based on domains comparison in two dimensions:
breadth and depth. The breadth dimension focuses
on conducting the analysis according to the
organizational structure, inventorying existing
activities and R&D development processes. It
considers the cloud computing company culture and
hype, when constructing the survey. The depth
dimension analysis is focused on providing a
description to the potential services, and preparing
them for the survey.
The breadth dimension supports identification of
the main research field characteristics. Here we
identified five main characteristics that influence the
quality of knowledge gathered in the context of
Cloud Computing:
(1) Organizational Analysis - including
identifying the company’s business units that may
affect the cloud computing proposed services based
on their known problems and needs, by interviewing
chief architects. In our case a total of seven
architects were interviewed.
(2) Inventory of existing activities within the
company that have a cloud terminology associated
with them, including potential patents. This phase
included working with the patent office and business
unit.
(3) Existing R&D development processes that
consider cloud issues. These included in our case the
Top Level Design Specifications of proposed
projects, the Product Marketing Documents
development, and strategic work on virtualization.
The technological community as a whole was
involved in gathering these data points. This phase
included 24 interviews.
(4) Cloud Computing interest groups were
engaged. Specifically, we investigated the cultural
and hype activities in the company occurring within
the technical community, including technology-scan
documents, cloud interest groups, internal IT
department and overall thought leadership around
the cloud.
(5) Survey construction that contains the above
dimensions mapped onto specific services coupled
with skeleton examples. The survey questions were
organized to more than 50 proposed IT services for
the cloud (ITS4C such as federated security service,
service optimizer, service analytics, service
orchestration, etc.) to cloud players (provider,
consumer, broker, developer), cloud types (internal,
private, hybrid, public), as well as deployment
methods (on and off-premise). The survey enabled
participants to skip services not in their interest, add
free comments, and indicate their level of expertise
in a specific ITS4C. In addition, we codified the
perceived market maturity for accepting a certain
solution, and the difficulty in implementing it. More
than 120 participants completed the survey across
the company. The results of this survey are beyond
the scope of this paper and will not be presented
here.
(6) Previous corporate work was inserted as a
disruptive analysis dimension. We scanned previous
recommendations, or topics suggested, and
considered how these different vectors might affect
the overall depth of each proposed service, and how
it might change the results’ aggregation. We
considered the company’s software-as-a-service
strategy, Alternative Delivery Methods strategy, and
emerging and global trends.
The depth dimension supports analysis of each of
the domains. We employed the following three
levels (based on Levy et al. 2009):
(1) Descriptive – the potential conceptual
service offering and proposed solution is defined by
a theoretical description. This was used when the
services proposed did not have existing
implementations to the best of our knowledge.
(2) Procedural and Sequential – a sequence
and example approach, where the solution is defined
by a ‘step by step’ analysis, usually comprising a
more granular approach to the “Descriptive”
dimension, based on either written or defined
invention disclosers, or other forms of commented
analysis such as from the standard organizations.
Examples may be cloud bursting scenarios,
provision servers to satisfy seasonal or temporary
needs, and cloud to cloud backup.
(3) Practical and existing – the method
provides elicitation and analysis of existing solutions
done by competitors, ones that exist within the
company or under development. Example are cloud
data backup, existing infrastructure renting, and
sales and client relationships management services.
Phase 3: Initial Analysis
The domain analysis players, stakeholders, and
categories are organized into four domains of
players (consumers, providers, brokers, developers)
coupled with the four types of clouds (Internal,
Private, Hybrid, Public). Accordingly, we observed
11 IT concerns. as displayed in Figure 1 (assets,
location, cost model, software development,
network, hardware, capacity, identity, data, process,
liability and risk), and their relevant characteristics
in traditional datacenters, outsourcing and cloud
environments. SEK considers all dimensions when
analyzing the different ITS4C services and
consequently, their technical possibilities
Phase 4: Data Collection and Interviews
Non-structured interviews and structured survey
defines the aggregation of proposed technology and
solution into buckets. Refinement and changed to
buckets is done and reviewed by a steering
committee. The interviews were performed in an
CLOSER 2011 - International Conference on Cloud Computing and Services Science
262