Patent Application
20140379539
The field relates generally to generate billing data of a cloud service, and in particular, to a system and method for generating billing data of a composite cloud service, wherein the composite cloud service includes infrastructure as a service, software as a service and manual services.
Cloud computing delivers information technology service such as infrastructure, software etc. as a utility over the network. It allows end users to obtain access to computation, software, data, storage and network without requiring user knowledge with regards to the actual location or configuration of the underlying service. There are several public cloud providers offering cloud services like Infrastructure as a Service (or IaaS), Platform as a Service (or PaaS) and Software as a Service (SaaS). Each of these services provides a flexible way for the user to provision any of these services that are required on demand, and the user can pay only for those services that are used. There are several challenges associated with adopting public cloud services like security risks because of shared infrastructure with other tenants, regulatory compliance challenges etc. So, several large enterprises are creating enterprise private clouds that create a common pool of infrastructure and leverage that for offering cloud services to their different organization units.
A key challenge for cloud providers including public, private and hybrid clouds is to develop a solution for metering the various cost elements involved in delivering a composite cloud service that have been used and charge the users based on that. There are several products available in the market to monitor the resource usage, but they are designed only for tracking infrastructure usage. These products have the have the limitation that they do not take the people factor into consideration to address the costs involved in utilizing skilled people to provide services along with software and infrastructure as a combined composite service as part of the metering and billing method.
The present technique overcomes the above mentioned limitation by addressing the complexities of metering and billing a composition of infrastructure, software and manual effort as a single unit. The invention helps in allowing enterprise cloud providers to define and implement a chargeback and billing solution for composite cloud services that include infrastructure, software and manual services. It also describes the metrics for the various components and how to define a billing policy. Based on the metered data for the provisioned services and the associated billing policy, the user can be charged. This enables better alignment of the cloud service consumption to the associated business benefits when applied in the context of an enterprise private cloud.
According to one embodiment of the present disclosure, a method for generating billing data of a composite cloud service is disclosed. The method includes receiving a user request for the composite cloud service. After receiving the user request, one or more infrastructure, software and manual resources required to fulfill the user request are provisioned. Thereafter, the consumption of the one or more infrastructure, software and manual resources in real time to fulfill the user request is measured based on a predefined monitoring metrics. Finally, billing data for the composite cloud service is generated based on the measured consumption data of the one or more infrastructure, software and manual resources, a predefined chargeback model and a predefined billing policy.
In an additional embodiment, a system for generating billing data of a composite cloud service is disclosed. The system includes a user request receiving module, a provisioning module, a metering module and a billing module. The user request receiving module is configured to receive a user request for the composite cloud service. The provisioning module is configured to provision one or more infrastructure, software and manual resources required to fulfill the user request. The metering module is configured to measure consumption of the one or more infrastructure, software and manual resources in real time to fulfill the user request based on a predefined monitoring metrics. The billing module is configured to generate billing data for the composite cloud service based on the measured consumption data of the one or more infrastructure, software and manual resources, a predefined chargeback model and a predefined billing policy.
In another embodiment, a computer-readable storage medium for generating billing data of a composite cloud service is disclosed. The computer-readable storage medium which is not a signal stores computer-executable instructions for receiving a user request for the composite cloud service, provisioning one or more infrastructure, software and manual resources required to fulfill the user request, measuring consumption of the one or more infrastructure, software and manual resources in real time to fulfill the user request based on a predefined monitoring metrics and generating billing data for the composite cloud service based on the measured consumption data of the one or more infrastructure, software and manual resources, a predefined chargeback model and a predefined billing policy.
Various embodiments of the invention will, hereinafter, be described in conjunction with the appended drawings provided to illustrate, and not to limit the invention, wherein like designations denote like elements, and in which:
The foregoing has broadly outlined the features and technical advantages of the present disclosure in order that the detailed description of the disclosure that follows may be better understood. Additional features and advantages of the disclosure will be described hereinafter which form the subject of the claims of the disclosure. It should be appreciated by those skilled in the art that the conception and specific embodiment disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. It should also be realized by those skilled in the art that such equivalent constructions do not depart from the spirit and scope of the disclosure as set forth in the appended claims. The novel features which are believed to be characteristic of the disclosure, both as to its organization and method of operation, together with further objects and advantages will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended as a definition of the limits of the present disclosure.
Exemplary embodiments of the present technique provide a system and method for generating billing data of a composite cloud service. This involves receiving a user request for composite cloud service and based on the user request one or more infrastructure, software and manual resources are provisioned. The real time consumption of the one or more infrastructure, software and manual services is measured based on a predefined monitoring metrics and finally, billing data of the composite cloud service is generated based on the measured consumption data of the one or more infrastructure, software and manual resources, a predefined chargeback model and a predefined billing policy.
With reference to
Based on the combination of above provided attributes, the system can internally identify the infrastructure needed, the software licenses needed, the number of people required for providing the manual services and the skill level of the people involved. The real time consumption of the one or more infrastructure, software and manual resources are measured based on a predefined monitoring metrics, as in step 206. The monitoring metrics capture the metric name, the unit of measurement and the type of resource as follows:
Table 1 shows a sample metrics that can be monitored across the different types of resources. In the infrastructure that has been provisioned, the usage of the number of virtual machines can be tracked. Similarly for software provisioned, its metrics for monitoring can be the number of licenses of that software used or the amount of time the software was in running state. For services such as “Test-as-a-Service” where skilled testers can be provided along with the required hardware and software resources, their efforts can be tracked based on various factors which include dynamic allocation and de-allocations of people providing the professional services, skill and experience based costs, costs based on onsite and offshore models, different types of contracts like fixed price professional services contracts based on parameters like deliverables, quality etc, time and contracts based on the duration and number of people, travel costs, communication costs, costs unique to people aspects like overtime costs that are negotiated or mandated by local labor laws and so on. The unit cost and the service instances for the one or more resources are calculated to determine the consumption level. The exemplary metering data may be as follows:
Referring back to
The Billing policy will be deduced as follows:
Billing Policy=Function(R+M+F+U+T+OC+FC)
This translates into mathematical equation for calculating the total charge:
The Consumption for each Resource Type (CR) is determined by the duration for which a virtual machine server is running.
C
R
=U×T
Based on the consumption or usage determined, the Charge for each Resource Type (CHR) is determined based on the base cost for that unit and the rate factor. This translates as follows:
CHR=(BC×F×CR)
There will be a fixed cost (FC) involved for each resource type which will then be added to the Total Charge for each Resource (TCHR). Further in case a resource is used more than the duration that it was requested for, an Overcharge Cost (OC) will be applied for the additional duration.
This is represented as follows:
TCHR=FC+CHR+(OC×T)
The Total Cost for the Service Type (TCs) will then be the sum of the Total Charge for infrastructure, software and manual service resources that are provisioned as part of the Service Type.
The cost of manual services include dynamic allocation and de-allocations of people providing the professional services, skill and experience based costs, costs based on onsite and offshore models, different types of contracts like fixed price professional services contracts based on parameters like deliverables, quality etc, time and contracts based on the duration and number of people, travel costs, communication costs, costs unique to people aspects like overtime costs that are negotiated or mandated by local labor laws and so on.
Dynamic People Allocation and De-Allocation Cost Model:
Unlike in a traditional services delivery models, in a cloud based delivery model the services are subscription based so there can be dynamic changes in the requirements so, the number of people allocated to deliver a cloud service instance can vary over time. It can even be driven by an automated resource allocation algorithm using statistical regression & forecasting techniques and predictive machine learning algorithms predicting and optimizing the allocations. The chargeback system includes a component that is integrated with the resource allocation component to enable track the allocations and de-allocations.
Skill and Experienced Based Cost Model:
The composite cloud service definition includes quantification of the complexity of the tasks and the skill and experience level combinations needed. Taxonomy of ‘skill’ and experience with different level of the subject matter expertise (SME) and experience is created and unit cost for each level is calculated for different sourcing models:
Onsite/Offshore Cost Models:
A Global Delivery Model (GDM) with optimal Onsite/Offshore location of people delivering the professional services is created based on the business needs, time zone issues, economic factors and so on. The chargeback system includes a components that track the onsite and offshore allocations which can keep changing. It also uses historical data and tracks the various expenses associated with these for the various sourcing models to arrive at unit costs.
Fixed Price, Time & Material Contract Cost Model:
In a fixed price contract the professional services are procured based on pre-defined service unit definitions. In another model the rates agreed upon for the skill and experience levels for the various locations and subject matters and based and based on the number of people, the duration of their allocation and their billing rates the costs are arrived at. The charge back system includes a component that enables track these contracts for the various contractors to enable arrive at the costs.
Overhead Costs—Travel, Communication & Over Time Cost (TCO):
Delivering the professional services includes several overhead costs like travel and communication costs, costs for over time etc which are also tracked by a component in the charge back system.
In House Employees Performing Services (IH-S):
The costs for this model are arrived at tracking and using the Dynamic people allocation and de-allocations, skills & experience based costs, onsite & offshore mix. The salary costs and overhead costs are used to arrive at the overall costs and then the unit costs:
It is a function of [Dynamic people allocation and de-allocation (DPA)], [Skill and experienced based cost (SE)], [Onsite/Offshore models cost (OO)], [Contractor Cost (CC, [Overhead costs, Travel, Communication & Over time cost (OHC)] each of which is a function of time
∫(DPA(t),SE(t),OO(t),CC(t),OHC(t)) t=0 to t
Contractors Performing Services (C-S):
The costs for this model are arrived at by tracking the various contracts and the dynamic people allocation and de-allocations belonging to the various contracts, skills & experience based costs defined in the contracts and the overhead costs.
Outsourced Provider Providing Services (OP-S):
The costs for this model are arrived by at by tracking the Fixed Price (FP) and Time & Material (T & M) contracts. For the T & M contracts, costs are arrived by at, by tracking the allocation and de-allocations of people and their corresponding skills & experience, the skills & experience based costs defined in the contracts, the overhead costs etc. For the FP contracts, the units of work allocated, the milestones delivered are tracked and the costs are arrived at.
Crowd-Sourced People Service (CS-S):
Crowd sourcing is a type of participative online activity in which an individual, an institution, a non-profit organization, or company proposes to a group of individuals of varying knowledge, heterogeneity, and number, via a flexible open call, the voluntary undertaking of a task. The work units are split and crowd sourcing is employed to get them completed. The costs for the overheads and any payments agreed upon are used to arrive at the costs of this model.
Auctioned Model for Services (AM-S):
In the auctioned model, the work unit is auctioned through various auction models. The costs of this model are arrived at based on the pricing arrived at through the auction and by tracking the work allocations.
All these different types of manual services are summed up to calculate the total manual service cost as mentioned below:
a(IH-S)+b(C-S)+c(OP-S)+d(CS-S)+e(AM-S)
The total charge of the manual services would be
TCHR (Manual Services)=Function(R-M, M-S, F, U, T, BC, OV, L)
Thus, the total charge of the composite cloud service would be:
TCs=TCHR(Infrastructure)+TCHR(Software)+TCHR(Manual Services)
In accordance with an embodiment of the present technique, future requirement of the one or more infrastructure, software and manual resources for fulfilling the user request is predicted based on historical data and a forecaster. In this step, at predetermined intervals, the resource allocation and the chargeback rates are computed. It involves the following stages:
a) Forecast Future Resource Usage
b) Re-Allocate Resources and Update Chargeback Rates
One or more computer-readable media (e.g., storage media) or one or more processor-readable media (e.g., storage media) can comprise computer-executable instructions causing a computing system (e.g., comprising one or more processors coupled to memory) (e.g., computing environment 100 or the like) to perform any of the methods described herein. Examples of such computer-readable or processor-readable media include magnetic media, optical media, and memory (e.g., volatile or non-volatile memory, including solid state drives or the like).
The above-mentioned description is presented to enable a person of ordinary skill in the art to make and use the invention and is provided in the context of the requirement for obtaining a patent. Various modifications to the preferred embodiment will be readily apparent to those skilled in the art and the generic principles of the present invention may be applied to other embodiments, and some features of the present invention may be used without the corresponding use of other features. Accordingly, the present invention is not intended to be limited to the embodiment shown but is to be accorded the widest scope consistent with the principles and features described herein.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2718/CHE/2013 | Jun 2013 | IN | national |
