Booking Units: Difference between revisions
No edit summary |
No edit summary |
||
| (5 intermediate revisions by 2 users not shown) | |||
| Line 1: | Line 1: | ||
= General concept = | = General concept = | ||
'''Booking units''' (sometimes abbreviated as '''BEH''' [Buchungseinheiten]) are a standardized accounting and allocation mechanism used in shared-service environments, particularly in information technology (IT), cloud computing, and other resource-based services. They provide a common quantitative measure for planning, consuming, and charging for services whose underlying costs are heterogeneous or variable. | |||
'''Booking units''' (sometimes abbreviated as BEH [Buchungseinheiten]) are a standardized accounting and allocation mechanism used in shared-service environments, particularly in information technology (IT), cloud computing, and other resource-based services. They provide a common quantitative measure for planning, consuming, and charging for services whose underlying costs are heterogeneous or variable. | |||
Booking units are not a physical resource themselves; rather, they represent an abstracted unit of consumption that aggregates multiple cost drivers into a single, comparable metric. | Booking units are not a physical resource themselves; rather, they represent an abstracted unit of consumption that aggregates multiple cost drivers into a single, comparable metric. | ||
== Purpose and role == | == Purpose and role == | ||
| Line 29: | Line 27: | ||
# '''Identification of cost drivers''' | # '''Identification of cost drivers''' | ||
#: Relevant cost components are identified, such as compute capacity, storage volume, network usage, operational effort, and overhead costs. | #: Relevant cost components are identified, such as compute capacity, storage volume, network usage, operational effort, and overhead costs. | ||
# '''Weighting and aggregation''' | # '''Weighting and aggregation''' | ||
#: Individual cost drivers are weighted according to their contribution to overall costs and aggregated into a single composite unit. | #: Individual cost drivers are weighted according to their contribution to overall costs and aggregated into a single composite unit. | ||
# '''Normalization''' | |||
#: The resulting unit is normalized to ensure comparability across services, time periods, or user groups. This may involve defining a reference workload or baseline consumption pattern. | |||
# '''Periodic calibration''' | |||
#: Booking unit definitions are regularly reviewed and adjusted to reflect changes in technology, cost structures, or usage behavior. | |||
The calculation is often retrospective: actual costs incurred during an accounting period are distributed across the total number of booking units consumed, ensuring alignment between usage and expenditure. | |||
== Booking units and pricing == | |||
Booking units should be distinguished from fixed prices. In many models, especially in non-commercial or public-sector settings, a booking unit does not have a predetermined monetary value. Instead, the monetary value of a booking unit is calculated after the accounting period, based on total costs and total consumption. | |||
This approach contrasts with commercial pricing models, where prices per unit are typically set in advance and include profit margins or risk buffers. | |||
== Advantages and limitations == | |||
=== Advantages === | |||
* Enables fair and usage-based cost allocation | |||
* Reduces complexity in multi-tenant service environments | |||
* Supports cost transparency without exposing sensitive internal calculations | |||
* Flexible and adaptable to evolving service portfolios | |||
=== Limitations === | |||
* Requires careful design and governance to maintain trust | |||
* May be less intuitive for end users than simple fixed pricing | |||
* Periodic recalibration can introduce variability in unit value | |||
= Reference values for BEH calculation in bwCloud-OS = | |||
Within '''bwCloud-OS''', the conversion of technical resource consumption into booking units (BEHs) is based on standardized reference values for core infrastructure resources. These reference values define how individual resource usages contribute to the overall BEH consumption. | |||
A commonly applied reference model uses the following baseline assumptions: | |||
* '''vCPU''': One virtual CPU allocated for one day constitutes one reference unit of compute consumption: | |||
** 1 vCPU eqals 1 BEH/day | |||
* '''RAM''': One gigabyte (GB) of allocated main memory for one day constitutes two reference unit of memory consumption: | |||
** 1 GB equals 2 BEH/day | |||
* '''Volume storage''': Ten gigabyte (GB) of persistent block storage allocated for one day constitutes one reference unit of storage consumption. | |||
** 10 GB equals 1 BEH/day | |||
E.g.: This implicates that the usage of a tiny sized virtual machine consumes 4 BEH per day. (The flavor <code>tiny_1</code>is a configuration of 1 vCPU, 1 GB RAM and 10 GB Storage) | |||
Actual BEH consumption is calculated by weighting and aggregating these resource-specific reference units according to their relative cost relevance within the overall service operation. The exact weighting factors may be adjusted periodically to reflect changes in hardware costs, energy prices, or operational overhead, while the underlying reference values remain stable to ensure consistency and comparability over time. | |||
These reference values serve as a technical normalization layer and do not represent fixed prices; the monetary value of a BEH is determined retrospectively based on total incurred costs and total BEH consumption within the accounting period. | |||
Latest revision as of 15:43, 26 January 2026
General concept
Booking units (sometimes abbreviated as BEH [Buchungseinheiten]) are a standardized accounting and allocation mechanism used in shared-service environments, particularly in information technology (IT), cloud computing, and other resource-based services. They provide a common quantitative measure for planning, consuming, and charging for services whose underlying costs are heterogeneous or variable. Booking units are not a physical resource themselves; rather, they represent an abstracted unit of consumption that aggregates multiple cost drivers into a single, comparable metric.
Purpose and role
The primary role of booking units is to simplify the management and allocation of shared resources. In complex service environments, actual costs are typically influenced by multiple factors, such as infrastructure investment, energy consumption, personnel effort, maintenance, and software licensing. Booking units translate these diverse inputs into a uniform measure that can be used for:
- allocating capacity among multiple users or institutions,
- tracking and comparing service consumption over time,
- enabling internal charging, cost recovery, or cost-neutral settlement models,
- supporting planning, budgeting, and governance processes.
By decoupling service usage from individual technical parameters, booking units allow users to focus on consumption at a service level rather than on detailed cost structures.
Use in shared and public-sector services
Booking units are commonly applied in environments where multiple organizations jointly use a centrally operated service, such as public-sector IT platforms, academic computing infrastructures, or cooperative cloud services. In these contexts, booking units help balance transparency and simplicity:
- Transparency, by providing a traceable link between service usage and incurred costs.
- Simplicity, by avoiding institution-specific pricing models or detailed cost breakdowns for each technical component.
In cost-neutral models, booking units are often used not to generate profit, but to ensure that total costs incurred during a given accounting period are fully distributed among participants according to their relative usage.
Determination of booking units
The determination of booking units typically follows a multi-step methodological process. While implementations vary, common principles include:
- Identification of cost drivers
- Relevant cost components are identified, such as compute capacity, storage volume, network usage, operational effort, and overhead costs.
- Weighting and aggregation
- Individual cost drivers are weighted according to their contribution to overall costs and aggregated into a single composite unit.
- Normalization
- The resulting unit is normalized to ensure comparability across services, time periods, or user groups. This may involve defining a reference workload or baseline consumption pattern.
- Periodic calibration
- Booking unit definitions are regularly reviewed and adjusted to reflect changes in technology, cost structures, or usage behavior.
The calculation is often retrospective: actual costs incurred during an accounting period are distributed across the total number of booking units consumed, ensuring alignment between usage and expenditure.
Booking units and pricing
Booking units should be distinguished from fixed prices. In many models, especially in non-commercial or public-sector settings, a booking unit does not have a predetermined monetary value. Instead, the monetary value of a booking unit is calculated after the accounting period, based on total costs and total consumption. This approach contrasts with commercial pricing models, where prices per unit are typically set in advance and include profit margins or risk buffers.
Advantages and limitations
Advantages
- Enables fair and usage-based cost allocation
- Reduces complexity in multi-tenant service environments
- Supports cost transparency without exposing sensitive internal calculations
- Flexible and adaptable to evolving service portfolios
Limitations
- Requires careful design and governance to maintain trust
- May be less intuitive for end users than simple fixed pricing
- Periodic recalibration can introduce variability in unit value
Reference values for BEH calculation in bwCloud-OS
Within bwCloud-OS, the conversion of technical resource consumption into booking units (BEHs) is based on standardized reference values for core infrastructure resources. These reference values define how individual resource usages contribute to the overall BEH consumption. A commonly applied reference model uses the following baseline assumptions:
- vCPU: One virtual CPU allocated for one day constitutes one reference unit of compute consumption:
- 1 vCPU eqals 1 BEH/day
- RAM: One gigabyte (GB) of allocated main memory for one day constitutes two reference unit of memory consumption:
- 1 GB equals 2 BEH/day
- Volume storage: Ten gigabyte (GB) of persistent block storage allocated for one day constitutes one reference unit of storage consumption.
- 10 GB equals 1 BEH/day
E.g.: This implicates that the usage of a tiny sized virtual machine consumes 4 BEH per day. (The flavor tiny_1is a configuration of 1 vCPU, 1 GB RAM and 10 GB Storage)
Actual BEH consumption is calculated by weighting and aggregating these resource-specific reference units according to their relative cost relevance within the overall service operation. The exact weighting factors may be adjusted periodically to reflect changes in hardware costs, energy prices, or operational overhead, while the underlying reference values remain stable to ensure consistency and comparability over time.
These reference values serve as a technical normalization layer and do not represent fixed prices; the monetary value of a BEH is determined retrospectively based on total incurred costs and total BEH consumption within the accounting period.