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infrastructures, adding a new 'external' dimension
of 'elasticity' to them by enhancing their 'home'
resource capacity whenever needed, on demand.
Existing businesses will use them for their peak
demands and for new projects, service providers
will host their applications on them and provide
Software as a Service, start-ups will integrate them
in their offerings without the need to buy resources
upfront, and setting up new social networks (Web
2.0 communities) will become very easy.
Cloud-enabling applications will follow simi-
lar strategies as with grid-enabling, as discussed in
the previous paragraphs. Similarly challenging as
with grids, though, are the cultural, mental, legal,
and political aspects in the Cloud context. Build-
ing trust and reputation among the users and the
providers will help in many scenarios. But it is
currently difficult to imagine that users may easily
entrust their corporate core assets and sensitive
data to Cloud service providers. Today (in Janu-
ary 2011) the status of HPC Clouds seems to be
similar to the status of Grids in the early 2000s:
a few standard and well-suited HPC application
scenarios run on Clouds, but many of the more
complex and demanding HPC applications in re-
search and enterprises will face barriers on Clouds
which still have to be removed. For example,
barriers may arise in the following context:
•
The process of setting up a service level
agreement.
•
Migrating your applications from their ex-
isting environments into the cloud.
And for that matter…
•
Do we all agree on the same security re-
quirements; do we need a checklist, or do
we need a federated security framework?
•
Do our existing identity, access manage-
ment, audit and monitoring strategies still
hold for the clouds?
•
What cloud deployment model would you
have to choose: private, public, hybrid, or
federated cloud?
•
How much does the virtualization layer of
the cloud affect application performance
(i.e. trade-off between abstraction versus
control)?
•
How will clouds affect performance of
high-throughput versus high-performance
computing applications?
•
What type of application needs what exe-
cution model to provide useful abstractions
in the cloud, such as for data partition-
ing, data streaming, and parameter sweep
algorithms?
•
How do we handle large scientific work-
flows for complex applications that may
be deployed as a set of virtual machines,
virtual storage and virtual networks to sup-
port different functional components?
•
The process of retrieving data from one
cloud and move them into another cloud,
and back to your desktop system, in a reli-
able and secure way.
•
The fulfilment of (e.g. government) re-
quirements for security, privacy, data pro-
tection, and the archiving risks associated
with the cloud.
•
What are common best practices and stan-
dards needed to achieve portability and
interoperability for cloud applications and
environments ?
•
The compliance with existing legal and
regulatory frameworks and current policies
(established far before the digital age) that
impose antiquated (and sometimes even
conflicting) rules about how to correctly
deal with information and knowledge.
•
How can (and will) organizations like
DMTF and OGF help us with our cloud
standardization requirements?
•
And last but not least, what if your cloud
service provider fails?
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