Towards Living Landscape Models: Automated Integration of Infrastructure Cloudin Enterprise Architecture Management

Matthias Farwick, Berthold Agreiter, Ruth Breu

Institute of Computer ScienceUniversity of Innsbruck,

Innsbruck, Austria{matthias.farwick,berthold.agreiter,ruth.breu}@uibk.ac.at

Matthias Haring, Karsten Voges, Inge Hanschke

iteratec GmbHMunich, Germany

{matthias.haering,karsten.voges,inge.hanschke}@iteratec.de

Abstract—Enterprise Architecture Management (EAM), andin particular IT–landscape management try to model the IT-and business elements of a company, in order to analyze its effi-ciency towards supporting business goals, optimize business–ITalignment, and to plan future IT–transformation as well as IT–standardization. A major challenge in this field is the elicitationof infrastructure information from run–time systems, e.g., toanswer the question which servers provide services to a specificinformation system. Capturing this data is a time consumingmanual task which leads to quickly outdated information.Similar to traditional hardware, cloud infrastructure needs tobe documented in an EA model in order to gain insight on itsrelationships with business information systems and ultimatelythe business goals. The aim of our research in this areais the automatic integration of various runtime informationsources into an EAM view. The overall goal is to minimizemanual work to keep enterprise architecture information up–to–date. This enables enterprise architects to make timely andprecise decisions. In this work we focus on how informationon the cloud infrastructure can be seamlessly integrated intoan EA view. Making the cloud visible for enterprise architectsis especially important to meet legal (privacy) requirements,on the storage and processing location of data. We presenta conceptual approach for the information integration prob-lem, and introduce our prototypical implementation with theopen–source infrastructure cloud implementation Eucalyptus,and the open–source enterprise architecture management tooliteraplan.

Keywords-infrastructure cloud; eam; it–management; cloudcomputing; cloud api; it–landscape modeling; enterprise archi-tecture management; open-source; iaas

I. INTRODUCTION

Enterprise Architecture Management (EAM) is an often

used practise in mid-sized to large organizations to align IT

and business goals, to assess risks, and to check compliance

with legal regulations. EAM helps to discuss and clarify

business processes and procedures and aims to visualize

the relationships among regulations, business processes,

software and the underlying infrastructure. This practice

achieves transparency over the IT–landscape, enables man-

agers to see how business and IT interrelate, and where the

This work was partially supported by the Austrian Federal Ministry ofEconomy as part of the Laura-Bassi – Living Models for Open Systems –project FFG 822740/QE LaB

mutual dependencies lie [8]. It is typically conducted by

people within one organization having different technical

and non–technical backgrounds. Hence, it brings together

experts to (i) analyze the current situation regarding the

aforementioned topics, and (ii) to define requirements and

plans for future standardization and changes. These planned

changes to the IT–environment, however, are mostly exe-

cuted in an unchecked manner by specialists and their status

is often not synchronized with the enterprise architecture

model.

IT–landscape modeling, as a sub–area of EAM, tries

to assess the IT–landscape of an organization to bring it

into relation with the information systems that ultimately

support the actual business functions. EAM tools support the

modeling of the IT–landscape, however the creation of these

models is a time–consuming task. Furthermore, the problem

that the manually created landscape models are often quickly

outdated persists also here.

To date, there exists no automated method to keep land-

scape models up–to–date. Certainly, current and consistent

information about the as–is landscape is needed in order

to come to the right business- and technology-decisions for

future changes.

Seen from another perspective, increased IT efficiency

and minimized costs are these days often promised by

shifting certain parts of the own IT infrastructure into public,

private or hybrid clouds. Infrastructure cloud computing,

also referred to as Infrastructure as a Service (IaaS), is

aimed at realizing higher utilization rates with less over-

provisioning, which means that money is only spent for

infrastructure that is actually used. Furthermore, it allows

for fast infrastructure changes when the business requires it,

because of its on demand availability. Clouds allow for self–

service provisioning through APIs, bringing a higher level

of automation and reducing management costs [16].

The lack of synchronicity between the planned enterprise

architecture model and real architecture persists also in

the case where cloud infrastructure is used to support an

organization’s own IT infrastructure. Hence, the question

we are tackling in the present contribution is: how can

infrastructural runtime information about cloud instances be

2010 IEEE 3rd International Conference on Cloud Computing

978-0-7695-4130-3/10 $26.00 © 2010 IEEE

DOI 10.1109/CLOUD.2010.20

35

integrated into enterprise architecture models in an auto-

mated way? This question is an integral part of the three

main problems that we try to solve in our research project

Living IT–landscape Models:

1) How can enterprise IT–landscape models be auto-

matically kept in–sync with the IT–landscape they

represent, and

2) how can this be achieved for (private) infrastructure

clouds that are emerging in many organizations?

3) Also, how can this automation be integrated into typi-

cal IT–infrastructure planning processes in enterprises.

It is the overall goal to minimize manual work to keep

enterprise architecture information up–to–date. In this paper

we focus on how planned and unplanned changes to the

cloud infrastructure can be automatically updated in an EAM

view. This helps IT architects to have an overview of the

current cloud infrastructure for decision making.

A. EAM and the CloudSimilar to traditional hardware, cloud infrastructure needs

to be documented in an EA model in order gain insight

on its relationships with business information systems and

ultimately the business goals. Figure 1 shows an extremely

simplified enterprise architecture model, that includes a

private and a public infrastructure cloud. It contains three

common layers of EA models: the business architecture

layer, the information system architecture layer and the

infrastructure landscape layer. These layers can, for example,

be found in the best-practice enterprise architecture by

Hanschke [8]. Via the visualization of the interconnection

between elements of these layers, enterprise architects can

immediately see which business functions are provided by

which application, and where the applications are hosted. In

the given example, one can see that the brokering application

is hosted both in the private as well as in the public cloud.In addition to the basic requirement of the coupling of EA

and infrastructure, several other motivating factors can be

identified. For example, making the usage of clouds visible

for higher–level management, highlights the advantages of

utilizing the infrastructure cloud by pointing out infrastruc-

ture simplification and cost savings. It thereby strengthens

proponents of cloud initiatives in the enterprise by showing

the return on investments. Also, cloud infrastructure is much

more volatile than traditional hardware infrastructure. There-

fore, it is important to couple EAM and cloud management

to form an IT–governance approach that controls change

processes in the cloud.Further, it is important to make cloud computing visible to

enterprise architects to be able to monitor compliance with

laws and regulations. For instance, regulations might prohibit

the storage of private data in a public cloud, as it can be seen

in Figure 1. An example for such a regulation is the EU Data

Protection Directive 95/46/EC1, which restricts the export of

1http://ec.europa.eu/justice home/fsj/privacy/index en.htm

private data, to non–EU countries that do not comply with

the data protection standards of the European Union. Non–

compliance to such regulations can lead to monetary loss,

as well as loss in trust by customers.

Datacenter

Private CloudPublic Cloud

BrokeringApplication

BrokeringBusinessFunction

OnlineBankingApplication

Online BankingBusinessFunction

supports supports

InfrastructureLandscape

InformationSystem

Architecture

BusinessArchitecture

hosted on hosted on

Figure 1. Example of simplified EAM model instance.

The need for this kind of integration has been identi-

fied by researchers and practitioners alike. For example,

Frank et al. [6] propose the integration of an EAM view

with the underlying IT–landscape to elicit Key Performance

Indicators (KPIs) from the runtime. On the practitioners

side, mainly IT–consulting firms and tool vendors, have

identified the need for cloud and EAM integration. In his

online article2 Wolfgang Jost, member of the executive

board of IDS Scheer AG3, states that Cloud Computing

in the enterprise can only work with the precise planning

of enterprise architecture management. The Oracle white

paper on cloud computing [3] argues that EAM helps to

more efficiently align business and IT with cloud computing.

In his blog the IT–consultant David Linthicum argues that

“Cloud computing needs governance to be successful”4.

Also, consulting agencies give high–level advice on how

cloud infrastructure should be managed [13]. However, there

currently do not exist sophisticated tools or methods to

support a cloud and EAM integration.

B. Contribution

In this work we present a method and a prototypical

implementation to integrate several management tools, to

keep them in–sync with the cloud infrastructure. These

management tools are an enterprise architecture management

tool (iteraplan5), and a project portfolio management tool

2http://www.computerwoche.de/software/soa-bpm/1928049 (in german)3IDS Scheer AG is one of the leading vendors of EAM tooling.4http://www.infoworld.com/d/architecture/cloud-computing-needs-

governance-be-successful-7575http://www.iteraplan.de

36

(project.net6). As the underlying infrastructure cloud we

use the open–source infrastructure cloud implementation

Eucalyptus [14], which implements the same API as the

Amazon EC2 Web Services (AWS). All components are

indirectly connected via a central model, that provides model

versioning. To the best of our knowledge no automated

approach has been documented in literature that enables the

coupling of EAM and underlying IT–infrastructure in gen-

eral, and none that enables this automation for infrastructure

cloud in specific.

C. Structure

The remainder of this paper is structured as follows: the

next section briefly expands on our overarching vision of

Living Models in the enterprise and how we plan to make

most use of such models. After that, Section III presents a

usage scenario highlighting the challenges of this contribu-

tion. Section IV describes our approach for integrating cloud

data into EAM by detailing our prototypical implementation.

In Section V the update mechanism is described. Section VI

presents related work and Section VII concludes.

II. THE VISION OF LIVING MODELS

One of the key deficiencies in most of the current

modeling methodologies and modeling applications is the

unsatisfactory integration of model instances with the run-

time environment. I.e. current modeling approaches fail in

automatically keeping model elements in–sync with what

they represent in the real world. For example, models of

a server landscape need to be manually updated when a

new server is started up, or legacy hardware is faded out

of production mode. Roundtrip–engineering approaches go

a step in the right direction, however, integration halts at

the source code level and does not allow for feeding back

runtime information into models. In the course of the project

Living Models for Open Systems and its sub–projects we

investigate on the tight coupling of models with runtime

artifacts, such as business process models, security(-policy)

models, SOA models, as well as enterprise and IT–landscape

models. In [5] we define the ten principles of our future

vision of Living Models. Living models specifically tackle

the particular challenges for handling changes in evolving

systems. The principles of living models are summarized in

Table I.

The contribution at hand specifically focuses on

stakeholder–centric modeling environments (P1) by devel-

oping extensions for an enterprise architecture and project

management tool, thereby creating a view for two spe-

cific stakeholders. The implication is that IT architects

and technical project managers always possess up–to–date

information, that is in–sync with the cloud architecture of

the enterprise. For example, enterprise architects can always

correctly answer the question which information objects

6http://www.project.net

ID Living Models Principle DescriptionP1 Stakeholder–Centric Modeling Environments.P2 Close Coupling of Models and Code/Runtime.P3 Bidirectional Information Flow between Models

and Code/Runtime.P4 Common System View.P5 Persistence.P6 Information Consistency and Retrieval.P7 Domains and Responsibilities.P8 Model Element States.P9 Change and Change Propagation.P10 Change–Driven Process.

Table ITHE TEN PRINCIPLES OF LIVING MODELS ACCORDING TO [5].

are stored in the cloud and which information systems are

hosted in the infrastructure cloud. Additionally, we propose

a methodology for the close coupling of models and runtime

artifacts (P2) and the support of a bidirectional information

flow between models and the runtime (P3). This is realised

with the help of a common system model capturing all

information available and bringing it into relation with

each other (P4). Living Landscape Models allow for tight

coupling of the EAM tool, the project management tool

and the cloud architecture. This directly tackles the syn-

chronicity problem between EA models, resp. key figures

relying thereon, and the infrastructure. Furthermore, also

project management information is automatically pushed to

the EAM tool which allows IT architects to have insight into

current and planned projects so decisions are made with the

most current information.

III. USAGE SCENARIO

The aim of IT–landscape management is to assess

the current state of the IT–landscape, and among others,

the target–focused planning towards a structurally and

technologically consolidated infrastructure landscape. We

now proceed with giving a typical scenario of planned

infrastructural change in an enterprise that needs to be

supported by tooling.

The banking–group XYZ–banking wants to give their

professional brokering customers a faster real–time

brokering experience within their existing brokering

application. As the enterprise architects assess the

corresponding IT–landscape in their EAM tool, they

realize that the server–cluster, which is responsible for the

brokering application, has already reached its maximum

capacity, is accessed with an outdated message format, and

would be costly to extend. They decide that the new backend

IT–architecture will reside in their private infrastructure

cloud. This is in accord with the longtime standardization

effort of the enterprise towards homogeneous usage of the

private infrastructure cloud. The IT architects decide that

some, security and privacy in–sensitive, computations can

be offloaded to a public infrastructure cloud at peak times.

37

However, they recognize that the transition from the old

architecture to the infrastructure cloud needs to be precisely

planned to be successful.

During the planning effort by the systems operation

team, a new infrastructure change project is initiated in the

project management tool of the company. The high–level

information on this project, like the planned cloud instances,

is automatically forwarded to the EAM tool over a central

integration component. Hence, this information is immedi-

ately visible to the enterprise architecture stakeholders.

As the systems operation team executes the project

plan to create new cloud instances (e.g. using a cloud

administration tool like Elasticfox7) the cloud instances

are tagged with the IDs that were assigned to them during

the planning phase. Once the instances in the private and

public cloud are started up, they are recognized by the

central component as running. From this information, the

integration component can inform the EAM tool, that the

originally planned cloud servers have been started up,

i.e. their status changes from PLANNED to CURRENT.

This way the EAM stakeholders always have a high–level

overview of the status of each cloud component. Since

the status of the planned servers is also updated in the

project management tool, the systems operation team is

also informed that the new brokering application can finally

be deployed to the production environment.

By this precise planning and monitoring, XYZ–banking

manages to switch the underlying IT–landscape of the bro-

kering application from a legacy server–cluster to an elastic

infrastructure cloud, that corresponds to the longtime stan-

dardization roadmap of the enterprise, without significant

downtime.

IV. APPROACH TO AUTOMATED CLOUD INTEGRATION IN

EAM

As mentioned before, our approach to automatically in-

tegrate information about running infrastructure cloud in-

stances, is part of a larger effort to integrate various runtime

information sources into an EAM view. In our solution, this

integration is achieved by a central model which receives

model updates from various sources, and pushes new, veri-

fied information to the EAM view. This central model will

be further discussed in Section IV-A2. With this setup we

follow the approach by Fischer et al. [1] who state that each

stakeholder in an enterprise (e.g. systems operation, project

management, etc.) needs their own set of tools, i.e. views

on the enterprise model, with which they are familiar. The

opposite approach would be to create a tool that caters for

the needs of all stakeholders at once. This, however, would

entail that all users need to get accustomed to a new generic

tool, which would lead to productivity loss. Therefore, we

7http://sourceforge.net/projects/elasticfox/

aim to only extend existing industry standard tools with

integration support.

Figure 2. Automated information flow to EAM tool. The informationsources relevant to this publication are colored in grey.

Figure 2 shows this federated approach. In this work, we

focus on the communication solution for the components

in Figure 2 that are colored in grey. It shows three layers,

of which the topmost represents the management view that

is constituted by an EAM tool. Information from lower

layers is first synchronized with a central repository. The

data–structure of this repository is based on an extensible

meta–model and capable of expressing all information that

is important to the management view of a specific enterprise.

The consolidated data from the lower layers is then pushed

from the central model to the EAM tool. The middle layer

contains information sources that can be summarized as the

systems operation information sources. Data from this layer

that is communicated to the central model can be character-

ized by the fact that it is not information coming directly

from the runtime, but is rather data that is entered/created by

operation personnel. This could, for example, be information

on ongoing infrastructure change projects that are planned

in a project management tool, or data that has already

been (possibly automatically) gathered in a Configuration

Management Database (CMDB) [12]. The bottom layer

shows information sources from the runtime that can be fed

into the central model. These can be, for instance, business

process engines, applications and hardware that have agents

deployed to them, or, as in the case of this publication, cloud

infrastructure that actually exposes an interface which can

be queried for the current state of cloud instances.

A. Prototypical Implementation Architecture

The major challenge for the implementation is the

synchronization of the different technologies and

applications involved. Figure 4 shows the basic setup

of our approach – each component will be further explained

38

Figure 3. The open–source enterprise architecture management tooliteraplan.

in the following subsections. In the center of the figure

is the central model controller. It handles the access and

changes to the model in the model repository. Other attached

components can push model changes to the model controller

via the provided Web service interface. This interface is,

for example, used by the project portfolio management tool

project.net, that we extend to push information on planned

infrastructure change projects to the central model. On a

regular basis, the central model controller polls the public

and the private cloud interfaces, which are drawn on the

lower left, to find out whether new instances have been

started up, or instances have been terminated. This queried

information is then compared with planned changes to the

infrastructure. The duration of this interval should be chosen

according to the frequency of changes within the cloud

infrastructure. For some organizations, a daily poll might

be sufficient, for others, however, a much smaller interval

is advisable. The top of Figure 4 shows the open–source

EAM tool iteraplan that we extend, in collaboration with

our partner company iteratec, with a Web service interface

to push changes that occur in the systems operation layer

or in the runtime layer to this EAM view. The lower right

corner of the figure shows a possible future extension

towards agents that are installed on hardware to report the

state of the machines to the central model.

1) Tagging Cloud Instances with enterprise–wide IDs:To test our approach we use the open–source infrastructure

cloud implementation Eucalyptus, which exposes the same

WSDL8 interface as Amazon EC29. Because this interface

is seen by some as the emerging standard API for the

infrastructure cloud [14], and it works for a private cloud

8http://www.w3.org/TR/wsdl9http://aws.amazon.com/ec2/

with Eucalyptus as well as for a public cloud with EC2

we use it for our implementation. However, in the future a

generic cloud API wrapper, like the one proposed by Harmer

et al. [9] could be used as well, to allow for the usage of

different cloud providers. For our setup we use one CloudController installed on a laptop as well as several NodeControllers, also installed on laptops.

In our approach all infrastructure elements have a UUID

(Universally Unique Identifier) assigned to them, as soon as

they are planned in the project management tool. This way,

once it is signaled to the central model that an instance,

tagged with a planned UUID, is running, it can be inferred

that a planned infrastructure element changed its status from

PLANNED to CURRENT.

A major problem we faced with the Amazon EC2 API was

that it does not directly provide a method to tag instances

with user–defined tags or IDs. Global IDs for cloud instances

are necessary in our approach, since they allow for globally

identifying cloud instances, in order to represent their status

in the EAM tool. This is needed to find out whether a

newly started instance corresponds to a planned instance.

Cloud management tools like Elasticfox provide tagging

functionality, however they store the tags locally, so they

are not globally available.

For this reason we utilize a workaround via security

groups to tag instances with IDs, as proposed in [15].

This is achieved by assigning security groups without any

added permission to a new instance that should be created.

This way, instances are tagged with security groups, but

no changes to permission assignment are done. With this

approach, however, care has to be taken not to assign the

same security group UUID to two different instances.

Security groups can be created and assigned to instances

on startup with graphical interfaces like Elasticfox or via

the Eucalyptus/EC2 commandline tools:

$ euca-add-group "UUID:123" -d "Global ID".

A new instance with this UUID can then be started with

the ID via:

$ euca-run-instances ami-bgf54s6g --instance-type

m1.medium --key keypair --group default --group UUID:123.

The new instance is now tagged with the security group

named “UUID:123” that does not add any extra restrictions

on permissions of the instance. This way the the global ID

of the instance can be stored in the cloud and be retrieved

and parsed, e.g. via

$ euca-describe-instances.

Of course, this is only a workaround. Amazon has identified

the need for a tagging mechanism which stores the tags

in the cloud, however, at the editorial deadline it was not

available.

2) Central Model Controller: In our approach, all

changes that happen in the infrastructure and the systems

39

Private Infrastructure Cloud

Cloud Nodes (Running Eucalyptus Node Controllers)

Eucalyptus Cloud Controller

Public Infrastructure Cloud

Amazon EC2

EAM Tool (iteraplan)

Iteraplan WSDL/REST API

Eucalyptus EC2WSDL API

Amazon EC2WSDL API

Traditional Data Center Hardware withAgents (Future Work)

Data Center Hardware

Model WSDLAPI

Project PortfolioManagement Tool(project.net)

Pull instance IDs

Push plannedcloud changes,e.g. creation ofnew instance withUUID XYZ.

CentralModel

ControllerModel

Repository

Pull instance IDs

Push changes toEAM view

Figure 4. Infrastructure cloud EAM integration architecture.

operation layer are either pushed to the central model on

change events, or are pulled by the central model controller

in regular intervals. The central controller implements a

WSDL interface that allows other components to update the

central model. The implementation builds on a co–project

called MoVE (Model Versioning and Evolution). This

model repository provides for model versioning and roll

back of EMF10 models, as well as the evolution of models

and the corresponding metamodels. It provides us with

the basic means to tackle transaction problems, and the

evolution of the underlying metamodel while the actual

model instance is already existing. More details about this

tool can be found in an accompanying publication [4].

3) EAM view with iteraplan: The web–based application

iteraplan is the first open–source enterprise architecture

management tool. Its source code has been contributed

by our partner, the consulting company iteratec, which

continues to contribute further development. Figure 3 shows

the web interface with its underlying extensible metamodel

for enterprise architecture. For our approach to combine

iteraplan with the infrastructure cloud we develop a Web

service interface that allows for the remote manipulation of

10http://www.eclipse.org/emf

IT–landscape data in the iteraplan datastore.

V. CHANGE SCENARIOS

In the preceding section we discussed the components

that are involved in a planned cloud infrastructure change

process. In this section we will expand on concrete change

scenarios that relate to the usage scenario of Section III.

Figure 5 shows an UML sequence diagram visualizing the

timing of actions, and messages between the interfaces in a

planned and unplanned change scenario of the infrastructure

cloud.

As in the usage scenario, the planned infrastructure change

project is first discussed by the enterprise architects and

then submitted as a new project to the project management

tool (steps 1 & 2). On this submission, the tool forwards

the project information to the central model controller in

step 3. In the following, the central model forwards these

new planned infrastructure elements to iteraplan and also

creates a new project within the EAM tool. According to

an automated interval, the controller polls the private cloud

for new instances that have been started up (steps 5 & 6).

However, it discovers in step 7 that no new and unknown

instances have been created by the cloud management team

since the last poll. In step 8, the cloud management team

starts up new instances with the UUIDs according to the

40

plan defined in the project management tool (step 8 &

9). At the next polling interval the controller notices the

new instances (steps 10 – 12) and compares them with the

planned instances. Once it finds an instance whose state

has the PLANNED status, it updates its status in the EAM

view to CURRENT. If the UUID of a new instance cannot

be identified as planned, steps 14 and 15 are executed. In

step 14 a manual check needs to be executed since the

new instance does not correspond to any planned instance.

Staff from the systems operation team could either decide

that the instance is not important for the EAM stakeholders

(e.g. it is a test server that has a short life span), or decide

to push the enriched information on this new infrastructure

element to iteraplan (step 15).

This walkthrough showed a possible execution of a

planned infrastructure change that is automatically signaled

to the EAM view. The same polling mechanism can detect

deleted cloud instances, by comparing the retrieved instance

UUIDs with the UUDIs marked as CURRENT in the central

model. However, it also reveals, that in some cases human

intervention is still necessary. Another case in which human

intervention is needed, is the case when a new instance

is started up, but is not in production mode. This can

only be detected by a human so far. Therefore, we further

investigate on notification mechanisms that allow for quality

assurance of the automated updates via human checks.

VI. RELATED WORK

To the best of our knowledge no automated approach

has been documented in literature that enables the coupling

of EAM and underlying IT-infrastructure in general, and

none that enables this automation for infrastructure cloud

in particular. Nonetheless, there exist several works in the

literature which discuss related topics.Similar to our approach, the work on orthographic mod-

eling by Atkinson et al. [2] describes a single underlying

model with an extensible meta model to which views can

be defined for different stakeholders. However, opposed to

our work the authors focus on software engineering and

model-driven development instead of enterprise architecture.

In their work on federated Enterprise Architecture Fischer et

al. [1] describe a federated approach to EAM with a central

model, for which information is manually gathered. They

see the automation as possible future work. Frank et al. [7]

state that their enterprise modeling language (ITML) can

be transformed into enterprise specific database schemas in

order to built management tools that represent instances from

the runtime in these tools. However, they neither describe

how this integration can be achieved automatically, nor

manually. In a different publication Frank et al. [6] propose

a modeling language to define Key Performance Indicators

that should be calculated from information that has its origin

in the runtime. The automation of this information retrieval

is left as future work. In another publication Holmes et al.

[11] describe a method to create a model–aware service

environment that allows Web–services to communicate with

a model repository that contains the model elements that

represent the services. This work is related to our publication

since Holmes et al. try to integrate the modeling environment

with the runtime. Head et al. [10] use the network discovery

tool nmap to elicit runtime information from a company’s

infrastructure to enable quick remote infrastructure manage-

ment (RIM) for specific infrastructure elements.

VII. CONCLUSION AND FUTURE WORK

In this contribution we have shown, that the need for

integrating enterprise architecture management with infor-

mation from actually running systems has been identified

both by researchers and practitioners. Enterprise architects

need an up–to–date view on the usage of infrastructure

clouds, in order to oversee e.g. compliance with (privacy)

laws that regulate the storage location of data, such as the

EU Data Protection Directive. As the first step towards

this integration, we present an approach towards automated

integration of the open–source EAM tool iteraplan and

private or public infrastructure cloud. This integration is

achieved via push and pull protocols to and from a central

model, that is also synchronized with a project management

tool to distinguish between planned and unplanned changes

on the cloud infrastructure.

As this work is embedded within a larger project towards

integrating many runtime information sources into an EAM

view, we still face several open issues and multiple areas of

future work.

A. Future Work and Open Issues

Most importantly, we will continue to implement and

evaluate the cloud integration approach described in this

work. We will also consider the usage of generic cloud APIs

and closely observe cloud standardization efforts. We will

also investigate on how the models of Platform as a Service

(PaaS) and Software as a Service (SaaS) can be integrated

into our approach. Another focus of future research will

lie on the central model and how synchronization issues

and metamodel evolution can be handled. The largest effort

will be put into the integration of various other runtime

information sources, e.g., by installing agents on systems

to report performance metrics as well as the status of in-

stalled applications from systems back to the central model.

These agents could, for example, already be pre-installed

on machine images that are started as cloud instances and

support the collection of utilization data.

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Figure 5. UML sequence diagram showing the communication of the different components in a planned and unplanned infrastructure cloud changeprocess.

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