclusion helps prevent
double counting of these quantities in the aggregation.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Conditional |
Allows nulls | True |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid decimal value |
Commitment Discount Status indicates whether the charge corresponds with the
consumption of a commitment
discount identified in the CommitmentDiscountId column or the
unused portion of the committed amount. The CommitmentDiscountStatus
column is only applicable to commitment discounts and not negotiated
discounts.
The CommitmentDiscountStatus column adheres to the following
requirements:
CommitmentDiscountStatus
Commitment Discount Status
Indicates whether the charge corresponds with the
consumption of a commitment discount or the unused portion of
the committed amount.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | Allowed Values |
Allowed values:
Value | Description |
---|---|
Used | Charges that utilized a specific amount of a commitment discount. |
Unused | Charges that represent the unused portion of the commitment discount. |
Commitment Discount Type is a provider-assigned name to identify the
type of commitment
discount applied to the row. The CommitmentDiscountType column
is only applicable to commitment discounts and not negotiated
discounts.
The CommitmentDiscountType column adheres to the following
requirements:
CommitmentDiscountType
Commitment Discount Type
A provider-assigned identifier for the type of commitment
discount applied to the row.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
Commitment Discount Unit represents the provider-specified
measurement unit indicating how a provider measures the Commitment Discount Quantity of a
commitment
discount. The CommitmentDiscountUnit column is only applicable
to commitment discounts and not negotiated
discounts.
The CommitmentDiscountUnit column adheres to the following
requirements:
See Examples: Commitment
Discount Flexibility for more details around commitment discount
flexibility.
CommitmentDiscountUnit
Commitment Discount Unit
The provider-specified measurement unit indicating how a provider
measures the Commitment Discount Quantity of a commitment
discount.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | Unit Format |
The Consumed Quantity represents the volume of a metered SKU
associated with a resource or
service used, based on the Consumed Unit. Consumed Quantity is often
derived at a finer granularity or over a different time interval when
compared to the Pricing Quantity
(complementary to Pricing Unit) and focuses
on resource and service consumption, not pricing and
cost.
The ConsumedQuantity column adheres to the following
requirements:
ConsumedQuantity
Consumed Quantity
The volume of a metered SKU associated with a resource or
service used, based on the Consumed Unit.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Conditional |
Allows nulls | True |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid decimal value |
The Consumed Unit represents a provider-specified measurement unit
indicating how a provider measures usage of a metered SKU associated
with a resource or service. Consumed Unit complements
the Consumed Quantity metric. It is
often listed at a finer granularity or over a different time interval
when compared to Pricing Unit (complementary
to Pricing Quantity), and focuses on
resource and service consumption, not pricing and
cost.
The ConsumedUnit column adheres to the following requirements:
ConsumedUnit
Consumed Unit
Provider-specified measurement unit indicating how a provider
measures usage of a metered SKU associated with a resource or
service.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | Unit Format recommended |
Contracted Cost represents the cost calculated by multiplying contracted unit
price and the corresponding Pricing
Quantity. Contracted Cost is denominated in the Billing Currency and is commonly used for
calculating savings based on negotiation activities, by comparing it
with List Cost. If negotiated discounts
are not applicable, the Contracted Cost defaults to the List Cost.
The ContractedCost column adheres to the following requirements:
ContractedCost
Contracted Cost
Cost calculated by multiplying contracted unit price and the
corresponding Pricing Quantity.
Aggregation: When aggregating Contracted Cost for
savings calculations, it’s important to exclude either Charge Category “Purchase” charges
(one-time and recurring) that are paid to cover future eligible
charges (e.g., commitment discount) or the
covered Charge Category “Usage”
charges themselves. This exclusion helps prevent double
counting of these charges in the aggregation. Which set of
charges to exclude depends on whether cost are aggregated on a
billed basis (exclude covered charges) or accrual basis
(exclude Purchases for future charges). For instance,
charges categorized as Charge
Category “Purchase” and their related Charge Category “Tax” charges for a
Commitment Discount might be excluded from an accrual basis cost
aggregation of Contracted Cost. This is because the “Usage” and “Tax”
charge records provided during the term of the commitment discount
already specify the Contracted Cost. Purchase charges that
cover future eligible charges can be identified by filtering
for Charge Category “Purchase” records
with a Billed Cost greater than 0 and an Effective Cost equal to 0.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Mandatory |
Allows nulls | False |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid decimal value |
The Contracted Unit Price represents the agreed-upon unit price for a
single Pricing Unit of the associated SKU,
inclusive of negotiated
discounts, if present, while excluding negotiated commitment discounts
or any other discounts. This price is denominated in the Billing Currency. The Contracted Unit Price
is commonly used for calculating savings based on negotiation
activities. If negotiated discounts are not applicable, the Contracted
Unit Price defaults to the List Unit
Price.
The ContractedUnitPrice column adheres to the following
requirements:
ContractedUnitPrice
Contracted Unit Price
The agreed-upon unit price for a single Pricing Unit of the
associated SKU, inclusive of negotiated discounts, if present, while
excluding negotiated commitment discounts or any other discounts.
Aggregation: Column values should only be viewed in
the context of their row and not aggregated to produce a total.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Conditional |
Allows nulls | True |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid non-negative decimal value |
Effective Cost represents the amortized cost of the charge after applying all reduced
rates, discounts, and the applicable portion of relevant, prepaid
purchases (one-time or recurring) that covered this charge. The
amortized portion included should be proportional to the Pricing Quantity and the time granularity of
the data. Since amortization breaks down and spreads the cost of a
prepaid purchase, to subsequent eligible charges, the Effective
Cost of the original prepaid charge is set to 0. Effective Cost
does not mix or “blend” costs across multiple charges of the
same service. This cost is
denominated in the Billing Currency. The
Effective Cost is commonly utilized to track and analyze spending
trends.
This column resolves two challenges that are faced by
practitioners:
The EffectiveCost column adheres to the following requirements:
EffectiveCost
Effective Cost
The amortized cost of the charge after applying all
reduced rates, discounts, and the applicable portion of relevant,
prepaid purchases (one-time or recurring) that covered this
charge.
Providers should distribute the commitment purchase amount
instead of including a row at the beginning of a period so
practitioners do not need to manually distribute the fee themselves.
Eligible purchases should be amortized using a methodology
determined by the provider that reflects the needs of their customer
base and is proportional to the Pricing Quantity and the time
granularity of the row. Should a practitioner desire to
amortize relevant purchases using a different approach, the
practitioner can do so using the Billed Cost
for the line item representing the initial purchase.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Mandatory |
Allows nulls | False |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid decimal value |
An Invoice ID is a provider-assigned identifier for an invoice
encapsulating some or all charges in the corresponding billing period for a given
billing account.
Invoices are commonly used for scenarios like tracking billing
transactions, facilitating payment processes and for performing invoice
reconciliation between charges and billing periods.
The InvoiceId column adheres to the following requirements:
See Appendix:
Grouping constructs for resources or services for details and
examples of the different grouping constructs supported by FOCUS.
InvoiceId
Invoice ID
The provider-assigned identifier for an invoice encapsulating some or
all charges in the corresponding billing period for a given
billing account.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Recommended |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
An Invoice Issuer is an entity responsible for issuing payable
invoices for the resources or
services consumed. It is
commonly used for cost analysis and reporting scenarios.
The InvoiceIssuerName column adheres to the following
requirements:
See Appendix: Origination of cost
data section for examples of Provider, Publisher and Invoice Issuer values that can be
used for various purchasing scenarios.
InvoiceIssuerName
Invoice Issuer
The name of the entity responsible for invoicing for the
resources or services consumed.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
List Cost represents the cost calculated by multiplying the list unit price and the
corresponding Pricing Quantity. List Cost
is denominated in the Billing Currency
and is commonly used for calculating savings based on various rate
optimization activities by comparing it with Contracted Cost, Billed
Cost and Effective Cost.
The ListCost column adheres to the following requirements:
ListCost
List Cost
Cost calculated by multiplying List Unit Price and the corresponding
Pricing Quantity.
Aggregation: When aggregating List Cost for savings
calculations, it’s important to exclude either Charge Category “Purchase” charges
(one-time and recurring) that are paid to cover future eligible
charges (e.g., commitment discount) or the
covered Charge Category “Usage”
charges themselves. This exclusion helps prevent double
counting of these charges in the aggregation. Which set of
charges to exclude depends on whether cost are aggregated on a
billed basis (exclude covered charges) or accrual basis
(exclude Purchases for future charges). For instance,
charges categorized as Charge
Category “Purchase” and their related Charge Category “Tax” charges for a
Commitment Discount might be excluded from an accrual basis cost
aggregation of List Cost. This is because the “Usage” and “Tax” charge
records provided during the term of the commitment discount already
specify the List Cost. Purchase charges that cover future
eligible charges can be identified by filtering for Charge Category “Purchase” records with a Billed Cost greater than 0 and an Effective Cost equal to 0.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Mandatory |
Allows nulls | False |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid decimal value |
The List Unit Price represents the suggested provider-published unit
price for a single Pricing Unit of the
associated SKU, exclusive of any discounts. This price is denominated in
the Billing Currency. The List Unit Price
is commonly used for calculating savings based on various rate
optimization activities.
The ListUnitPrice column adheres to the following requirements:
ListUnitPrice
List Unit Price
The suggested provider-published unit price for a single Pricing Unit
of the associated SKU, exclusive of any discounts.
Aggregation: Column values should only be viewed in
the context of their row and not aggregated to produce a total.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Conditional |
Allows nulls | True |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid non-negative decimal value |
Pricing Category describes the pricing model used for a charge at the time of use or
purchase. It can be useful for distinguishing between charges
incurred at the list unit
price or a reduced price and exposing optimization
opportunities, like increasing commitment discount
coverage.
The PricingCategory column adheres to the following requirements:
PricingCategory
Pricing Category
Describes the pricing model used for a charge at the time of
use or purchase.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | Allowed values |
Allowed values:
Value | Description |
---|---|
Standard | Charges priced at the agreed upon rate for the billing account, including negotiated discounts. This pricing includes any flat rate and volume/tiered pricing but does not include dynamic pricing or reduced pricing due to the application of a commitment discount. This does include the purchase of a commitment discount at agreed upon rates. |
Dynamic | Charges priced at a variable rate determined by the provider. This includes any product or service with a unit price the provider can change without notice, like interruptible or low priority resources. |
Committed | Charges with reduced pricing due to the application of the commitment discount specified by the Commitment Discount ID. |
Other | Charges priced in a way not covered by another pricing category. |
Pricing Currency is
the national or virtual currency denomination that a resource or service was priced in. Pricing
Currency is commonly used in scenarios where different currencies are
used for pricing and billing.
The PricingCurrency column adheres to the following requirements:
PricingCurrency
Pricing Currency
The national or virtual currency denomination that a
resource or service was priced in.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | Currency Format |
The Pricing Currency Contracted Unit Price represents the agreed-upon
unit price for a single Pricing Unit of the
associated SKU, inclusive of negotiated discounts,
if present, while excluding negotiated commitment discounts
or any other discounts. This price is denominated in the Pricing Currency. When negotiated discounts
do not apply to unit prices and instead are applied to exchange rates,
the Pricing Currency Contracted Unit Price defaults to the Pricing Currency List Unit
Price. The Pricing Currency Contracted Unit Price is commonly used
to calculate savings based on negotiation activities.
The PricingCurrencyContractedUnitPrice column adheres to the
following requirements:
PricingCurrencyContractedUnitPrice
Pricing Currency Contracted Unit Price
The agreed-upon unit price for a single Pricing Unit of the
associated SKU, inclusive of negotiated discounts, if present,
while excluding negotiated commitment discounts or any other
discounts, and expressed in Pricing Currency.
Aggregation: Column values should only be viewed in
the context of their row and not aggregated to produce a total.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Conditional |
Allows nulls | True |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid non-negative decimal value |
The Pricing Currency Effective Cost represents the cost of the charge after applying all reduced
rates, discounts, and the applicable portion of relevant, prepaid
purchases (one-time or recurring) that covered this charge, as
denominated in Pricing Currency. This
allows the practitioner to perform a conversion from either 1) a national currency to a virtual currency (e.g.,
tokens to USD), or 2) one national currency to another (e.g., EUR to
USD).
The PricingCurrencyEffectiveCost column adheres to the following
requirements:
PricingCurrencyEffectiveCost
Pricing Currency Effective Cost
The cost of the charge after applying all reduced rates,
discounts, and the applicable portion of relevant, prepaid purchases
(one-time or recurring) that covered this charge, as
denominated in Pricing Currency.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Conditional |
Allows nulls | True |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid decimal value |
The Pricing Currency List Unit Price represents the suggested
provider-published unit price for a single Pricing Unit of the associated SKU, exclusive of any discounts. This
price is denominated in the Pricing
Currency. The Pricing Currency List Unit Price is commonly used for
calculating savings based on various rate optimization activities.
The PricingCurrencyListUnitPrice column adheres to the following
requirements:
PricingCurrencyListUnitPrice
Pricing Currency List Unit Price
The suggested provider-published unit price for a single Pricing Unit
of the associated SKU, exclusive of any discounts and expressed
in Pricing Currency.
Aggregation: Column values should only be viewed in
the context of their row and not aggregated to produce a total.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Conditional |
Allows nulls | True |
Data type | Decimal |
Value format | Numeric Format |
Number range | Any valid non-negative decimal value |
The Pricing Quantity represents the volume of a given SKU associated with a resource or service used or purchased, based
on the Pricing Unit. Distinct from Consumed Quantity (complementary to Consumed Unit), it focuses on pricing and cost,
not resource and service consumption.
The PricingQuantity column adheres to the following requirements:
PricingQuantity
Pricing Quantity
The volume of a given SKU associated with a
resource or service used or purchased, based on the
Pricing Unit.
Aggregation: When aggregating Pricing Quantity for
commitment utilization calculations, it’s important to exclude commitment discount
purchases (i.e. when Charge Category is “Purchase”) that are paid to
cover future eligible charges
(e.g., commitment discount). Otherwise, when accounting for all
upfront or accrued purchases, it’s important to exclude commitment
discount usage (i.e. when Charge Category is “Usage”). This
exclusion helps prevent double counting of these quantities in the
aggregation.
Constraint | Value |
---|---|
Column type | Metric |
Feature level | Mandatory |
Allows nulls | True |
Data type | Decimal |
Value format | Numeric Format |
Number Range | Any valid decimal value |
The Pricing Unit represents a provider-specified measurement unit for
determining unit prices, indicating how the provider rates measured
usage and purchase quantities after applying pricing rules like block pricing. Common
examples include the number of hours for compute appliance runtime
(e.g., Hours
), gigabyte-hours for a storage appliance
(e.g., GB-Hours
), or an accumulated count of requests for a
network appliance or API service (e.g., 1000 Requests
).
Pricing Unit complements the Pricing
Quantity metric. Distinct from the Consumed
Unit, it focuses on pricing and cost, not resource and service consumption, often at a
coarser granularity.
The PricingUnit column adheres to the following requirements:
PricingUnit
Pricing Unit
Provider-specified measurement unit for determining unit prices,
indicating how the provider rates measured usage and purchase quantities
after applying pricing rules like block pricing.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | True |
Data type | String |
Value format | Unit Format |
A Provider is an entity that makes the resources or services available for purchase.
It is commonly used for cost analysis and reporting scenarios.
The ProviderName column adheres to the following requirements:
See Appendix: Origination of cost
data section for examples of Provider, Publisher and Invoice Issuer
values that can be used for various purchasing scenarios.
ProviderName
Provider
The name of the entity that made the resources or
services available for purchase.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
A Publisher is an entity that produces the resources or services that were purchased. It
is commonly used for cost analysis and reporting scenarios.
The PublisherName column adheres to the following requirements:
See Appendix: Origination of cost
data section for examples of Provider,
Publisher and Invoice Issuer values that
can be used for various purchasing scenarios.
PublisherName
Publisher
The name of the entity that produced the resources or
services that were purchased.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
A Region ID is a provider-assigned identifier for an isolated
geographic area where a resource is provisioned or a service is provided. The region is
commonly used for scenarios like analyzing cost and unit prices based on
where resources are deployed.
The RegionId column adheres to the following requirements:
RegionId
Region ID
Provider-assigned identifier for an isolated geographic area where a
resource is provisioned or a service is provided.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
Region Name is a provider-assigned display name for an isolated
geographic area where a resource is provisioned or a service is provided. Region Name
is commonly used for scenarios like analyzing cost and unit prices based
on where resources are deployed.
The RegionName column adheres to the following requirements:
RegionName
Region Name
The name of an isolated geographic area where a resource is
provisioned or a service is provided.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
A Resource ID is an identifier assigned to a resource by the provider. The
Resource ID is commonly used for cost reporting, analysis, and
allocation scenarios.
The ResourceId column adheres to the following requirements:
ResourceId
Resource ID
Identifier assigned to a resource by the provider.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
The Resource Name is a display name assigned to a resource. It is commonly used for
cost analysis, reporting, and allocation scenarios.
The ResourceName column adheres to the following requirements:
ResourceName
Resource Name
Display name assigned to a resource.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
Resource Type describes the kind of resource the charge applies to. A Resource Type
is commonly used for scenarios like identifying cost changes in groups
of similar resources and may include values like Virtual
Machine, Data Warehouse, and Load Balancer.
The ResourceType column adheres to the following requirements:
ResourceType
Resource Type
The kind of resource the charge applies to.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
The Service Category is the highest-level classification of a service based on the core function
of the service. Each service should have one and only
one category that best aligns with its primary purpose. The Service
Category is commonly used for scenarios like analyzing costs across
providers and tracking the migration of workloads across fundamentally
different architectures.
The ServiceCategory column adheres to the following requirements:
ServiceCategory
Service Category
Highest-level classification of a service based on the core
function of the service.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | Allowed Values |
Allowed values:
Service Category | Description |
---|---|
AI and Machine Learning | Artificial Intelligence and Machine Learning related technologies. |
Analytics | Data processing, analytics, and visualization capabilities. |
Business Applications | Business and productivity applications and services. |
Compute | Virtual, containerized, serverless, or high-performance computing infrastructure and services. |
Databases | Database platforms and services that allow for storage and querying of data. |
Developer Tools | Software development and delivery tools and services. |
Multicloud | Support for interworking of multiple cloud and/or on-premises environments. |
Identity | Identity and access management services. |
Integration | Services that allow applications to interact with one another. |
Internet of Things | Development and management of IoT devices and networks. |
Management and Governance | Management, logging, and observability of a customer’s use of cloud. |
Media | Media and entertainment streaming and processing services. |
Migration | Moving applications and data to the cloud. |
Mobile | Services enabling cloud applications to interact via mobile technologies. |
Networking | Network connectivity and management. |
Security | Security monitoring and compliance services. |
Storage | Storage services for structured or unstructured data. |
Web | Services enabling cloud applications to interact via the Internet. |
Other | New or emerging services that do not align with an existing category. |
A service represents an
offering that can be purchased from a provider (e.g., cloud virtual
machine, SaaS database, professional services from a systems
integrator). A service offering can include various types of
usage or other charges. For
example, a cloud database service may include compute, storage,
and networking charges.
The Service Name is a display name for the offering that was
purchased. The Service Name is commonly used for scenarios like
analyzing aggregate cost trends over time and filtering data to
investigate anomalies.
The ServiceName column adheres to the following requirements:
ServiceName
Service Name
An offering that can be purchased from a provider (e.g., cloud
virtual machine, SaaS database, professional services from a
systems integrator).
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
The Service Subcategory is a secondary classification of the Service Category for a service based on its core
function. The Service Subcategory (in conjunction with the Service
Category) is commonly used for scenarios like analyzing spend and usage
for specific workload types across providers and tracking the migration
of workloads across fundamentally different architectures.
The ServiceSubcategory column adheres to the following
requirements:
ServiceSubcategory
Service Subcategory
Secondary classification of the Service Category for a
service based on its core function.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Recommended |
Allows nulls | False |
Data type | String |
Value format | Allowed Values |
Allowed values:
Service Category | Service Subcategory | Service Subcategory Description |
---|---|---|
AI and Machine Learning | AI Platforms | Unified solution that combines artificial intelligence and machine learning technologies. |
AI and Machine Learning | Bots | Automated performance of tasks such as customer service, data collection, and content moderation. |
AI and Machine Learning | Generative AI | Creation of content like text, images, and music by learning patterns from existing data. |
AI and Machine Learning | Machine Learning | Creation, training, and deployment of statistical algorithms that learn from and perform tasks based on data. |
AI and Machine Learning | Natural Language Processing | Generation of human language, handling tasks like translation, sentiment analysis, and text summarization. |
AI and Machine Learning | Other (AI and Machine Learning) | AI and Machine Learning services that do not fall into one of the defined subcategories. |
Analytics | Analytics Platforms | Unified solution that combines technologies across the entire analytics lifecycle. |
Analytics | Business Intelligence | Semantic models, dashboards, reports, and data visualizations to track performance and identify trends. |
Analytics | Data Processing | Integration and transformation tasks to prepare data for analysis. |
Analytics | Search | Discovery of information by indexing and retrieving data from various sources. |
Analytics | Streaming Analytics | Real-time data stream processes to detect patterns, trends, and anomalies as they occur. |
Analytics | Other (Analytics) | Analytics services that do not fall into one of the defined subcategories. |
Business Applications | Productivity and Collaboration | Tools that facilitate individuals managing tasks and working together. |
Business Applications | Other (Business Applications) | Business Applications services that do not fall into one of the defined subcategories. |
Compute | Containers | Management and orchestration of containerized compute platforms. |
Compute | End User Computing | Virtualized desktop infrastructure and device / endpoint management. |
Compute | Quantum Compute | Resources and simulators that leverage the principles of quantum mechanics. |
Compute | Serverless Compute | Enablement of compute capabilities without provisioning or managing servers. |
Compute | Virtual Machines | Computing environments ranging from hosts with abstracted operating systems to bare-metal servers. |
Compute | Other (Compute) | Compute services that do not fall into one of the defined subcategories. |
Databases | Caching | Low-latency and high-throughput access to frequently accessed data. |
Databases | Data Warehouses | Big data storage and querying capabilities. |
Databases | Ledger Databases | Immutable and transparent databases to record tamper-proof and cryptographically secure transactions. |
Databases | NoSQL Databases | Unstructured or semi-structured data storage and querying capabilities. |
Databases | Relational Databases | Structured data storage and querying capabilities. |
Databases | Time Series Databases | Time-stamped data storage and querying capabilities. |
Databases | Other (Databases) | Database services that do not fall into one of the defined subcategories. |
Developer Tools | Developer Platforms | Unified solution that combines technologies across multiple areas of the software development lifecycle. |
Developer Tools | Continuous Integration and Deployment | CI/CD tools and services that support building and deploying code for software and systems. |
Developer Tools | Development Environments | Tools and services that support authoring code for software and systems. |
Developer Tools | Source Code Management | Tools and services that support version control of code for software and systems. |
Developer Tools | Quality Assurance | Tools and services that support testing code for software and systems. |
Developer Tools | Other (Developer Tools) | Developer Tools services that do not fall into one of the defined subcategories. |
Identity | Identity and Access Management | Technologies that ensure users have appropriate access to resources. |
Identity | Other (Identity) | Identity services that do not fall into one of the defined subcategories. |
Integration | API Management | Creation, publishing, and management of application programming interfaces. |
Integration | Messaging | Asynchronous communication between distributed applications. |
Integration | Workflow Orchestration | Design, execution, and management of business processes and workflows. |
Integration | Other (Integration) | Integration services that do not fall into one of the defined subcategories. |
Internet of Things | IoT Analytics | Examination of data collected from IoT devices. |
Internet of Things | IoT Platforms | Unified solution that combines IoT data collection, processing, visualization, and device management. |
Internet of Things | Other (Internet of Things) | Internet of Things (IoT) services that do not fall into one of the defined subcategories. |
Management and Governance | Architecture | Planning, design, and construction of software systems. |
Management and Governance | Compliance | Adherance to regulatory standards and industry best practices. |
Management and Governance | Cost Management | Monitoring and controlling expenses of systems and services. |
Management and Governance | Data Governance | Management of the availability, usability, integrity, and security of data. |
Management and Governance | Disaster Recovery | Plans and procedures that ensure systems and services can recover from disruptions. |
Management and Governance | Endpoint Management | Tools that configure and secure access to devices. |
Management and Governance | Observability | Monitoring, logging, and tracing of data to track the performance and health of systems. |
Management and Governance | Support | Assistance and expertise supplied by providers. |
Management and Governance | Other (Management and Governance) | Management and governance services that do not fall into one of the defined subcategories. |
Media | Content Creation | Production of media content. |
Media | Gaming | Development and delivery of gaming services. |
Media | Media Streaming | Multimedia delivered and rendered in real-time on devices. |
Media | Mixed Reality | Technologies that blend real-world and computer-generated environments. |
Media | Other (Media) | Media services that do not fall into one of the defined subcategories. |
Migration | Data Migration | Movement of stored data from one location to another. |
Migration | Resource Migration | Movement of resources from one location to another. |
Migration | Other (Migration) | Migration services that do not fall into one of the defined subcategories. |
Mobile | Other (Mobile) | All Mobile services. |
Multicloud | Multicloud Integration | Environments that facilitate consumption of services from multiple cloud providers. |
Multicloud | Other (Multicloud) | Multicloud services that do not fall into one of the defined subcategories. |
Networking | Application Networking | Distribution of incoming network traffic across application-based workloads. |
Networking | Content Delivery | Distribution of digital content using a network of servers (CDNs). |
Networking | Network Connectivity | Facilitates communication between networks or network segments. |
Networking | Network Infrastructure | Configuration, monitoring, and troubleshooting of network devices. |
Networking | Network Routing | Services that select paths for traffic within or across networks. |
Networking | Network Security | Protection from unauthorized network access and cyber threats using firewalls and anti-malware tools. |
Networking | Other (Networking) | Networking services that do not fall into one of the defined subcategories. |
Security | Secret Management | Information used to authenticate users and systems, including secrets, certificates, tokens, and other keys. |
Security | Security Posture Management | Tools that help organizations configure, monitor, and improve system security. |
Security | Threat Detection and Response | Collect and analyze security data to identify and respond to potential security threats and vulnerabilities. |
Security | Other (Security) | Security services that do not fall into one of the defined subcategories. |
Storage | Backup Storage | Secondary storage to protect against data loss. |
Storage | Block Storage | High performance, low latency storage that provides random access. |
Storage | File Storage | Scalable, sharable storage for file-based data. |
Storage | Object Storage | Highly available, durable storage for unstructured data. |
Storage | Storage Platforms | Unified solution that supports multiple storage types. |
Storage | Other (Storage) | Storage services that do not fall into one of the defined subcategories. |
Web | Application Platforms | Integrated environments that run web applications. |
Web | Other (Web) | Web services that do not fall into one of the defined subcategories. |
Other | Other (Other) | Services that do not fall into one of the defined categories. |
A SKU ID is a provider-specified unique identifier that represents a
specific SKU. SKUs are
quantifiable goods or service offerings in a FOCUS dataset that represent
specific functionality and technical specifications. Examples of
SKUs include but are not limited to:
Each SKU ID represents a unique set of features that can be sold at
different price points or SKU
Prices. SKU ID is consistent across all pricing variations,
which may differ based on multiple factors beyond the common
functionality and technical specifications. Examples include but are not
limited to:
SKU ID should be consistent across pricing variations of a good or
service to facilitate price comparisons for the same functionality, like
where the functionality is provided or how it’s paid for. SKU ID can be
referenced on a catalog or price
list published by a provider to look up detailed information
about the SKU. The composition of the properties associated
with the SKU ID may differ across providers. SKU ID is commonly used for
analyzing and comparing costs for the same SKU across different price
details (e.g., term, tier, location).
The SkuId column adheres to the following requirements:
SkuId
SKU ID
Provider-specified unique identifier that represents a specific
SKU (e.g., a quantifiable good or service offering).
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
SKU Meter describes the functionality being metered or measured by a
particular SKU in a charge.
Providers often have billing models in which multiple SKUs exist for
a given service to describe and bill for different functionalities for
that service. For example, an object storage service may have separate
SKUs for functionalities such as object storage, API requests, data
transfer, encryption, and object management. This field helps
practitioners understand which functionalities are being metered by the
different SKUs that appear in a FOCUS dataset.
The SkuMeter column adheres to the following requirements:
Compute Usage, Block Volume Usage, Data Transfer, API Requests
SkuMeter
SKU Meter
Describes the functionality being metered or measured by a particular
SKU in a charge.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
SKU Price Details represent a list of SKU Price properties (key-value
pairs) associated with a specific SKU Price
ID. These properties include qualitative and quantitative properties
of a SKUs (e.g., functionality and
technical specifications), along with core stable pricing properties
(e.g., pricing terms, tiers, etc.), excluding dynamic or negotiable
pricing elements such as unit price amounts, currency (and related
exchange rates), temporal validity (e.g., effective dates), and
contract- or negotiation-specific factors (e.g., contract or account
identifiers, and negotiable discounts).
The composition of properties associated with a specific SKU
Price may differ across providers and across SKUs within
the same provider. However, the exclusion of dynamic or negotiable
pricing properties should ensure that all charges with the same SKU Price ID
share the same SKU Price Details, i.e., that SKU Price Details remains
consistent across different billing periods and billing accounts within a
provider.
SKU Price Details helps practitioners understand and distinguish
SKU Prices, each identified by a SKU Price ID and associated
with a used or purchased resource or service. It can also help
determine the quantity of units for a property when it holds a numeric
value (e.g., CoreCount), even when its unit differs from the one in
which the SKU is priced and charged, thus supporting FinOps
capabilities like unit economics. Additionally, the SKU Price Details
may be used to analyze costs based on pricing properties such as terms
and tiers.
The SkuPriceDetails column adheres to the following requirements:
{
"StorageClass": "Archive",
"CoreCount": 4,
"x_PremiumProcessing": true,
}
SkuPriceDetails
SKU Price Details
A set of properties of a SKU Price ID which are meaningful and common
to all instances of that SKU Price ID.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | JSON |
Value format | KeyValueFormat |
The following keys should be used when applicable to facilitate
cross-SKU and cross-provider queries for the same conceptual property.
Focus-defined keys will appear in the list below and Provider-defined
keys will be prefixed with “x_” to make them easy to identify as well as
prevent collisions.
Key | Description | Data Type | Unit of Measure (numeric) or example values (string) |
---|---|---|---|
CoreCount | Number of physical or virtual CPUs available1 |
Numeric | Measure: Quantity of Cores |
DiskMaxIops | Storage maximum sustained input/output operations per second1 |
Numeric | Measure: Input/Output Operations per Second (IOPS) |
DiskSpace | Storage capacity available | Numeric | Measure: Gibibytes (GiB) |
DiskType | Kind of disk used | String | Examples: “SSD”, “HDD”, “NVMe” |
GpuCount | Number of GPUs available | Numeric | Measure: Quantity of GPUs |
InstanceType | Common name of the instance including size, shape, series, etc. |
String | Examples: “m5d.2xlarge”, “NC24rs_v3”, “P50” |
InstanceSeries | Common name for the series and/or generation of the instance |
String | Examples: “M5”, “Dadv5”, “N2D” |
MemorySize | RAM allocated for processing | Numeric | Measure: Gibibytes (GiB2) |
NetworkMaxIops | Network maximum sustained input/output operations per second1 |
Numeric | Measure: Input/Output Operations per Second (IOPS) |
NetworkMaxThroughput | Network maximum sustained throughput for data transfer1 |
Numeric | Measure: Megabits per second (Mbps) |
OperatingSystem | Operating system family3 | String | Examples: “Linux”, “MacOS”, “Windows” |
Redundancy | Level of redundancy offered by the SKU |
String | Examples: “Local”, “Zonal”, “Global” |
StorageClass | Class or tier of storage provided | String | Examples: “Hot”, “Archive”, “Nearline” |
Notes
1 In the case of “burstable” SKUs offering
variable levels of performance, the baseline or guaranteed value should
be used.
2 Memory manufacturers still commonly uses “GB”
to refer to 230 bytes, which is known as GiB in other
contexts.
3 This is the operating system family of the
SKU, if it’s included with the SKU or the SKU only supports one type of
operating system.
SKU Price ID is a provider-specified unique identifier that
represents a specific SKU
Price associated with a resource or service used or purchased. It
serves as a key reference for a SKU Price in a price list published by a
provider, allowing practitioners to look up detailed information about
the SKU Price.
The composition of properties associated with the SKU Price ID may
differ across providers and across SKUs within the same
provider. However, the exclusion of dynamic or negotiable pricing
properties, such as unit price amount, currency (and related exchange
rates), temporal validity (e.g., effective dates), and contract- or
negotiation-specific elements (e.g., contract or account identifiers,
and negotiable discounts), ensures that the SKU Price ID remains
consistent across different billing periods and billing accounts within
a provider. This consistency enables efficient filtering of charges to track price fluctuations
(e.g., changes in unit price amounts) over time and across billing
accounts, for both list and contracted unit prices. Additionally, the
SKU Price ID is commonly used to analyze costs based on pricing
properties such as terms and tiers.
The SkuPriceId column adheres to the following requirements:
See Examples: Commitment
Discount Flexibility for more details around commitment discount
flexibility.
SkuPriceId
SKU Price ID
A provider-specified unique identifier that represents a specific
SKU Price associated with a resource or
service used or purchased.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
A Sub Account ID is a provider-assigned identifier assigned to a sub account. Sub Account ID is
commonly used for scenarios like grouping based on organizational
constructs, access management needs, and cost allocation strategies.
The SubAccountId column adheres to the following requirements:
See Appendix:
Grouping constructs for resources or services for details and
examples of the different grouping constructs supported by FOCUS.
SubAccountId
Sub Account ID
An ID assigned to a grouping of resources or services, often used to manage
access and/or cost.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
A Sub Account Name is a display name assigned to a sub account. Sub account Name
is commonly used for scenarios like grouping based on organizational
constructs, access management needs, and cost allocation strategies.
The SubAccountName column adheres to the following requirements:
See Appendix:
Grouping constructs for resources or services for details and
examples of the different grouping constructs supported by FOCUS.
SubAccountName
Sub Account Name
A name assigned to a grouping of resources or services, often used to manage
access and/or cost.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
Sub Account Type is a provider-assigned name to identify the type of
sub account. Sub Account
Type is a readable display name and not a code. Sub Account Type is
commonly used for scenarios like mapping FOCUS and provider constructs,
summarizing costs across providers, or invoicing and chargeback.
The SubAccountType column adheres to the following requirements:
SubAccountType
Sub Account Type
A provider-assigned name to identify the type of sub
account.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | String |
Value format | <not specified> |
The Tags column represents the set of tags assigned to tag sources that also account
for potential provider-defined or user-defined tag evaluations. Tags are
commonly used for scenarios like adding business context to cost and
usage data to identify and accurately allocate charges. Tags may also be referred
to by providers using other terms such as labels.
A tag becomes finalized when a single
value is selected from a set of possible tag values assigned to the tag
key. When supported by a provider, this can occur when a tag value is
set by provider-defined or user-defined rules.
The Tags column adheres to the following requirements:
This example illustrates various tags produced from multiple
user-defined and provider-defined tag schemes. The first three tags
illustrate examples from three different, user-defined tag schemes. The
provider predetermined that 1 user-defined tag scheme (i.e.,
"foo": "bar"
) does not have a prepended prefix, but the
remaining two user-defined tag schemes (i.e.,
"userDefinedTagScheme2/foo": "bar"
,
"userDefinedTagScheme3/foo": true
) do have provider-defined
and reserved prefixes. Additionally, the third tag is produced from a
valueless, user-defined tag scheme, so the provider also applies
true
as its default value.
The last two tags illustrate examples from two different,
provider-defined tag schemes. Since all provider-defined tag schemes
require a prefix, the provider has prepended predefined and reserved
prefixes (providerDefinedTagScheme1/
,
providerDefinedTagScheme2/
) to each tag.
{
"foo": "bar",
"userDefinedTagScheme2/foo": "bar",
"userDefinedTagScheme3/foo": true,
"providerDefinedTagScheme1/foo": "bar",
"providerDefinedTagScheme2/foo": "bar"
}
Within a provider, tag keys may be associated with multiple values,
and potentially defined at different levels within the provider, such as
accounts, folders, resource
and other resource grouping constructs. When finalizing,
providers must reduce these multiple levels of definition to a
single value where each key is associated with exactly one value. The
method by which this is done and the semantics are up to each provider
but must be documented within their respective documentation.
As an example, let’s assume 1 sub
account exists with 1 virtual machine with the following
details, and tag inheritance favors Resources over Sub
Accounts.
The table below represents a finalized dataset with these
resources. It also shows the finalized state after all
resource-oriented, tag inheritance rules are processed.
ResourceType | ResourceId | Tags |
---|---|---|
Sub Account | my-sub-account | { “team”: “ops”, “env”: “prod” } |
Virtual Machine | my-vm | { “team”: “web”, “env”: “prod” } |
Because the Virtual Machine Resource did not have an env
tag, it inherited tag, env:prod
(italicized), from its
parent sub account. Conversely, because the Virtual Machine
Resource already has a team
tag (team:web
), it
did not inherit team:ops
from its parent sub
account.
Tags
Tags
The set of tags assigned to tag sources that account for
potential provider-defined or user-defined tag evaluations.
Constraint | Value |
---|---|
Column type | Dimension |
Feature level | Conditional |
Allows nulls | True |
Data type | JSON |
Value format | Key-Value Format |
1.0-preview
Attributes are requirements that apply across a FOCUS dataset instead of an
individual column level. Requirements on data content can include naming
conventions, data types, formatting standardizations, etc. Attributes
may introduce high-level requirements for data granularity, recency,
frequency, etc. Requirements defined in attributes are necessary for
servicing FinOps
capabilities accurately using a standard set of instructions
regardless of the origin of the data.
A FOCUS dataset
consists of a set of columns that convey information about the charges
incurred with a provider. Each column describes an aspect of the charge,
including but not limited to:
While FOCUS establishes the core structure and standardizes columns
for consistent reporting of cost and usage data, the diverse and
evolving landscape of providers and service offerings may require
providers and data generators to include supplemental columns in the
FOCUS dataset. These additional columns may enable deeper analysis and
provide more detailed descriptions of usage that may not be fully
captured by standard FOCUS dataset columns.
In such cases, providers and data generators are responsible for
ensuring that their usage and cost data is accurately and
comprehensively represented by including necessary supplemental columns
without duplicating data in FOCUS columns. Rows in a FOCUS dataset may
be aggregated or split differently than non-FOCUS datasets to align with
FOCUS requirements (e.g., Discount Handling), while enriching the
dataset, providers and data generators must maintain the integrity of
FOCUS-defined dimensions and metrics. When performing these
transformations, providers and data generators must ensure the accuracy
of all dimensions and metrics, particularly summable values such as
costs and quantities.
Columns within FOCUS include an ID and a display name. Column IDs are
used in files and database tables and display names can be used in
report output and other descriptive content, like documentation. Column
IDs provided in a FOCUS dataset follow consistent naming and
ordering conventions for FinOps practitioners who consume the data for
analysis, reporting, and other use cases.
All columns defined in the FOCUS specification MUST follow the naming
and ordering requirements listed below.
ColumnHandling
Column Handling
Naming and ordering convention for columns appearing in a FOCUS
dataset.
Id
orName
suffix in the Column ID.Name
suffix if thereCategory
suffix MUST bex_
Columns that contain currency information in cost data following a
consistent format reduce friction for FinOps practitioners who consume
the data for analysis, reporting, and other use cases.
A currency may be one of the following currency types:
All columns capturing a currency value, defined in the FOCUS
specification, MUST follow the requirements listed below. Custom
currency-related columns SHOULD also follow the same formatting
requirements.
CurrencyFormat
Currency Format
Formatting for currency columns appearing in a FOCUS dataset.
None
Columns that provide date and time information conforming to
specified rules and formatting requirements ensure clarity, accuracy,
and ease of interpretation for both humans and systems.
All columns capturing a date/time value, defined in the FOCUS
specification, MUST follow the formatting requirements listed below.
Custom date/time-related columns SHOULD also follow the same formatting
requirements.
DateTimeFormat
Date/Time Format
Rules and formatting requirements for date/time-related columns
appearing in a FOCUS
dataset.
None
A discount is a pricing construct where providers offer a reduced
price for services. Providers
may have many types of discounts, including but not limited to
commercially negotiated
discounts, commitment discounts
when you agree to a certain amount of usage or spend, and bundled
discounts where you receive free or discounted usage of one product or
service based on the usage of another. Discount Handling is
commonly used in scenarios like verifying discounts were applied and
calculating cost savings.
Some discount offers can be purchased from a provider to get reduced
prices. The most common example is a commitment discount, where
you “purchase” a commitment to use or spend a specific amount within a
period. When a commitment isn’t fully utilized, the unused amount
reduces the potential savings from the discount and can even result in
paying higher costs than without the discount. Due to this risk, unused
commitment amounts need to be clearly identifiable at a granular level.
To facilitate this, unused commitments are recorded with a separate row
for each charge period where the commitment was not fully utilized. To
show the impact of purchased discounts on each discounted row, discount
purchases need the purchase amount to be amortized over the term the discount is applied to
(e.g., 1 year) with each charge
period split and applied to each row that received the
discount.
Amortization is a process used to break down and spread purchase
costs over a period of time or term of use. When a purchase is
applicable to resources, like commitment discounts, the
amortized cost of a resource takes the initial payment and term
into account and distributes it out based on the resource’s usage,
attributing the prorated cost for each unit of billing. Amortization
enables users of billing data to distribute purchase charges to the
appropriate audience in support of cost allocation efforts. Discount
Handling for purchased commitments is commonly used for scenarios like
calculating utilization and implementing chargeback for the purchase
amount.
While providers may use different terms to describe discounts, FOCUS
identifies a discount as being a reduced price applied directly to a
row. Any price or cost reductions that are awarded after the fact are
identified as a “Credit” Charge Category. One example might be when a
provider offers a reduced rate after passing a certain threshold of
usage or spend.
All rows defined in FOCUS MUST follow the discount handling
requirements listed below.
DiscountHandling
Discount Handling
Indicates how to include and apply discounts to usage charges or rows
in a FOCUS dataset.
None
Columns that provide Key-Value information are often used in place of
separate columns for enumerating data which would be inherently sparse
and/or without predetermined keys. This consolidates related information
and provides more consistency in the schema. Key-value pairs are also
referred to as name-value pairs, attribute-value pairs, or field-value
pairs.
All key-value related columns defined in the FOCUS specification MUST
follow the key-value formatting requirements listed below.
KeyValueFormat
Key-Value Format
Rules and formatting requirements for columns appearing in a FOCUS dataset that convey
data as key-value pairs.
true
, false
, ornull
.None
Cost data rows that don’t have a
value that can be presented for a column must be handled in a consistent
way to reduce friction for FinOps practitioners who consume the data for
analysis, reporting, and other use cases.
All columns defined in the FOCUS specification MUST follow the null
handling requirements listed below. Custom columns SHOULD also follow
the same formatting requirements.
NullHandling
Null Handling
Indicates how to handle columns that don’t have a value.
None
Columns that provide numeric values conforming to specified rules and
formatting requirements ensure clarity, accuracy, and ease of
interpretation for humans and systems. The FOCUS specification does not
require a specific level of precision for numeric values. The level of
precision required for a given column is determined by the provider and
should be part of a data definition published by the provider.
All columns capturing a numeric value, defined in the FOCUS
specification, MUST follow the formatting requirements listed below.
Custom numeric value capturing columns SHOULD adopt the same format
requirements over time.
NumericFormat
Numeric Format
Rules and formatting requirements for numeric columns appearing in a
FOCUS dataset.
Data Type | Type Description |
---|---|
Integer | Specifies a numeric value represented by a whole number or by zero. Integer number formats correspond to standard data types defined by ISO/IEC 9899:2018 |
Decimal | Specifies a numeric value represented by a decimal number. Decimal formats correspond to ISO/IEC/IEEE 60559:2011 and IEEE 754-2008 definitions. |
Data Type | Precision | Definition | Range / Significant Digits |
---|---|---|---|
Integer | Short | 16-bit signed short int ISO/IEC 9899:2018 |
-32,767 to +32,767 |
Integer | Long | 32-bit signed long int ISO/IEC 9899:2018 |
-2,147,483,647 to +2,147,483,647 |
Integer | Extended | 64-bit signed two’s complement integer or higher |
-(2^63 – 1) to (2^63 – 1) |
Decimal | Single | 32-bit binary format IEEE 754-2008 floating-point (decimal32) |
9 |
Decimal | Double | 64-bit binary format IEEE 754-2008 floating-point (decimal64) |
16 |
Decimal | Extended | 128-bit binary format IEEE 754-2008 floating-point (decimal128) or higher |
36+ |
This format requires that single numeric values be represented using
an integer or decimal format without additional characters or
qualifiers. The following lists provide examples of values that meet the
requirements and those that do not.
None
Columns that capture string values conforming to specified
requirements foster data integrity, interoperability, and consistency,
improve data analysis and reporting, and support reliable data-driven
decision-making.
All columns capturing a string value, defined in the FOCUS
specification, MUST follow the requirements listed below. Custom string
value capturing columns SHOULD adopt the same requirements over
time.
StringHandling
String Handling
Requirements for string-capturing columns appearing in a FOCUS dataset.
Billing data frequently captures data measured in units related to
data size, count, time, and other dimensions. The Unit Format
attribute provides a standard for expressing units of measure in columns
appearing in a FOCUS
dataset.
All columns defined in FOCUS specifying Unit Format as a value format
MUST follow the requirements listed below.
UnitFormat
Unit Format
Indicates standards for expressing measurement units in columns
appearing in a FOCUS dataset.
<plural-units>
– “GB”, “Seconds”<singular-unit>-<plural-time-units>
–<plural-units>/<singular-time-unit>
–<quantity> <plural-units>
– “1000 Tokens”,<plural-units>/<interval> <plural-time-units>
Data size unit names MUST be abbreviated using one of the
abbreviations in the following table. For example, a unit name of “TB”
is a valid unit name, and a unit name of “terabyte” is an invalid unit
name. Data size abbreviations can be considered both the singular and
plural form of the unit. For example, “GB” is both the singular and
plural form of the unit “gigabyte”, and “GBs” would be an invalid unit
name. Values that exceed 10^18 MUST use the abbreviation for exabit,
exabyte, exbibit, and exbibyte, and values smaller than a byte MUST use
the abbreviation for bit or byte. For example, the abbreviation “YB” for
“yottabyte” is not a valid data size unit name as it represents a value
larger than what is listed in the following table.
The following table lists the valid abbreviations for data size units
from a single bit or byte to 10^18 bits or bytes.
Data size in bits | Data size in bytes |
---|---|
b (bit) = 10^1 | B (byte = 10^1) |
Kb (kilobit = 10^3) | KB (kilobyte = 10^3) |
Mb (megabit = 10^6) | MB (megabyte = 10^6) |
Gb (gigabit = 10^9) | GB (gigabyte = 10^9) |
Tb (terabit = 10^12) | TB (terabyte = 10^12) |
Pb (petabit = 10^15) | PB (petabyte = 10^15) |
Eb (exabit = 10^18) | EB (exabyte = 10^18) |
Kib (kibibit = 2^10) | KiB (kibibyte = 2^10) |
Mib (mebibit = 2^20) | MiB (mebibyte = 2^20) |
Gib (gibibit = 2^30) | GiB (gibibyte = 2^30) |
Tib (tebibit = 2^40) | TiB (tebibyte = 2^40) |
Pib (pebibit = 2^50) | PiB (pebibyte = 2^50) |
Eib (exbibit = 2^60) | EiB (exbibyte = 2^60) |
A count-based unit is a noun that represents a discrete number of
items, events, or actions. For example, a count-based unit can be used
to represent the number of requests, instances, tokens, or
connections.
If the following list of recommended values does not cover a
count-based unit, a provider MAY introduce a new noun representing a
count-based unit. All nouns appearing in units that are not listed in
the recommended values table will be considered count-based units. A new
count-based unit value MUST be capitalized.
Count |
---|
Count |
Unit |
Request |
Token |
Connection |
Certificate |
Domain |
Core |
A time-based unit is a noun that represents a time interval.
Time-based units can be used to measure consumption over a time interval
or in combination with another unit to capture a rate of consumption.
Time-based units MUST match one of the values listed in the following
table.
Time |
---|
Year |
Month |
Day |
Hour |
Minute |
Second |
If the unit value is a composite value made from combinations of one
or more units, each component MUST also align with the set of
recommended values.
Instead of “per” or “-” to denote a Composite Unit, slash (“/”) and
space(” “) MUST be used as a common convention. Count-based units like
requests, instances, and tokens SHOULD be expressed using a value listed
in the count dimension. For example, if a usage unit is
measured as a rate of requests or instances over a period of time, the
unit SHOULD be listed as “Requests/Day” to signify the number of
requests per day.
None
1.0-preview
The FOCUS specification defines a metadata structure to be supplied
by data providers to facilitate practitioners’ use of FOCUS data. This
metadata includes general information about the data generator and the
schema of the FOCUS
dataset.
FOCUS Metadata SHOULD be provided in a format that is accessible
programmatically, such as a file, website, API, or table. Providers
SHOULD provide documentation on their implementation of the FOCUS
metadata.
The FOCUS metadata about the generator of the FOCUS data.
The FOCUS Data Generator metadata MUST be provided. This metadata
MUST be of type Object and MUST NOT contain null values.
For an example of the FOCUS Data Generator metadata please refer to:
Data Generator Example
Human-readable name of the entity that is generating the data.
The DataGenerator MUST be provided in the metadata. DataGenerator
MUST be of type String and MUST NOT be null. The DataGenerator SHOULD be
easily associated with the provider who generated the FOCUS dataset.
DataGenerator
Data Generator
Constraint | Value |
---|---|
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
The schema metadata object and its contents provides information
about the structure of the data provided.
FOCUS data artifacts, whether they are data files, data streams, or
data tables, MUST provide a clear reference to the schema of the data.
This reference MUST be retrievable without inspection of the contents of
the FOCUS data within the data artifact. For some delivery mechanisms
such as database tables, the provider may rely on the schema
functionality of the providing system.
It is recommended that the schema reference be provided as an
external reference rather than included in full as metadata accompanying
the data artifact. This allows for easier understanding of when changes
to the schema of the FOCUS
datasets occurs.
Should the provider change the structure of the supplied FOCUS data
artifact, a new schema metadata object MUST be supplied. These scenarios
include, but are not limited to:
Should there be an error where the schema metadata object does not
match the schema of the FOCUS data artifact, the provider MUST update
the schema metadata object to match the schema of the FOCUS data
artifact. This is to ensure that the schema metadata object is always
accurate.
For an example of the FOCUS schema metadata please refer to: Schema Metadata Example
The Schema ID provides the reference item to associate which Schema
was used for the generation of a FOCUS Dataset.
The SchemaId MUST be present in the metadata. The SchemaId MUST be of
String. It is RECOMMENDED for SchemaId to be a Globally Unique
Identifier (GUID).
SchemaId
Schema ID
Constraint | Value |
---|---|
Feature level | Mandatory |
Allows nulls | False |
Data type | STRING |
Value format | Recommend GUID String |
Date the schema was created.
The CreationDate MUST be present in the metadata. This MUST be of
type Date/Time and MUST NOT contain null values. CreationDate MUST
conform to DateTimeFormat.
CreationDate
Creation Date
Constraint | Value |
---|---|
Feature level | Mandatory |
Allows nulls | False |
Data type | Date/Time |
Value format | Date/Time Format |
The version of FOCUS utilized for building the dataset.
The FocusVersion MUST be provided in the metadata. FocusVersion MUST
be of type String and MUST NOT contain null values. FocusVersion MUST
match one of the published versions of the FOCUS specification.
FocusVersion MUST match the version of the FOCUS specification that the
FOCUS dataset conforms
to.
FocusVersion
FOCUS Version
Constraint | Value |
---|---|
Feature level | Mandatory |
Allows nulls | False |
Data type | STRING |
Value format | Must align with a published FocusVersion |
The DataGeneratorVersion MAY be supplied to declare the version of
logic by which the FOCUS
dataset was generated and is separate from FOCUS Version.
DataGeneratorVersion allows for the provider to specify changes that may
not result in a structural change in the data. It is suggested that the
DataGeneratorVersion use a versioning approach such as SemVer version.
The DataGeneratorVersion column adheres to the following
requirements:
DataGeneratorVersion
Data Generator Version
Constraint | Value |
---|---|
Feature level | Optional |
Allows nulls | False |
Data type | STRING |
Value format | <not specified> |
The FOCUS metadata schema column definition provides a list of the
columns present in the FOCUS
dataset along with metadata about the columns.
This metadata MUST be present in the FOCUS metadata schema. This
metadata MUST be of type Object and MUST NOT contain null values.
The name of the column provided in the FOCUS dataset.
The ColumnName MUST be provided in the FOCUS Metadata schema.
ColumnName MUST be of type String and MUST NOT contain null values.
ColumnName
Column Name
Constraint | Value |
---|---|
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
The data type of the column provided in the FOCUS dataset.
The DataType MUST be provided in the FOCUS Metadata schema. DataType
MUST be of type String and MUST NOT contain null values.
DataType
Data Type
Constraint | Value |
---|---|
Feature level | Mandatory |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
The deprecation status of any column in a FOCUS dataset.
Deprecated MUST be provided in the FOCUS Metadata schema when a
column will be removed in a future delivered schema definition. DataType
MUST be of type Boolean and MUST NOT contain null values. The value of
deprecated should only be “true” if the column is deprecated. Providers
can choose to always provide the deprecation key or elect to only
include it when the deprecation status of a column is “true”. Deprecated
must be “true” when the provider removes a column at a future date, or
the column has been identified for deprecation for the FOCUS version
identified in the schema definition.
Deprecated
Deprecated
Constraint | Value |
---|---|
Feature level | Conditional |
Allows nulls | False |
Data type | Boolean |
Value format | <not specified> |
Numeric Precision is the maximum number of digits for the values in
the column.
NumericPrecision SHOULD be provided in the FOCUS Metadata schema for
Numeric Format columns. NumericPrecision MUST be of type Integer and
MUST NOT contain null values.
NumericPrecision
Numeric Precision
Constraint | Value |
---|---|
Feature level | Conditional |
Allows nulls | False |
Data type | Integer |
Value format | Numeric Format |
The number scale of the data provides the maximum number of digits
after the decimal point in decimal numbers.
NumberScale SHOULD be provided in the FOCUS Metadata schema for
Decimal columns. NumberScale MUST be of type Integer and MUST NOT
contain null values.
NumberScale
Number Scale
Constraint | Value |
---|---|
Feature level | Conditional |
Allows nulls | False |
Data type | Integer |
Value format | Numeric Format |
The PreviousColumnName field indicates that on that schema the column
where the key is included was renamed.
In cases where the PreviousColumnName is present, the following
applies:
PreviousColumnName
Previous Column Name
Constraint | Value |
---|---|
Feature level | Conditional |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
The Provider Tag Prefixes define the list of prefixes used in the tag
name of provider-defined tags. This metadata is
useful for the consumer to identify which tags are provider-defined vs
user-defined.
The ProviderTagPrefixes MUST be provided when ColumnName is equal to
Tags. The ProviderTagPrefix MUST be of type Array of Strings. The
ProviderTagPrefixes SHOULD be easily associated with the provider who
generated the FOCUS
dataset.
ProviderTagPrefixes
Provider Tag Prefixes
Constraint | Value |
---|---|
Feature level | Conditional |
Allows nulls | False |
Data type | Array |
Value format | STRING datatype values in the array |
The string encoding scheme of the column provided in the FOCUS dataset.
StringEncoding SHOULD be provided in the FOCUS Metadata schema when
it is required to know this information in order to successfully read
the data. StringEncoding MUST be of type String and MUST NOT contain
null values.
StringEncoding
StringEncoding
Constraint | Value |
---|---|
Feature level | Conditional |
Allows nulls | False |
Data type | String |
Value format | <not specified> |
The string max length of the data that can be stored in the
column.
StringMaxLength SHOULD be provided in the FOCUS Metadata schema for
String columns. StringMaxLength MUST be of type Integer and MUST NOT
contain null values.
StringMaxLength
String Max Length
Constraint | Value |
---|---|
Feature level | Conditional |
Allows nulls | False |
Data type | Integer |
Value format | Numeric Format |
1.0
This specification is based on a set of common FinOps use cases,
which are publicly available at https://focus.finops.org/use-cases/.
Developed by FinOps practitioners, these use cases are organized by
persona and capability, making it easy to find relevant scenarios. Each
use case includes sample SQL queries to help you get started with
implementation.
A charge representing a modification to billing data to account for
certain events or circumstances not previously captured, or captured
incorrectly. Examples include billing errors, service disruptions, or
pricing changes.
The distribution of upfront costs over time to accurately reflect the
consumption or benefit derived from the associated resources or
services. Amortization is valuable when the commitment period (time
duration of the cost) extends beyond the granularity of the source
report.
A collection of geographically separated locations containing a data
center or cluster of data centers. Each availability zone (AZ) should
have its own power, cooling, and networking, to provide redundancy and
fault tolerance.
A charge that serves as the basis for invoicing. It includes the
total amount of fees and discounts, signifying a monetary obligation.
Valuable when reconciling cash outlay with incurred expenses is
required, such as cost allocation, budgeting, and invoice
reconciliation.
A container for resources and/or services that are billed together in
an invoice. A billing account may have sub accounts, all of whose costs
are consolidated and invoiced to the billing account.
An identifier that represents the currency that a charge for
resources and/or services was billed in.
The time window that an organization receives an invoice for,
inclusive of the start date and exclusive of the end date. It is
independent of the time of usage and consumption of resources and
services.
A pricing approach where the cost of a particular resource or service
is determined based on predefined quantities or tiers of usage. In these
scenarios, the Pricing Unit and the corresponding Pricing Quantity can
be different from the Consumed Unit and Consumed Quantity.
A capacity reservation is an agreement that secures a dedicated
amount of resources or services for a specified period. This ensures the
reserved capacity is always available and accessible, even if it’s not
fully utilized. Customers are typically charged for the reserved
capacity, regardless of actual consumption.
A row in a FOCUS-compatible cost and usage dataset.
The time window for which a charge is effective, inclusive of the
start date and exclusive of the end date. The charge period for
continuous usage should match the time granularity of the dataset (e.g.,
1 hour for hourly, 1 day for daily). The charge period for a non-usage
charge with time boundaries should match the duration of
eligibility.
A company or organization that provides remote access to computing
resources, infrastructure, or applications for a fee.
A customer’s agreement to consume a specific quantity of a service or
resource over a defined period, usually also creating a financial
commitment throughout the entirety of the commitment period. Some
commitments also hold Providers to certain assurance levels of resource
availability.
A billing discount model that offers reduced rates on preselected
SKUs in exchange for an obligated usage or spend amount over a
predefined term. Commitment discount purchases, made upfront and/or with
recurring monthly payments are amortized evenly across predefined charge
periods (i.e., hourly), and unused amounts cannot be carried over to
subsequent charge periods. Commitment discounts are publicly available
to customers without special contract arrangements.
Commitment
Discount Flexibility
A feature of commitment
discounts that may further transform the predetermined amount
of usage purchased or consumed based on additional, provider-specific
requirements.
The agreed-upon unit price for a single Pricing Unit of the associated SKU, inclusive of
negotiated discounts, if present, and exclusive of any other discounts.
This price is denominated in the Billing Currency.
A charge to correct cost or usage data in a previously invoiced billing period.
A financial incentive or allowance granted by a provider unrelated to
other past/current/future charges.
A specification-defined categorical attribute that provides context
or categorization to billing data.
The amortized cost of the charge after applying all reduced rates,
discounts, and the applicable portion of relevant, prepaid purchases
(one-time or recurring) that covered this charge.
A Date/Time Format value that is not contained within the ending
bound of a time period.
A tag with one tag value chosen from a set of possible tag values
after being processed by a set of provider-defined or user-defined
rules.
FinOps Cost
and Usage Specification (FOCUS)
An open-source specification that defines requirements for billing
data.
A structured collection of cost and usage data that meets the BCP14 criteria defined by
FOCUS. In addition to FOCUS columns, the dataset should include custom
provider columns (prefixed with x_
) when these columns
provide additional information not captured by the existing FOCUS
columns. If introducing a custom column could result in splitting
original charge records into multiple entries, the data generator is
responsible for ensuring that the FOCUS dataset fully conforms to all
aggregation-related requirements for metric columns, particularly those
concerning costs and quantities.
A Date/Time Format value that is contained within the beginning bound
of a time period.
A category of compute resources that can be paused or terminated by
the CSP within certain criteria, often advertised at reduced unit
pricing when compared to the equivalent non-interruptible resource.
The suggested provider-published unit price for a single Pricing Unit of the associated SKU, exclusive of any discounts. This price is
denominated in the Billing
Currency.
Managed Service
Provider (MSP)
A company or organization that provides outsourced management and
support of a range of IT services, such as network infrastructure,
cybersecurity, cloud computing, and more.
A FOCUS-defined column that provides numeric values, allowing for
aggregation operations such as arithmetic operations (sum,
multiplication, averaging etc.) and statistical operations.
A government-issued currency (e.g., US dollars, Euros).
A contractual agreement where a customer commits to specific spend or
usage goals over a term in
exchange for discounted rates across varying SKUs. Unlike commitment discounts,
negotiated discounts are typically more customized to customer’s
accounts, can be utilized at varying frequencies, and may overlap with
commitment discounts.
A term that describes a service that is available and provided
immediately or as needed, without requiring a pre-scheduled appointment
or prior arrangement. In cloud computing, virtual machines can be
created and terminated as needed, i.e., on demand.
Pascal Case (PascalCase, also known as UpperCamelCase) is a format
for identifiers which contain one or more words meaning the words are
concatenated together with no delimiter and the first letter of each
word is capitalized.
A long and often painful conversation had by the FOCUS contributors.
Sometimes the name of a thing that we could not yet name. No starchy
root vegetables were harmed during the production of this specification.
We thank potato for its contribution in the creation of this
specification.
An individual who performs FinOps within an organization to maximize
the business value of using cloud and cloud-like services.
A comprehensive list of prices offered by a provider.
An entity that made internal or 3rd party resources and/or services
available for purchase.
A return of funds that have previously been charged.
A unique component that incurs a charge.
A row in a FOCUS-compatible cost and usage dataset.
An offering that can be purchased from a provider, and can include
many types of usage or other charges; eg., a cloud database service may
include compute, storage, and networking charges.
A construct composed of the common properties of a product offering
associated with one or many SKU Prices.
A pricing construct that encompasses SKU properties (e.g.,
functionality and technical specifications), along with core stable
pricing details for a particular SKU, while excluding dynamic or
negotiable pricing elements such as unit price amounts, currency (and
related exchange rates), temporal validity (e.g., effective dates), and
contract- or negotiation-specific factors (e.g., contract or account
identifiers, and negotiable discounts).
A sub account is an optional provider-supported construct for
organizing resources and/or services connected to a billing account. Sub
accounts must be associated with a billing account as they do not
receive invoices.
A metadata label assigned to a resource to provide information about
it or to categorize it for organizational and management purposes.
A Resource or Provider-defined construct for grouping resources
and/or other Provider-defined construct that a Tag can be assigned
to.
A duration of a contractual agreement like with a commitment discount or
negotiated
discount.
A proprietary currency (e.g., credits, tokens) issued by providers
and independent of government regulation.
This section is non-normative.
A commitment
discount is a billing discount model that offers reduced rates
on preselected SKUs in exchange for
an obligated usage or spend amount over a predefined term. Commitment discounts
typically consist of purchase and usage records within cost and usage
datasets.
Usage-based commitment discounts obligate a customer to a
predetermined amount of usage over a preselected term. In some
cases, usage-based commitment discounts also feature commitment discount
flexibility which may expand the types of resources that a commitment
discount can cover. It is important to note when mixing
commitment discounts with and without commitment discount
flexibility, the CommitmentDiscountUnit should reflect
this difference.
Spend-based commitment discounts obligate a customer to a
predetermined amount of spend over a preselected term. In the
usage examples below, each row
measures the monetary amount of the hourly commit consumed by the
commitment discount, so the CommitmentDiscountUnit chosen is
“USD”, or the billing
currency.
While customers are bound to the term of a commitment
discount, providers offer some or all of the following payment
options before and/or during the term:
For example, if a customer buys a 1-year, spend-based commitment
discount with a $1.00 hourly commit and pays with the partial
option, the commitment discount’s payment consists of a
one-time purchase in the beginning of the term and
monthly recurring purchases with the following totals:
24 hours * 365 days * $1.00 * 0.5
)24 hours * 365 days * $1.00 / 12 months
)Commitment discounts follow a “use-it-or-lose-it” model where the amortization of a
commitment discount’s purchase applies evenly to eligible
resources over each charge period of the
term.
For example, if a customer buys a spend-based commitment
discount with a $1.00 hourly commit in January (31 days), only
$1.00 is eligible for consumption for each hourly charge
period. If a customer has eligible resources running
during this charge period, an amount of up to $1.00 will be
allocated to these resources. Conversely, if a customer does
not have eligible resources running that fully take advantage
of this $1.00 during this charge period, then some or all of
this amount will go to waste.
Within the FOCUS specification, the following examples demonstrate
how a commitment discount appears across various payment and
usage scenarios.
All commitment discount purchases appear with a positive BilledCost, PricingCategory as “Standard”, and with the
commitment discount’s id populating both the ResourceId and CommitmentDiscountId value. One-time
purchases appear as a single record with ChargeCategory as “Purchase”, ChargeFrequency as “One-Time”, and the total
quantity and units for commitment discount’s term
reflected as CommitmentDiscountQuantity and
CommitmentDiscountUnit, respectively.
Recurring purchases are allocated across all corresponding charge
periods of the term when ChargeCategory is “Purchase”,
ChargeFrequency is “Recurring”, and CommitmentDiscountQuantity and
CommitmentDiscountUnit are reflected only for that charge
period.
Using the same commitment discount example as above with a
one-year, spend-based commitment discount with a $1.00 hourly
commit purchased on Jan 1, 2023, various purchase options are
available:
The entire commitment discount is billed once
during the first charge period of the term for $8,670
(derived as 24 hours * 365 days * $1.00
).
The commitment discount is billed across all 8,760
(24 hours * 365 days
) charge periods of the
term with $1.00 allocated to each charge period over
the term.
This example shows the first three hourly rows of 8,760 total rows
that are all the same except for the incrementing monthly and hourly
timeframes denoted in the Billing Period and Charge Period columns,
respectively.
With a 50/50 split, half of the commitment is billed once
during the first charge period of the term for $4,380
(derived as 24 hours * 182.5 days * $1.00
), and
the other half is billed across each charge period over the
term, derived as ($1.00 * 8,760 hours * 0.5
).
Amortized costs incur half of the amount (i.e., $0.50) from the one-time
purchase and the other half from the recurring purchase.
This example shows the first three hourly rows of 8,760 total rows
that are all the same except for the incrementing monthly and hourly
timeframes denoted in the Billing Period and Charge Period columns,
respectively.
Amortization of commitment discounts occur
similarly regardless of how commitment discount purchases are
made. The same usage-based or spend-based amount is applied evenly
across all charge periods and potentially allocated to eligible
resources. Continuing with the same commitment
discount example, a one-year, spend-based commitment
discount with a $1.00 hourly commit and 1 resource (for
simplicity) yields 4 types of scenarios that can occur during a
charge period:
In this scenario, one eligible resource runs for the full
hour and consumes $1.00, so one row allocated to the
resource is produced.
In this situation, the full eligible, $1.00 amount remained
unutilized and results in 1 unused row. In this scenario, it is
important to note that while CommitmentDiscountQuantity is not because
$1 was still drawn down by the commitment discount even though,
no resource was allocated, so ConsumedQuantity and ConsumedUnit are null.
In this scenario, one eligible resource runs for the full
hour and consumes $0.75 of the $1.00 allocation. One row shows
$0.75 to a resource, and the other row shows that
$0.25 was unused.
In this scenario, one eligible resource runs for the full
hour and is charged $1.50. One row shows that $1.00 was
amortized from the commitment discount, and the other
shows that $0.50 was charged as standard, on-demand spend.
A usage-based commitment
discount obligates a customer to a usage amount for one or more
related SKUs in return for reduced rates. For example, when a
usage-based commitment discount is purchased to cover a
specific database SKU, this commitment will cover every hour over the
term where at least one instance of this SKU is running. The usage-based
commitment can cover 1 resource over the hour, or in the case of commitment discount
flexibility, it can cover a portion of 1 resource or multiple
resources at a time.
When mixing usage-based commitment discounts with and without
commitment discount flexibility and CommitmentDiscountQuantity
measured by time, it is important to differentiate the CommitmentDiscountUnit for
each type of commitment discount. In each scenario below,
commitment discounts without commitment discount
flexibility applied use “Hour” as the
CommitmentDiscountUnit, and conversely commitment discounts
with commitment discount flexibility applied use
“Normalized Hour” as the CommitmentDiscountUnit.
For more details on exactly how commitment discounts
purchase and usage rows appear with and without commitment discount
flexibility, see the following scenarios:
For this example, fictitious provider, TinyCloud, offers the
following SKU catalog which is used in the scenario below.
Service | Sku Id | Sku Price Id | Sku Price Unit Price | Normalization Factor |
---|---|---|---|---|
Compute | VM_SMALL | VM_SMALL_COMMITTED_PURCHASE_NO_UPFRONT | $0.50 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_COMMITTED_PURCHASE_NO_UPFRONT | $1.00 | 2 |
Compute | VM_LARGE | VM_LARGE_COMMITTED_PURCHASE_NO_UPFRONT | $1.50 | 3 |
Compute | VM_XLARGE | VM_XLARGE_COMMITTED_PURCHASE_NO_UPFRONT | $2.00 | 4 |
Compute | VM_SMALL | VM_SMALL_COMMITTED_HOUR | $0.50 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_COMMITTED_HOUR | $1.00 | 2 |
Compute | VM_LARGE | VM_LARGE_COMMITTED_HOUR | $1.50 | 3 |
Compute | VM_XLARGE | VM_XLARGE_COMMITTED_HOUR | $2.00 | 4 |
Compute | VM_SMALL | VM_SMALL_ON_DEMAND_HOUR | $1.00 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_ON_DEMAND_HOUR | $2.00 | 2 |
Compute | VM_LARGE | VM_LARGE_ON_DEMAND_HOUR | $3.00 | 3 |
Compute | VM_XLARGE | VM_XLARGE_ON_DEMAND_HOUR | $4.00 | 4 |
The above SKU Catalog shows that this provider only has 1 service
that offers 4 virtual machine SKUs at various list rates, commitment discount
rates, and normalization factors. Each SKU’s normalization factor
classifies its relative size to its commitment discount rate.
Usage-based commitment discounts with commitment discount
flexibility can fully cover any combination of 1 or more SKUs
where the sum of their normalization factor is less than or equal to the
normalization factor of the commitment discount.
For this example, fictitious provider, TinyCloud, offers the
following SKU catalog which is used in the scenario below.
Service | Sku Id | Sku Price Id | Sku Price Unit Price | Normalization Factor |
---|---|---|---|---|
Compute | VM_SMALL | VM_SMALL_COMMITTED_PURCHASE_NO_UPFRONT | $0.50 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_COMMITTED_PURCHASE_NO_UPFRONT | $1.00 | 2 |
Compute | VM_LARGE | VM_LARGE_COMMITTED_PURCHASE_NO_UPFRONT | $1.50 | 3 |
Compute | VM_XLARGE | VM_XLARGE_COMMITTED_PURCHASE_NO_UPFRONT | $2.00 | 4 |
Compute | VM_SMALL | VM_SMALL_COMMITTED_HOUR | $0.50 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_COMMITTED_HOUR | $1.00 | 2 |
Compute | VM_LARGE | VM_LARGE_COMMITTED_HOUR | $1.50 | 3 |
Compute | VM_XLARGE | VM_XLARGE_COMMITTED_HOUR | $2.00 | 4 |
Compute | VM_SMALL | VM_SMALL_ON_DEMAND_HOUR | $1.00 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_ON_DEMAND_HOUR | $2.00 | 2 |
Compute | VM_LARGE | VM_LARGE_ON_DEMAND_HOUR | $3.00 | 3 |
Compute | VM_XLARGE | VM_XLARGE_ON_DEMAND_HOUR | $4.00 | 4 |
The above SKU Catalog shows that this provider only has 1 service
that offers 4 virtual machine SKUs at various list unit prices, commitment discount
unit prices, and normalization factors. Each SKU’s normalization factor
classifies its relative size to its commitment discount unit
price. Usage-based commitment discounts with commitment discount
flexibility can fully cover any combination of 1 or more SKUs
where the sum of their normalization factor is less than or equal to the
normalization factor of the commitment discount.
For this example, fictitious provider, TinyCloud, offers the
following SKU catalog which is used in the scenario below.
Service | Sku Id | Sku Price Id | Sku Price Unit Price | Normalization Factor |
---|---|---|---|---|
Compute | VM_SMALL | VM_SMALL_COMMITTED_PURCHASE_NO_UPFRONT | $0.50 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_COMMITTED_PURCHASE_NO_UPFRONT | $1.00 | 2 |
Compute | VM_LARGE | VM_LARGE_COMMITTED_PURCHASE_NO_UPFRONT | $1.50 | 3 |
Compute | VM_XLARGE | VM_XLARGE_COMMITTED_PURCHASE_NO_UPFRONT | $2.00 | 4 |
Compute | VM_SMALL | VM_SMALL_COMMITTED_HOUR | $0.50 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_COMMITTED_HOUR | $1.00 | 2 |
Compute | VM_LARGE | VM_LARGE_COMMITTED_HOUR | $1.50 | 3 |
Compute | VM_XLARGE | VM_XLARGE_COMMITTED_HOUR | $2.00 | 4 |
Compute | VM_SMALL | VM_SMALL_ON_DEMAND_HOUR | $1.00 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_ON_DEMAND_HOUR | $2.00 | 2 |
Compute | VM_LARGE | VM_LARGE_ON_DEMAND_HOUR | $3.00 | 3 |
Compute | VM_XLARGE | VM_XLARGE_ON_DEMAND_HOUR | $4.00 | 4 |
The above SKU catalog shows that this provider only has 1 service
that offers 4 virtual machine SKUs at various list rates, commitment
discount rates, and normalization factors. Each SKU’s normalization
factor classifies its relative size to its commitment discount
rate. Usage-based commitment
discounts with commitment discount
flexibility can fully cover any combination of 1 or more SKUs
where the sum of their normalization factor is less than or equal to the
normalization factor of the commitment discount.
For this example, fictitious provider, TinyCloud, offers the
following SKU catalog which is used in the scenario below.
Service | Sku Id | Sku Price Id | Sku Price Unit Price | Normalization Factor |
---|---|---|---|---|
Compute | VM_SMALL | VM_SMALL_COMMITTED_PURCHASE_NO_UPFRONT | $0.50 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_COMMITTED_PURCHASE_NO_UPFRONT | $1.00 | 2 |
Compute | VM_LARGE | VM_LARGE_COMMITTED_PURCHASE_NO_UPFRONT | $1.50 | 3 |
Compute | VM_XLARGE | VM_XLARGE_COMMITTED_PURCHASE_NO_UPFRONT | $2.00 | 4 |
Compute | VM_SMALL | VM_SMALL_COMMITTED_HOUR | $0.50 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_COMMITTED_HOUR | $1.00 | 2 |
Compute | VM_LARGE | VM_LARGE_COMMITTED_HOUR | $1.50 | 3 |
Compute | VM_XLARGE | VM_XLARGE_COMMITTED_HOUR | $2.00 | 4 |
Compute | VM_SMALL | VM_SMALL_ON_DEMAND_HOUR | $1.00 | 1 |
Compute | VM_MEDIUM | VM_MEDIUM_ON_DEMAND_HOUR | $2.00 | 2 |
Compute | VM_LARGE | VM_LARGE_ON_DEMAND_HOUR | $3.00 | 3 |
Compute | VM_XLARGE | VM_XLARGE_ON_DEMAND_HOUR | $4.00 | 4 |
The above SKU Catalog shows that this provider only has 1 service
that offers 4 virtual machine SKUs at various list rates, commitment
discount rates, and normalization factors. Each SKU’s normalization
factor classifies its relative size to its commitment discount
rate. Usage-based commitment
discounts with commitment discount
flexibility can fully cover any combination of 1 or more SKUs
where the sum of their normalization factor is less than or equal to the
normalization factor of the commitment discount.
The following sections contain examples of metadata provided by a
hypothetical FOCUS data provider called ACME to supply the required
reference between the FOCUS
dataset and the schema metadata. Provider implementations will
vary on how the metadata is disseminated; however, the provider’s chosen
metadata delivery approach should be able to support the structure
represented in this example.
In this example, the provider supports delivery of FOCUS data via
file export to a data storage system. It uses JSON as the format for
providing the metadata. The provider delivers data every 12 hours into a
path structure described below:
Type of data | Path |
---|---|
Export location | /FOCUS |
Metadata location | /FOCUS/metadata |
Cost data location | /FOCUS/data |
Here are some metadata examples for various scenarios:
Acme provides metadata about the data generator as a part of their
FOCUS data export. They provide the relevant data via the Data Generator schema object.
Metadata can be provided at a location such as
/FOCUS/metadata/data_generator.json
.
The updated data generator related metadata could look like this:
{
"DataGenerator": "Acme"
}
ACME has decided to deprecate columns prior to removal from their
FOCUS data export. The column for deprecation is x_awesome_column3. The
provider creates a new Schema object to represent
the new schema, with a unique SchemaId.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-34567-abcde-34567-abcde-34567.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "34567-abcde-34567-abcde-34567",
"FocusVersion": "1.0",
"CreationDate": "2024-03-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
},
{
"ColumnName": "x_awesome_column3",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8",
"Deprecation": true
}
]
}
For an example of how ACME ensures the schema metadata reference
requirement is met see: Schema Metadata to FOCUS Data
Reference
ACME has decided to rename a column in their FOCUS data export. The
column for rename is x_awesome_column1 and will be renamed to
x_awesome_column_one. The provider creates a new Schema object to represent the new schema, with a
unique SchemaId. After this schema definition is
created if the data generator creates another schema, the
PreviousColumnName is removed.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-34567-abcde-34567-abcde-34567.json
.
The updated schema related metadata for the schema where the rename
took place could look like this:
{
"SchemaId": "34567-abcde-34567-abcde-34567",
"FocusVersion": "1.0",
"CreationDate": "2024-03-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column_one",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8",
"PreviousColumnName": "x_awesome_column1"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
},
{
"ColumnName": "x_awesome_column3",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8",
"Deprecation": true
}
]
}
The subsequent new schema metadata after the rename could look like
this:
{
"SchemaId": "34567-abcde-34567-abcde-34567",
"FocusVersion": "1.0",
"CreationDate": "2024-03-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column_one",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
},
{
"ColumnName": "x_awesome_column3",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8",
"Deprecation": true
}
]
}
For an example of how ACME ensures the schema metadata reference
requirement is met see: Schema Metadata to FOCUS Data
Reference
ACME has only provided one Schema for their
FOCUS data export. ACME provides a directory of schemas and each schema
is a single file. Acme provides a file representing the schema for the
data they provide.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-1234-abcde-12345-abcde-12345.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "1234-abcde-12345-abcde-12345",
"FocusVersion": "1.0",
"CreationDate": "2024-01-01T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
}
]
}
ACME makes a change to the Schema of their data
exports. For each FOCUS data export, ACME includes a metadata reference
to the schema object. Because multiple files are provided in each
export, Acme has elected to include a metadata file in each export
folder that includes the FOCUS schema reference that applies to the data
export files within that folder. When the schema changes, they include
the new Schema ID in their export metadata file
of the new folder.
Metadata can be provided at a location such as
/FOCUS/data/export1-metadata.json
The export metadata could look like this:
{
"SchemaId":"1234-abcde-12345-abcde-12345",
"data_location":
[
{
"filepath": "/FOCUS/data/export1/export1-part1.csv",
"total_bytes": 9010387,
"total_rows": 4450
},
{
"filepath": "/FOCUS/data/export1/export1-part2.csv",
"total_bytes": 9010387,
"total_rows": 4450
},
{
"filepath": "/FOCUS/data/export1/export1-part3.csv",
"total_bytes": 9010387,
"total_rows": 4450
},
{
"filepath": "/FOCUS/data/export1/export1-part4.csv",
"total_bytes": 9010387,
"total_rows": 4450
}
]
}
New metadata can be provided at a location such as
/FOCUS/data/export2-metadata.json
.
The new export metadata could look like this:
{
"SchemaId":"23456-abcde-23456-abcde-23456",
"data_location":
[
{
"filepath": "/FOCUS/data/export2/export2-part1.csv",
"total_bytes": 9010387,
"total_rows": 4450
},
{
"filepath": "/FOCUS/data/export2/export2-part2.csv",
"total_bytes": 9010387,
"total_rows": 4450
},
{
"filepath": "/FOCUS/data/export2/export2-part3.csv",
"total_bytes": 9010387,
"total_rows": 4450
},
{
"filepath": "/FOCUS/data/export2/export2-part4.csv",
"total_bytes": 9010387,
"total_rows": 4450
}
]
}
ACME specifies the optional metadata property Data Generator Version in their Schema object. They made a change to the FOCUS dataset they produce
that does not adopt a new FOCUS Version, nor does it make a change the
included columns, but does impact values in the data. This example
illustrates that Data Generator Version changes are independent of
column changes, however data generator version changes may include
column changes.
The data generator creates a new schema object to represent the new
schema. The data generator includes both the FOCUS Version and Data
Generator Version in the schema object.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-56789-abcde-56789-abcde-56789.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "56789-abcde-56789-abcde-56789",
"FocusVersion": "1.1",
"DataGeneratorVersion": "2.4",
"CreationDate": "2024-05-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"DataGeneratorTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
}
]
}
For an example of how ACME ensures the schema metadata reference
requirement is met see: Schema Metadata to FOCUS Data
Reference
ACME has decided to add additional columns to their FOCUS data
export. The new columns are x_awesome_column1, x_awesome_column2, and
x_awesome_column3. The provider creates a new Schema object to represent the new schema, this
schema object has a unique SchemaId. The
subsequent data exports that use the new schema include the new schema’s
id as a reference to their corresponding schema object.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-23456-abcde-23456-abcde-23456.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "23456-abcde-23456-abcde-23456",
"FocusVersion": "1.0",
"CreationDate": "2024-02-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["awecorp", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
},
{
"ColumnName": "x_awesome_column3",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
}
]
}
For an example of how ACME ensures the schema metadata reference
requirement is met see: Schema Metadata to FOCUS Data
Reference
ACME has decided to remove columns from their FOCUS data export. The
column removed is x_awesome_column3. The provider creates a new Schema object to represent the new schema, with a
unique SchemaId.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-34567-abcde-34567-abcde-34567.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "34567-abcde-34567-abcde-34567",
"FocusVersion": "1.0",
"CreationDate": "2024-03-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
}
]
}
For an example of how ACME ensures the schema metadata reference
requirement is met see: Schema Metadata to FOCUS Data
Reference
ACME has decided to change the datatype of column x_awesome_column1
from a string to a number. ACME creates a new Schema object with the modification to
x_awesome_column2.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-67891-abcde-67891-abcde-67891.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "67891-abcde-67891-abcde-67891",
"FocusVersion": "1.0",
"CreationDate": "2024-06-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
}
]
}
For an example of how ACME ensures the schema metadata reference
requirement is met see: Schema Metadata to FOCUS Data
Reference
ACME has discovered that while their export includes the column
x_awesome_column3, the Schema metadata does not
include this column. In this case, the provider fixes the metadata in
the existing schema object and does not need to create a new schema
object. Reference metadata remains the same.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-34567-abcde-34567-abcde-34567.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "34567-abcde-34567-abcde-34567",
"FocusVersion": "1.0",
"CreationDate": "2024-03-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
}
]
}
ACME’s previous exports used FOCUS version 1.0. They are now going to
adopt FOCUS version 1.1. It is required that they create a new schema
metadata object which specifies the new FOCUS version via the FOCUS Version property—regardless of schema
changes. In this example, the new FOCUS version adoption doesn’t include
columns changes. This is to illustrate that FOCUS version changes are
independent of column changes, however, this scenario is unlikely.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-45678-abcde-45678-abcde-45678.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "45678-abcde-45678-abcde-45678",
"FocusVersion": "1.1",
"CreationDate": "2024-04-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
}
]
}
For an example of how ACME ensures the schema metadata reference
requirement is met see: Schema Metadata to FOCUS Data
Reference
ACME specifies the optional metadata property Data Generator Version in their Schema object. Their data generator version 2.2
supported FOCUS version 1.0. They are now going to adopt FOCUS Version
1.1 which requires that they update their Data Generator Version when
updating the FOCUS Version. They create a new schema object designating
that both properties have changed. In this example, the adoption of the
new FOCUS version doesn’t include additional columns. This is to
illustrate that Data Generator Version can change independent of column
changes; however, this scenario is unlikely.
The data generator creates a new schema object to represent the new
schema. The data generator includes both the new FOCUS Version and Data
Generator Version in the schema object.
Metadata can be provided at a location such as
/FOCUS/metadata/schemas/schema-45678-abcde-45678-abcde-45678.json
.
The updated schema related metadata could look like this:
{
"SchemaId": "45678-abcde-45678-abcde-45678",
"FocusVersion": "1.1",
"DataGeneratorVersion": "2.3",
"name": "New Columns",
"CreationDate": "2024-04-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
}
]
}
For reference, the prior schema object looked like this:
{
"SchemaId": "34567-abcde-34567-abcde-34567",
"FocusVersion": "1.0",
"DataGeneratorVersion": "2.2",
"CreationDate": "2024-04-02T12:01:03.083z",
"ColumnDefinition": [
{
"ColumnName": "BillingAccountId",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "BillingAccountName",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "ChargePeriodStart",
"DataType": "DATETIME"
},
{
"ColumnName": "ChargePeriodEnd",
"DataType": "DATETIME"
},
{
"ColumnName": "BilledCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "EffectiveCost",
"DataType": "DECIMAL",
"NumericPrecision": 20,
"NumberScale": 10
},
{
"ColumnName": "Tags",
"DataType": "JSON",
"ProviderTagPrefixes": ["acme", "ac"]
},
{
"ColumnName": "x_awesome_column1",
"DataType": "STRING",
"StringMaxLength": 64,
"StringEncoding": "UTF-8"
},
{
"ColumnName": "x_awesome_column2",
"DataType": "DATETIME"
}
]
}
For an example of how ACME ensures the schema metadata reference
requirement is met see: Schema Metadata to FOCUS Data
Reference
The following section contains examples with how SaaS providers may
implement the FOCUS specification. SaaS provider implementations will
vary on the level of the detail available in their data, contract terms,
purchasing options, and other factors.
Many SaaS providers provide simple contract terms, therefore don’t
need to support complex scenarios like spend commitments or pricing
strategies in their billing data.
The scenarios described below illustrate how a FOCUS-compliant
dataset should look for simple SaaS agreement scenarios (these scenarios
may not be specific to SaaS agreements only).
ACME Corp allows its customers to purchase their service for a term
(in this case, a year) for a $10,000. ACME provides AwesomeCorp with a
single invoice for their usage. ACME does not provide detailed cost and
usage reports to AwesomeCorp throughout the Charge Period after the
initial purchase.
Given that ACME does not charge based on or track usage, its usage
details are irrelevant to this scenario.
Note the following details in the example dataset:
ACME Corp offers its customer the ability to purchase a fixed
quantity of licenses for their service. ACME provides AwesomeCorp with a
single invoice for their usage. ACME does not provide detailed cost and
usage reports to AwesomeCorp throughout the Charge Period after the
initial purchase.
On April 1st, 2025, ACME executes a contract and invoices AwesomeCorp
$50,000 (Billed Cost) for a Charge Period of April 1st 2025 to April 1st
2026. As there is no negotiated discount, List Cost of the purchase is
also $50,000.
Note the following details in the example dataset:
On June 1st 2025 ACME provides the following records due to
AwesomeCorp’s $1,000 mid-contract purchase of an additional 10 licenses
for the same Charge Period (April 1st 2025 to April 1st 2026).
Note the following additional details in the example dataset:
Similar to Scenario A above, ACME Corp offers its customer the
ability to purchase their service with a fixed quantity of licenses.
However, in Scenario B, ACME issues the invoice at the end of the usage
period.
On April 1st, 2026, ACME invoices AwesomeCorp $50,000 (Billed Cost)
for the Charge Period of April 1st 2025 to April 1st 2026. As there is
no negotiated discount, List Cost of the purchase is also $50,000.
Note the following additional details in the example dataset:
Like Scenario A2 above, ACME Corp offers its customers the ability to
purchase their service with a fixed quantity of licenses. However, in
Scenario C, ACME issues invoices at the end of each month (usage
period). For this scenario, contract terms additionally include the
following terms:
AwesomeCorp’s consumption looks like this:
Note the following additional details in the example dataset:
Many SaaS providers support billing models that allow (or in some
cases require) consumers to agree to an amount to spend over a period.
In some cases, customers receive a negotiated discount for usage during
that period in exchange for the spend agreement. Spend agreements can
have different payment models like billing in arrears or pre-paid
contracts and may impose minimum spend requirements for parts of the
agreement.
The scenarios described below illustrate how a FOCUS-compliant
dataset should look for various spend agreement scenarios.
The following baseline conditions apply to the scenarios described
below:
For this scenario A, contract terms include the following terms in
addition to the baseline scenario mentioned above:
For this scenario, contract terms additionally include the following
terms:
AwesomeCorp’s consumption looks like this:
Note the following details in the example dataset:
The spend agreement with Acme requires the customer to spend a
minimum amount in each Billing Period (monthly). Unused fees are charged
per Billing Period when the consumption is below this level (use-it or
lose-it). For this scenario, contract terms additionally include the
following terms:
AwesomeCorp’s consumption looks like this:
Note the following details in the example dataset:
For this scenario B, contract terms include the following terms in
addition to the baseline scenario mentioned above:
Scenario B1 is similar to scenario A1 with the difference being that
it’s a pre-paid contract.
Note the following details in the example dataset:
Scenario B2 is similar to A2 with the difference being that it’s a
pre-paid contract.
Note the following details in the example dataset:
Many SaaS providers support pricing models that utilize virtual
currencies such as credits, tokens, or points. Charges may be provided
using a virtual currency, which can subsequently be converted to a
national currency such as USD or EUR at an advertised or agreed-upon
conversion rate.
The scenarios described below illustrate how a FOCUS-compliant
dataset should look for various scenarios where a provider utilizes this
pricing model.
The following baseline conditions apply to the scenarios described
below:
For this scenario, contract terms include the following terms in
addition to the baseline scenario mentioned above:
For this scenario, the initial purchase of virtual currency is
executed as follows:
Note the following details in the example dataset:
Awesome Corp uses Acme’s services consuming tokens as follows in the
first day:
Note the following details in the example dataset:
For this scenario, contract terms include the following terms in
addition to the baseline scenario mentioned above:
For this scenario, the initial purchase of virtual currency is
executed as follows:
Note the following details in the example dataset:
Awesome Corp uses Acme’s services, consuming tokens as follows in the
first day:
Note the following details in the example dataset:
Awesome Corp uses Acme’s services consuming tokens as follows in the
first day:
Additionally, Acme Co offers a modified usage to token ratio for one
of their services as follows:
Note the following details in the example dataset:
For this scenario, Awesome Corp has exceeded their purchased tokens
on October 1st 2025 by 1,500 tokens and Acme Co has charged them for the
overage. The following conditions apply:
Note the following details in the example dataset:
Providers natively support various constructs for grouping resources or services. These grouping
constructs are often used to mimic organizational structures, technical
architectures, cost attribution/allocation and access management
boundaries, or other customer-specific structures based on
requirements.
Providers may support multiple levels of resource or service grouping
mechanisms. FOCUS supports two distinct levels of groupings that are
commonly needed for FinOps capabilities like chargeback, invoice
reconciliation and cost allocation.
The table below highlights key properties of the two grouping
constructs supported by FOCUS.
Property | Billing account | Sub account |
---|---|---|
Requirement level | Mandatory | Optional |
Receives an invoice? | Yes | No |
Invoiced at | Self | Associated billing account |
Examples | AWS: Management Account* GCP: Billing Account Azure MCA: Billing Profile Snowflake: Organizational Account |
AWS: Member Account GCP: Project Azure MCA: Subscription Snowflake: Account |
* For organizations that have multiple AWS Member Accounts
within an AWS Organization, consolidated billing is enabled by default
and invoices are received at Management Account level. A Member Account
can be removed from AWS consolidated billing whereby the removed account
receives independent invoices and is responsible for payments.
Cost data presented in the billing datasets originates from various
sources depending on the purchasing mechanism. There are at least 3
different pieces of information that are important for understanding
where cost originated from.
The value for each of these may be different depending on the various
purchasing scenarios for resources or services. Use
cases for purchasing direct, via a Managed Service Provider (MSP), via a
cloud marketplace, and from internal service offerings were considered.
The table below presents a few scenarios to show how the value for each
dimension may change based on the purchasing scenario.
# | Scenario | Provider | Publisher | Invoice Issuer |
---|---|---|---|---|
1.1 | Purchasing cloud services directly from cloud provider |
Cloud service provider | Cloud service provider | Cloud service provider |
1.2 | Purchasing cloud services from the cloud provider where the cloud region is operated by a 3rd party |
Cloud service provider | Cloud service provider | Entity operating the region for the cloud service provider |
2.1 | Purchasing cloud services via MSP | Managed Service Provider | Cloud service provider | Managed Service Provider |
2.2 | Purchasing cloud-agnostic resources or services built/sold by an MSP |
Managed Service Provider | Managed Service Provider | Managed Service Provider |
2.3 | Purchasing labor services from managed service provider |
Managed Service Provider | Managed Service Provider | Managed Service Provider |
3.1 | Purchasing a cloud marketplace offering that runs on the cloud provider |
Cloud service provider | Company building the software or services (Cloud service provider OR third-party software or services company) |
Cloud service provider |
3.2 | Purchasing a cloud marketplace offering that is not running directly on your cloud infrastructure (e.g,. SaaS product, Professional Services) |
Cloud service provider | Company producing the SaaS or services product |
Cloud service provider |
3.3 | Purchasing a SaaS product that is not directly running on your cloud infrastructure from a 3rd party reseller managed cloud marketplace |
Cloud service provider | SaaS provider | Reseller |
4.1 | Purchasing SaaS software directly from provider |
SaaS provider | SaaS provider | SaaS provider |
4.2 | Purchasing SaaS software that additionally runs on your cloud resources (in addition to #4.1) |
Cloud service provider | Cloud service provider | Cloud service provider |
5.1 | Purchasing internal infrastructure or services offerings running on-premise |
Internal product name | Internal product name | Internal product name |
5.2 | Purchasing internal infrastructure or services offerings running on cloud |
Internal product name | Internal product name | Internal product name |
5.3 | Associated software license cost for use on an on-premise infrastructure platform (Where license cost is presented separately in cost data) |
Internal product name | Company producing the software | Internal product name |
Explore the goals of FOCUS, view sample use cases, and learn about gathering FOCUS conformed datasets.
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