Clearing the Clouds
Understanding cloud computing
Ali Khajeh-Hosseini
S T
C L O U D
A N D R E W S
C O M P U T I N G
C O - L A B O R A T O R Y
Cloud computing
• There are many definitions and they all differ
• Simply put, cloud computing is a model for delivering IT as a
Service. Clouds refer to the actual data centres that house the
hardware and software
• US National Institute of Standards and Technology working
definition:
Cloud computing has
• Five characteristics
• Three service models
• Four deployment models
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Characteristics
1. On-demand self-service: you can start using computing
resources at anytime without needing human interaction
with cloud service providers. Computing resources can be
storage, processing, memory, network bandwidth, VMs...
2. Broad network access: you can access those resources over
the network using laptops, mobiles phones etc.
3. Resource pooling: the computing resources are shared by
multiple users (multi-tenancy)
4. Rapid elasticity: you can scale up or down the amount of
resources that you’re using very quickly
5. Measured service: resource usage is metered by measuring
your storage, CPU hours, bandwidth usage etc.
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Service Models
• Infrastructure as a Service
– Low level of abstraction, most flexible, dealing with
virtual machines
• Platform as a Service
– High level of abstraction, less flexibility, dealing with
your application code and your provider’s APIs
• Software as a Service
– Using software that others have developed and offer
as a service over the web
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Deployment Models
• Private cloud: controlled and used by one
organization
• Community cloud: used by several organizations
• Public cloud: available to the general public
• Hybrid cloud: mixture of the above, allows cloud
bursting
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StACC
• St Andrews Cloud Computing Co-laboratory
launched in April 09
• Local investment of about £0.5 million covering
– PhD Studentships
– Experimental hardware platform
– Technical support
• Our aim was to explore the research potential of
CC bringing together researchers in distributed
systems, high-performance computing and
systems engineering
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StACC Experimental Cloud
• The StACC private cloud is now operational
– 10 servers (Cloud controller, storage server, 8 * 4 core
general purpose servers)
– Running Eucalyptus open source software
• Objectives
– To understand what’s involved in setting up and running a
cloud (more than you might think!)
– To provide an experimental platform that we can measure
– To provide us with a platform that we can extend (and
break)
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Cloud Service Consumers
Software as a Service
Platform as a Service
Infrastructure as a Service
Private
Clouds
Public
Clouds
Is it cheaper?
Is it secure?
How will it effect my work?
Community
Clouds
Hybrid
Clouds
• We did an extensive literature survey to see if we can find out
the answers...
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Costs
• Should I lease or buy?
• Walker modelled the cost of a CPU hour when purchased as
part of a server cluster and compared it with Amazon EC2
• 2 scenarios, purchasing:
– a 60,000 core HPC cluster
– a compute blade rack consisting of 176 cores
• Model showed that it’s cheaper to buy in both scenarios
assuming that CPU utilization is very high and electricity is
cheap
• Good first step but far too narrow in scope, what about costs
of housing the infrastructure, installation and maintenance,
staff, storage and networking?
E. Walker, The Real Cost of a CPU Hour, 2009
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Costs
• Deelman et al. used simulation to calculate the cost of running a
data-intensive astronomy application on Amazon’s cloud
• Highlighted the potentials of using cloud computing as a costeffective deployment option for data-intensive scientific application
• Assumed the cost of running instances on AWS EC2 are calculated
on a dollar-per-CPU-second basis, i.e. they normalised the costs
• But, AWS charge on a dollar-per-CPU-hour basis and charge for a
full hour even for partial hours. So launching 100 instances for 5
minutes would cost 100 CPU hours
• Makes a significant difference in costs
E. Deelman, G. Singh, M. Livny, B. Berriman, J. Good, The cost of doing science on the cloud: the Montage example, 2008
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Costs
• Kondo et al. investigated the costs of using cloud computing
for desktop grid projects such as SETI@Home
• They found that deploying the servers used for the
SETI@Home project on Amazon’s cloud would cost 40% less
than using their university’s data centre
• Didn’t include upfront server purchasing costs or staff costs
• Cloud computing would look even more attractive if they did
D. Kondo, B. Javadi, P. Malecot, F. Cappello, D. P. Anderson, Cost-benefit analysis of Cloud Computing versus desktop grids, 2009
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Costs
• So is it really cheaper?
• Not really sure, it all depends on the specific
scenario and what you include in your
calculations
• We’re developing a tool to help users decide
for themselves...
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Security
• Security concerns are often mentioned in cloud
computing but not much research has been done to
address them
• The Cloud Security Alliance has published a set of
security guidelines in the form of problem statements
and issues that need to be considered by users
• Most concerns are about loss of control over physical
hardware which then lead on to legal issues...
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Legal Issues
• Most legal issues are related to the cloud’s physical location, which
determine its jurisdiction
• Amazon have data centres in 2 regions (US and Europe) so they can deal
with these issues
• But the cloud’s nature means that users don’t know (or care) about this
information: “it’s all in the cloud”
• Location is important because cloud computing increases the control of
governments and corporations over resources*. Cloud computing brings
together vast amounts of data and computing resources in centralised
data centres, compared to how they are currently hosted in geographically
dispersed locations
• It’s unlikely that these jurisdiction issues will stop the use of cloud services
* P. T. Jaeger, J. Lin, J. M. Grimes, S. N. Simmons, Where is the cloud? Geography, economics, environment, and jurisdiction in cloud computing, 2009
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Effects on Work
• How will cloud computing effect the work of
IT departments?
• Their authority has been diminishing over the
last few decades, from mainframes to PCs
• Cloud computing is going to decrease their
authority further
• Users are turning into “choosers”* who can
replace the services provided by the IT
department with service offered in the cloud
* R. Yanosky, From Users to Choosers: The Cloud and the Changing Shape of Enterprise Authority, 2008
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Case Study
• To study these issues, we performed a case study
examining the relative costs of migrating from a
locally provided host to a host provided on Amazon
• The system studied was a fairly small data acquisition
IT system from the Oil & Gas industry. The system
had a contract value of £104,000 and was deployed
in a local data centre
• Our focus was socio-technical – what are the human
and organisational issues that influence such
decisions
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Case Study
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Case Study
• Infrastructure costs over 5 years
In-house
Cloud
£57,000
£25,000
• Around 55% cheaper
Support Issue
• 218 support calls over 5 years
• 20% of them would be eliminated
• Backup, power and network issues would be Amazon’s responsibility
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Interviews
• We took these findings and presented them to various people
in the company and interviewed them
• Technical manager:
–
–
–
–
It looks attractive
We would lose leverage over support contracts
Concerned about security and protection of virtual machines
Some corporations veto data going over port 80
• Support staff:
– Very negative about cloud computing
– Feel threatened
– Don’t want to lose control over hardware
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Interviews
• Project manager:
–
–
–
–
Hard to sell this idea, there’s no data centre to show clients
Difficult to alter corporate security policies
Easier to manage cash flow
Reduces required skill-set and overheads
• Business development manager:
– We are under pressure to reduce electricity usage
– It presents new opportunities for us, e.g. running training
courses in the cloud
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Decision Support System
• Cloud computing has sparked a huge interest in the IT industry
• Many organizations are thinking about migrating their systems
to the cloud. During this period, many migration decisions need
to be made, what to keep in-house, what to migrate
• These aren’t simple decisions and there are a range of issues
that need to be considered when making these decisions:
economic, technical, organizational, risks etc.
• We are developing a decision support system to help people
make those decisions…
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Summary
• Cloud computing is still in its early days
• We are currently at the start of a transition
period, the shift towards cloud computing
could take many years
• Not much research has been done about
issues effecting cloud service consumers
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