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Cloud Computing Costs and Benefits
AnITManagementPointofView
Nane Kratzke
Abstract Although cloud computing is in all mouth today it seems that there exist
only little evidence in literature that it is more economical effective than classical
data center approaches. Due to a performed qualitative analysis on COBIT, TOGAF
and ITIL this paper postulates that cloud-based approaches are likely to provide
more benefits than disprofits to IT management. Nevertheless one astonishing issue
is the not often stressed ex ante cost intransparency of cloud based approaches
which is a major implicit problem for IT investment decisions. This paper presents
considerations how to estimate costs of cloud based systems before they enter their
operational phase. This is necessary in order to make economical IT investment
decisions for or against cloud computing more objective.
Keywords Cloud • Business information system • Cost • Costestimation • Cost
transparency • ITIL • COBIT • TOGAF
1 Introduction
Providing IT-Services is a complex management as well as technological problem.
There exist a lot of parameters on different management,design as well as operation
levels which have significant influence on the overall effort efficiency.
Cloud computing is one of the latest developments within the business informa-
tion systems domain and describes a new delivery model for IT services based on
the Internet, and it typically involves the provision of dynamically scalable and often
virtualized resources.
N. Kratzke ()
Computer Science and Business Information Systems,
L¨ubeck University of Applied Sciences, L ¨ubeck, Germany
e-mail: kratzke@fh-luebeck.de
I. Ivanov et al. (eds.), Cloud Computing and Services Science, Service Science: Research
and Innovations in the Service Economy, DOI 10.1007/978-1-4614-2326-3 10,
© Springer Science+Business Media New York 2012
185
186 N. Kratzke
Most of the overall effort efficiency is deduced by capacity efficiency in literature
which is intensively proclaimed as a key benefit by cloud service providers. The
simple fact that only the used capacity of a cloud-based service has to be paid
inveigles to postulate the overall effort effectiveness of cloud-based approaches.
Almost every analyzed publication repeats this more or less unreflected—even
Talukader et al. [13]. This paper does not denial this postulation but advocates a
more critical view. The overall cost effectiveness of can should not be reduced to
their capacity efficiency.
1.1 Outline
Section 2starts with a brief summary and quintessence of a performed literature
review regarding the actual state of research in cloud cost estimation models.
In Sect. 3the overall relevance of cloud-based approaches is analyzed by well
known industry best practice management frameworks (COBIT, TOGAF and ITIL).
Section 3shows furthermorethat cloud-based approaches are likely to providemore
benefits than disprofits to IT management (see also Kratzke [8,9]). Nevertheless
there exist disprofits and issues which have to be solved. One issue is the ex ante
cost intransparency of cloud based approaches which is a major problem for IT
investment decisions. This contribution presents in Sect. 4first considerations how
to overcome the issue of ex ante cost intransparencyof cloud based services in order
to make IT investment decisions for cloud based approaches more reliable and trust
worthy.
2 The Literature Review
Due to page limitations this paper presents only a short summary of the literature re-
view results. This paper refers to Kratzke [8,9] for a more detailed description of the
performed literature review. Last but not least it turned out that no substantial cost
estimation models could be found in literature. Weinman provided a “mathematical
proof” of the inevitability of cloud computing [16]. Nevertheless Weinman only
“proofs” that several usage characteristics (e.g. peak load behaviour)of applications
fits very well with the cloud service business model from an economic point of view.
He does not provide a model to calculate likely costs of a cloud based information
system before it enters its operational phase. This is also stated by Truong and
Dustdar [14] formulating the wish “for a cost model associated with application
models” provided to academical research communities.
But literature review revealed some interesting basic approaches. From this paper
point of view the domain specific cost calculation approaches (e.g. Hazelhurst [5]
and Berrriman et al. [2]), usage characteristic specific approaches (e.g. Mazhelis
et al. [11] did this for communications intensive applications) as well as a domain
Cloud Computing Costs and Benefits 187
neutral indicator based methods (like cost effort per web interaction, e.g. Kossman
and Kraska [7]) seem the most promising approaches for providing representative
cost data of cloud-based applications which can be used for own cost and effort
estimations.
3 Impacts to Well Known Industry Best Practices
Krcmar [10] depicts in core three Information Management Domains: Overall
Management and Governance Functions, Enterprise Wide Information System
Design, Information Systems Development1and Information Systems Operation
(see Fig. 1). This paper covers all mentioned IT management domains by three
industry best practice standards (COBIT, TOGAF, ITIL). So this section focus
the impact of cloud computing to overall governance functions by using COBIT
[6], to enterprise wide information systems design by using TOGAF [4]andto
information systems operation by using ITIL (according to B ¨
ottcher [3]) as a
evaluation reference.
By applying these models qualitative impacts of business cloud computing to
one or more of the mentioned industry best practices standards are deduced. For
each of the mentioned models a process tree was developed and used to depict
qualitative impacts to the mentioned reference models. These process trees are
used to depict qualitative impacts. An qualitative impact may be positive (effort
reducing), negative (effort adding) or neutral (effort invariant). These impacts are
rated in the following way:
–Positive (marked (C)) if cloud computing may reduce efforts (compared to
classical information system approaches).
–Negative (marked ()) if cloud computing introduces additional efforts (com-
pared to classical information system approaches).
Fig. 1 Reflected IT
management standards
and classification models
1System design and development is not covered by this paper.
188 N. Kratzke
–Neutral (no mark) if cloud computing has no effect (compared to classical
information system approaches).2
Due to page limitations this paper presents no detailed (but in references existing)
reasoning of the postulated qualitative impacts to the analyzed models. Only the core
impacts with a short reasoning are stated. And whenever a process is rated neutral
(and therefore not mentioned in the next sections) this paper states neither effort
adding nor reducing impacts to these processes. This is mainly due to the fact that
these process steps should be done with or without a cloud-based foundation of
(business) information systems.
3.1 Impact to COBIT (Governance)
The Control Objectives for Information and related Technology (COBIT) is a
set of best practices (framework) for information technology (IT) management.
COBIT provides a set of measures, indicators, processes and best practices, to assist
maximizing the benefits derived through the use of information technology, and
developing appropriate IT governance and control in a company. COBIT defines a
set of deliver and support, acquire and implement, monitor and evaluate as well as
planning processes to operationalize IT-governance in companies (see Fig.2).
3.1.1 Cloud Computing Is Likely to Reduce Overall Efforts
In the Following COBIT Process Steps
Within the deliver and support process it is likely to reduce efforts for managing
performance and capacity, operations, continuous service as well as managing
physical environment due to the fact that this tasks are transferred to the cloud
vendor (Talukader et al. [13]). Furthermore efforts are likely reduced in definition of
third party services (already done by cloud vendor) and identification and allocation
cost (also done by cloud vendor duringbilling—so called ex post cost transparency).
Regarding the acquire and implementation process it is likely to reduce efforts in
identifying automated solutions, acquire and maintain technology infrastructure and
procure IT resources due to the fact that these tasks have to be performed by the
cloud vendor [13]. Regarding the planning processes it is likely to reduce efforts in
managing IT investments (this has to be done by the cloud vendor) as well as IT
Human resources (tendency to reduce the IT staff but need for IT professional with
2This is mainly due to tasks which are necessary for cloud-based or classical business information
systems governance, design, development or operation as well.
Cloud Computing Costs and Benefits 189
Fig. 2 Qualitative cloud impact to the Cobit process tree
cloud knowledge). Regarding the monitor and evaluation processes it is likely to
reduce efforts in monitoring and evaluating IT performance (this has to be done by
the cloud vendor).
3.1.2 Cloud Computing Has the Tendency to Enhance Occasionally
Efforts In the Following COBIT Process Steps
Within the deliver and support process it is likely to create additional efforts due
to a lot of security issues, (see Onwubiko et al. [12]) as well as due to a more
complex configuration management of virtual cloud assets which are not under
direct control of the cloud customer. Regarding the acquire and implementation
process it is likely to create additional efforts due to more complex (PaaS based)
Application development and their corresponding installation and accreditation
processes. Regarding the planning processes it is likely to create additional efforts
190 N. Kratzke
in assessing IT risks, defining IT processes and relationships as well as managing
projects (due to an additional actor—the cloud vendor). Regarding the monitor and
evaluation processes it is likely to create additional efforts ensuring compliance with
external requirements (due to the fact that the cloud vendor and its internal processes
have to reflected, see Onwubiko et al. [12]).
3.2 Impact to TOGAF (Enterprise Wide Design)
The Open Group Architecture Framework (TOGAF) is a framework for enter-
prise architecture management which provides a comprehensive approach to the
design, planning, implementation, and governance of an enterprise information
architecture. TOGAF based Enterprise Architectures are typically modeled at
four levels: Business, Application, Data and Technology. Application and data
architecture are integrated in a so called Information System Architecture. TOGAF
Enterprise Architectures should be developed using the Architecture Development
Model (ADM) Cycle shown in Fig. 3. TOGAF relies deeply on modularization,
standardization and already existing, proven technologies and products which fits
well with standardized cloud based IaaS, PaaS or SaaS services.
By using cloud-based approaches it is likely to reduce application design efforts
by using SaaS or PaaS3cloud-based services4due to the fact that the cloud service
providers have to provide precisely defined architecture building blocks which are
there chargeable assets.
It is furthermore likely to reduce technology architecture design efforts due to
the fact that they are predefined by IaaS5cloud service providers.In the most of use
cases it is easier to chose a technology architecture than to design one.
Both above mentioned facts will likely produce new opportunities and so-
lutions for business information systems and their corresponding information
architectures—this is also mentioned by Barr who emphasizes the business charac-
teristics of cloud computing: business flexibility, cost associativity as well as cheap
experimentation (see Barr [1], p. 9 and 10).
According to the performed literature research no negative effects of cloud
computing could be identified from a TOGAF point of view.
3SaaS—Software as a Service, e.g. SAP BUSINESS BYDESIGN; PaaS—Platform as a Service,
e.g. Google Apps.
4See [12–14] for a definition of SaaS or PaaS.
5IaaS—Infrastructure as a Service, e.g. Amazon EC2 (see [12–14] for a definition of IaaS).
Cloud Computing Costs and Benefits 191
Fig. 3 Qualitative cloud impact to the TOGAF process map
3.3 Impact to ITIL (Operations)
ITIL is an industry best practice standard for operating and providing IT-services
according to B¨
ottcher [3]. ITIL provides best practice processes to design and
operate IT-services for internal or external customers. IT-Services are driven by
general business requirements supporting a service strategy. All IT services are
handled in a service pipeline defining planned, operated and outdated processes.
The step from planned to operated services is done by so called service transition
processes. Figure 4lists all relevant ITIL processes according to B¨
ottcher [3].
192 N. Kratzke
Fig. 4 Qualitative cloud impact to the ITIL V3 process tree
3.3.1 Cloud Computing Shows the Potential to Reduce Overall Efforts
In the Following ITIL Process Steps
By using cloud-based approaches it is likely to reduce service design efforts in
capacity, availability as well as continuity management (see e.g Wood et al. [17]
or Talukader et al. [13]). This is due to the inherent capabilities of clouds. It is
furthermore likely to reduce service operation efforts in event, incident as well as
problem management because a lot of efforts have to be handled by cloud service
providers.
Cloud Computing Costs and Benefits 193
Tab l e 1 Overall weaknesses and strengths of cloud based approaches
Derived by analyzing COBIT TOGAF ITIL
Strengths Inherent scalability in capacity and performance x x
Inherent continuousity and availability x
Ex post cost transparency x x
Provision of automated infrastructure services x x x
Provision of automated functional services x x x
Physical infrastructure free (for customers) x x
Low level service free (for customers) x
Higher order service enabling x x
Weaknesses Additional cloud SW development skills x
More complex configuration management x x
More complex service and process management x x
More complex security management x x
More complex compliance management x
Ex ante cost intransparency x
3.3.2 Cloud Computing May Occasionally Enhance Efforts
in the Following ITIL Process Steps
By using cloud-based approaches it is likely to increase service level management
efforts which is due to involving an additional service providing party (the cloud
service provider, check Talukader et al. [13]). Additional efforts are also likely to
perform information security and compliancy management (see Onwubiko et al.
[12]) because aspects like privacy, data ownership, confidentiality, data location,
regulatory compliance, forensic evidence, auditing and overall trust issues have to be
considered. Furthermore additional efforts are likely to perform a service asset and
configuration management. A configuration management has to handle and control
virtual cloud assets which are not under direct control of the cloud-using service
customer.
3.4 Qualitative Weaknesses and Strengths of Clouds
Regarding the cloud impacts to COBIT (Governance, see Sect.3.1), to TOGAF
(Enterprise Wide Systems Design, see Sect. 3.2) and to ITIL (Service Operation, see
Sect. 3.3) this paper postulates the in Table 1listed overall qualitative weaknesses
and strengths of cloud-based approaches to IT management.
Analyzing Table 1you see that the strengths of clouds lay in their inherent
structure (scalability, continuousity, availability, etc.) as well as necessary market re-
quirements (provide well defined and therefore billable infrastructure or functional
services) which reduce efforts on the cloud customer side (avoiding to provide such
services on their own with smaller economical scale effects).
194 N. Kratzke
The weaknesses according to Table 1are mainly introduced by the fact that
an additional player (the cloud service provider) enters the game—so additional
interaction business processes become necessary introducing additional efforts.
From this paper point of view these additional service, process and configuration
management efforts will be overcompensated by the strengths of the cloud based
approaches. Sections 3.1–3.3 showed that more processes have benefits than
disprofits.
But let us look closer to security and compliance management aspects. This
category of weakness may come along with substantial “showstoppers” for a cloud
based approach. Whenever a company has to be compliant to regulatorieswhich can
not be fullfilled by cloud service level agreements (e.g. privacy requirements, data
ownership, confidentiality, data location, forensic evidence, auditing, etc.) cloud-
based approaches may be not feasible. But this is not due to economical but higher
order considerations.
Nevertheless there exist even an ex ante cost transparency weakness as it is stated
for example by Truong and Dustar [14]. This very important weakness (from an IT
management point of view) is even little reflected in literature so far. To answer
the question whether a cloud-based approach is more cost efficient than a classical
data center centric approach it has to be answered the question what costs will be
generated per month before an application enters operation (see also Walker et al.
[15]). This is very difficult to answer ex ante because it is influenced by a bunch of
interdependent parameters. Some of them are analysed in the following Sect. 4.
This finding is astonishing because it is postulated and repeated by several
authors that cloud services are increasing cost transparency (e.g. Talukader et al.
[13]). This paper agrees that cloud services will increase ex post cost transparency
mainly due to the underlying billing process of cloud service providers. But it
seems very hard to estimate cloud costs ex ante. Nevertheless this is needed for
IT investment decisions. Without being able to calculate or estimate cloud service
costs ex ante it is very hard to decide for a cloud-service based or a classical data
center centric approach.
4 A Resulting Cost Estimation Approach
As it was stated in Sect. 3.4 cloud services provide excellent ex post cost
transparency.
It was furthermore stated that there exist barley cost estimation models6for ex
ante cost calculation and transparency. This paper presents an approach to use the
strength of ex post cost transparency of cloud services to compensate the weak of
ex ante cost estimation.
6Which are cloud vendor independent.
Cloud Computing Costs and Benefits 195
System space
a
b
Using ex post cost data to estimate costs
Fig. 5 Visualization of the cost estimation principle
The core idea is a very simple one. Whenever running a cloud-service based
system it is easy to gather the costs ex post. Your cloud service provider will deliver
a bill with the used cloud service assets. Whenever you plan another cloud service
based system of comparable complexity and usage parameters you can look at costs
of your already running cloud service based system. It is likely that your ex post
costs of the existing system will have the same characteristics of your planned
system of comparable complexity and usage parameters.
This very simple idea has one evident problem. It will provide only good cost
estimations for comparable systems with comparable usage characteristics which is
not a very realistic assumption. But what to do when decisions have to be made for
non comparable systems? We have to make our model a little bit more complex.
One possibility is to inter- or extrapolate costs from nearest neighbors
(see Fig. 5). Nevertheless we have to describe cost driving parameters in a way
that they can be inter- or extrapolated to your planned system and we have to
deduce parameters which are appropriate to describe the dimensions of a system
space (which are most likely much more than two—so Fig.5shows an extreme
simplification of the to be encountered problem). A substantial cost calculation
model should have the capability to select the most comparable system of a given
system space in order to inter- or extrapolate the most appropriate cost driving
parameters for a cloud based application.
4.1 A Cloud Cost Model
A performed analysis of cloud service providers and their underlying billing
structures showed that the following aspects drive primarily costs of a cloud based
approach (see Fig. 6).
196 N. Kratzke
Fig. 6 Influences to cloud based costs
Figure 6shows the principal relations which should be covered by cloud based
cost analysis. First of all a perfect scalable (and cloud based) information system
should produce no costs at all if the system do not process any requests. And the
costs should raise with the amount of to be processed requests. So the core cost
driver are system usage requests. System usage requests create a cloud service usage
on an IaaS, PaaS or SaaS level (we use the short term XaaS if we refer to all three
levels) which is lastly billed by cloud service providers. Nevertheless which types
of XaaS services are used (and therefore billed) are also highly influenced by the
general (cloud based) information systems architecture.
Furthermore there exist feedback relations in the presented model. System
architecture also influences the generated service usage. Imagine a non scalable
system which has to handle a spur-of-the-momentusage peak. Typically the system
response times increase dramatically (or fail completely) if the peak usage exceed
significantly the designed maximum capacity. If this happens to often it is very
likely that the overall system usage declines in total because the system is rated
as unreliable by its users. Such spur-of-the-moment peak loads show no significant
impact to the overall system usage of highly scalable information systems because
theses systems can handle peak load scenarios. So you can see an indirect feedback
relation between a system architecture and the overall system usage of a cloud based
information system.
Cloud Computing Costs and Benefits 197
Another indirect feedback relation exists between the generated costs and
the system architecture. If a cloud based information system is meant to be to
expensive it is very likely to change its cost characteristic by changing its system
architecture—typically to reduce costs. There exist several strategies to do this—
e.g. replacing typical more expensive PaaS services by less convenient but cheaper
IaaS services, using more load balanced but less performant processing instances,
etc. This all has impact to the overall cloud based information system architecture.
In the following sections it is shown what parameters are appropriate to measure
cloud service usage and corresponding costs (see Sect. 4.2) and how influence of
an information systems architecture can be expressed in numbers (see Sect.4.4)
as well as how to measure the overall system usage of a cloud based information
system (see Sect. 4.3). Finally Sect. 4.5 shows how these components can be used to
identify comparable cloud based systems in order to use theirex post cost and usage
data to estimate costs of a planned cloud based information system.
4.2 Parameters to Describe Service Usage and Resulting Costs
Analysis of real world bills of cloud service providers7showed that on almost each
cloud service provision level (IaaS, PaaS, SaaS) cloud customers are billed for the
following service usage categories:
Data Transfer This includes all data which has to be transferred into, out of or
within a service. Sometimes data transfer is made explicit by being billed for
incoming, outgoing and inner traffic.
Data Storage This includes all data which has to be stored by a service provider in
order to process service requests.
Processing This includes the amount of time processing instances were used.
Processing time can be billed by instance uptime hours (typically only on IaaS level)
or by time spent for processing requests (this is more common on PaaS and SaaS
level).
Requests If a service provides its output via requests it is a common strategy to be
billed per request. This is very common on PaaS and SaaS level but less common
on IaaS level. Nevertheless even on IaaS level this type of billing can be found—
especially in data backup services like EC2 from Amazon Web Services. This is
called a micro request. Micro requests are seldom relevant cost drivers.
7The billing of Amazon Web Services and Google App Engine was analysed intensively but the
derived findings stay valid for other cloud service providers like Rackspace.com, Salesforce.com,
Windows (Azure), etc. cross checking their public accessible billing customer informations.
198 N. Kratzke
Tab l e 2 Cost categories
aligned to service levels Cost category IaaS PaaS SaaS
Data transfer (in, out, within) x x x
Data storage x x x
Processing (instance hours) x
Processing per request x x
Micro request x
Request x x
Network x
Network This includes all efforts in order to get a necessary network infrastructure
running. Typically network costs are billed only on the IaaS level. If they are relevant
on higher service levels they are typically billed via request costs.8Typically you
are billed for things like load balancers, ip addresses, auto scalers, etc.
The following Table 2shows which cost categories apply typically on which
cloud service level. By applying the following table it is possible to compare
different cloud service providers.
It is now possible to aggregate costs of different cloud service providers along a
row or a column. Let us do this exemplarily by aggregating Platform as a Service
costs of a specific cloud service provider. As you can see in Table 2Platform as a
Service costs are composed of data transfer, data storage, processing per request and
request costs.
Typically these parameters are billed by cloud services providers per identifiable
service (e.g. AWS Messaging Service).
– Amount of service requests SERV REQStto a service t
–DatastorageSERV STORAGEtassociated with service t
– Data transfer SERV TRANSFERrassociated with service t
– Resulting computing hours PROCHOURStassociated with service t
These parameters can be summarized over all used services tof a cloud-based
system and multiplied with the charge per service usage parameter CSERV REQ,
CSERV STORAGEt,CSERV TRANSFERtand CPROCHOURt. Therefore these costs can be
simply aggregated to system service cost PAASCOSTtper month for a service t.
PAASCOSTtD X
i
SERV REQSti!CSERV REQtC X
i
SERV STORAGEti!CSERV STORAGEt
C X
i
SERV TRANSFERti!CSERV TRANSFERtC X
i
PROCHOURSti!CPROCHOURt
For example this is what Amazon Web Services is charging on a monthly basis
for its S3, RDS-Service or Google for its GoogleApp-Service.
8Typically in these cases network costs are billed as non mentioned cost component of request
costs in bills.
Cloud Computing Costs and Benefits 199
The same is possible for infrastructure IAASCOST or software as a service
costs SAASCOST.9So it is possible to compare the costs of two or more different
cloud service providers on different service levels. It is furthermore possible to
calculate service level independent costs for network NETWORKCOST , request
REQUESTCOST, processing PROCESSINGCOST, data transfer DATA TRANSCOST or
data storage DATA STORAGECOST costs if you are interested in separating these
concerns.
4.3 Parameters to Describe System Usage
In Sect. 4.4 it is shown by principle how to compare different architectures in
order to get a feeling whether a reference cloud-based system has a comparable
architecture and therefore is a good candidate to evaluate its ex post cost data.
But systems with similar architectures do not automatically produce the same
cost. Cloud costs are produced primarily by usage.10 We only use architectures
to select the most comparable systems due to the fact that we think they will
produce a similar cost characteristic. The following usage parameters are deduced
by the analysis of web-based systems and analysis tools like GoogleAnalytics,11
AWStats,12 or Open Web Analytics.13 So the following considerations are strictly
speaking only valid for web based systems but the core idea should be easily
transferred to other types of systems.
All mentioned analytic packages provide a usage analysis of web-based systems
and they all distinct (in common) the following levels of a user interaction:
– Number of page views in a given time frame (typical within a hour, day, month,
etc.) as smallest entity
– Number of visits in a given time frame (a visit aggregates all page views produced
by the same visitor in a given time frame)
– Number of users (user of a web-based system with an account)
The cost producing usage is only induced in a web-system by pageviews. Nothing
else. From a cost perspective it is irrelevant whether 1,000 pageviews are produced
by 100 or 10 visits which can be assigned to 100, 10 or only 1 visitor (user). The
produced costs are the same. Nevertheless from cost estimation perspective it is
much easier to estimate users or visits than to estimate page views.14
9Which is not done in this paper due to page limitations. But the aggregation is analog.
10This is what every cloud service provider stresses as THE key benefit of cloud computing.
11http://www.google.com/intl/en/analytics/index.html.
12http://awstats.sourceforge.net.
13http://www.openwebanalytics.com.
14Think about a situation like, setting up a social network and you plan to orient on a platform like
facebook.com or linkedin. Facebook has something about five hundred million users, linked in has
200 N. Kratzke
We think that the above mentioned web-based usage parameters can be gener-
alized and that they are adequate for describing and compare usage characteristics.
They are all measured per month, due to the fact that underlying billing cycles of
cloud service providers are also made on a monthly interval.
– Number of requests reqs per month (generalized from page views) to a system
– Number of user interactions ints per month (generalized from visits) with a
system
– Number of active accounts accs in a month (generalized from users) of a system
– Number of unregistered users anons in a month (generalized from users) of
system
For cost estimation and inter- or extrapolation total numbers should be made
relative. So typically interactions per user ipu and cost driving requests per
interaction rpi are calculated. Especially for web-based systems these data can be
easily measured by using established toolings already mentioned above.
ipu WD anons Caccs
ints rpi WD reqs
ints
By having these indicatorswe can now map the core cost driver (requests) to the
usage data which is measured and billed by the cloud service provider. This is done
in Sect. 4.5.
4.4 Parameters to Describe Architectural Influence
The architecture of a cloud-based system influences massively the costs. For
example a system running on a single instance is likely to produce much less costs
then a massive parallel systems with a lot of instances. Nevertheless between these
extremes there exist hybrid forms and it is not always obvious which configuration
is more cost efficient.15
For first considerations a system can be described by a set of characteristic
parameters—for example the following ones:
– Total number of instances I
– Number of additional (autoscaling) instances IAS
– Number of running loadbalancers L
– Set of used services S
about seventy million users. But how many pageviews has Facebook or linkedin? Hard to estimate
or to research.
15For example answer yourself the question whether two high-performance instance systems are
more cost efficient than ten low-performance but load balanced ones? It is likely that your answer
is like: “It depends.”
Cloud Computing Costs and Benefits 201
So the above mentioned architectural description tuple seem adequate to compare
different cloud-based system architectures on a basic infrastructure level by the
following tuple .I; IAS ;L;S/. It is possible to define a similarity function to
compare two architecture description tuples .I1;I
AS1;L
1;S
1/and .I2;I
AS2;L
2;S
2/.
Two architectures are likely to produce the same cost characteristics if the have the
same amount of running instances load balancers and are using the same services.
This is expressible by the following function definition16:
similarity.I1;I
AS1;L
1;S
1;I
2;I
AS2;L
2;S
2/
WD 1
4I1C1
I2C1CIAS1C1
IAS2C1CL1C1
L2C1CjS1\S2j
max.jS1[S2j;1/
So two identical architectures will produce a similarity of 1. The more different
architectures are the more their similarity will move away from 1. Such similarity
functions can be used to filter most comparable systems with ex post data of a given
cost database (please compare Fig.5).
4.5 Using Cloud Service and System Usage As Well
As Architectural Description Parameters to Estimate Costs
So architectural parameters are used to filter most comparable systems out of a
given system space by using a similarity function (see Sect. 4.4 for an example).
We furthermore have identified the core cost driving parameter to a cloud-based
system—the request. So requests have to be related to the usage data and resulting
cloud costs. As it was mentioned in Sect. 4.2 the total costs can be calculated by
summing up service level costs17 or category costs:
TOTAL DNETWORKCOST CREQUESTCOST CPROCESSINGCOST
CDATA TRANSCOST CDATA STORAGECOST
Reflecting all made considerations it is now possible to calculate total cost
estimations for a planned or estimated number of users per month. The necessary
cost indicators are collected but measuring costs and usage characteristics of already
running cloud-based systems which are comparable in architecture (see Sect.4.4).
Please have the definitions of rpi and ipu in Sect. 4.3 in mind.
16 This is due to validation—it might be possible to use a completely different similarity function.
The presented function is only for exemplification purposes.
17TOTAL DIAASCOST CPAASCOST CSAASCOST .
202 N. Kratzke
TOTALestimate.user/DTOTAL
rrpi ipu user
PROCESSINGestimate.user/DPROCESSINGCOST
rrpi ipu user
STORAGEESTIMATE.user/DDATA STORAGECOST
rrpi ipu user
At the L¨ubeck University of Applied Sciences we use the presented approach
successfully in order to estimate cloud costs for the next semester.18
5 Conclusions, Outlook and Acknowledgements
For IT management investment decisions an ex ante rather than an ex post cost
transparency is needed. But ex ante cost estimation models do not exist so far and
have to be established and cross checked. We presented a cost estimation model
in its early research stages by using the strengths of cloud services (ex post cost
transparency) to provide missing ex ante cost transparency in order to improve
economical IT management decision-making for or against cloud based information
system solutions.
The presented approach is in its core idea quite simple but powerful.
– Measure service usage data of already running systems (costs for infrastructure,
scalability efforts and additional service usage).
– Measure usage characteristics (requests, interactions and user amounts).
– Analyse the architecture of a planned system and already running systems in the
cloud in order to find out the most comparable system by a similarity function.
– Deduce the most comparable real world systems to estimate the cloud cost of
planned systems by using their usage—as well as cost-indicators.
Thanks to Amazon Web Services for supporting our ongoing research in this field
with several substantial research as well as educational grants.
18The cost estimation is performed for lectures “Web Technology” and “Databases”. In both
lectures a varying amount of students over time have to pass practical exams in which they have
to set up and implement an interactive web presence or database intensive application. The system
usage characteristi c includes a 24 7 phase of 4 weeks. All necessary infrastructure is provided by
Amazon Web Services. By applying the mentioned cost estimation models we figured out to have
18.81 USD per student cloud costs per student. So if our next classes have 100 students we assume
1,881.00 USD for 100 students cloud costs for the next semester.
Cloud Computing Costs and Benefits 203
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