"A view of Cloud Computing" article presentation

1. A View of Cloud
Computing
ASLI YAZAĞAN
IS 748 Cloud Computing
8 May 2013
Michael Armbrust, Armando Fox, Rean Griffith, Anthony D. Joseph,
Randy Katz, Andy Konwinski, Gunho Lee, Dav id Patterson, Ariel
Rabkin, Ion Stoica, and Matei Zaharia
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2. Article Goals
• To clarify terms
• Identifying top technical and non-technical
obstacles and opportunities of Cloud
Computing.
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3. Outline
• Definitions
– Cloud Providers and Users
– 3 Example of Cloud Services
– Cloud Economics
• Top 10 Obstacles and Opportunities for Cloud
Computing
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4. Definitions
• Cloud Computing
• Saas, IaaS, PaaS
• Cloud
• Private Cloud
• Public Cloud
• Utility Computing
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5. Cloud Computing
1. Applications delivered as services over the
internet (SaaS)
2. The hardware and system software in the
data centers that provide those services
According to authors, IaaS and PaaS are alike
than different.
“Low level infrastructre” ~ “Higher level platform”
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6. Cloud Computing vs.
• Utility computing is the packaging of computer resources,
such as computation, storage and services, as a metered
service.
• The technique of running a single calculation on multiple
computers is known as distributed computing.
• Grid computing is a particular form of distributed
computing, where the supporting nodes are geographically
distributed.
• Cloud computing is where an application doesn't access
resources it requires directly, rather it accesses them
through something like a service.
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7. Public - Private Cloud
• Data Center hardware and software is called cloud.
• Public Cloud: A cloud is made available pay-as-you-
go manner.
• Private Cloud: Internal data centers and businesses
or other organizations when they are large enough to
benefit Cloud Computing.
• Utiliy Computing: The services being sold.
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8. Cloud Computing - Redefined
1. SaaS (Applications delivered as services over the
internet )
2. Utility Computing (The hardware and system
software in the data centers that provide those
services)
 Does not include small and medium sized data
centers.
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9. Users and Providers of CC
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10. 3 Aspects of Cloud Computing
• Infinite capacity on demand
• No upfront commitment
• Short- term usage
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11. Two Scenario
• 1. Consider a public-facing Internet service hosted on an ISP
who can allocate more machines to the service given four
hours notice.
• 2. Consider an internal enterprise data center whose
applications are modified only with significant advance notice
to administrators.
Since load surges on the public Internet can happen much more quickly than
that. This is not cloud computing.
Large load surges on the scale of minutes are highly unlikely, so as
long as allocation can track expected load increases, this scenario
fulfills one of the necessary conditions for operating as a cloud.
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12. Classes of Utility Computing
• Computation, Storage, Communication Model for an
application is necessary.
• Utility Computing offerings will be distinguished
based on
1. the cloud system software’s level of abstraction
2. the level of management of resources
To meet the
needs of
applications in
cloud
Elasticity
The Statistical
Multiplexing
Infinite resources
Automatic
allocation and
management
VIRTULIZATION
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13. 3 Examples of Utility Computing Services
1. Amazon E2C
– Looks like a physical hardware.
– User can control entire software stack from the kernel upward.
– Makes difficult to offer automatic scalibility and failover.
2. Google AppEngine
– Automatic Scaling
– High-availability mechanism
– Data storage
– Enough CPU, bandwidth, and storage to serve around 5 million
monthly pageviews for free
3. Microsoft Azura
– A language dependent managed enviroment
– More flexible than Google AppEngine
– But still constraints the user’s choice of storage model and
applicaiton structure. 13IS748 Cloud Computing, May 2013

14. Cloud Computing Economics
CASES
1. When demand for a service varies with time.
2. When demand is unknown in advance
3. When a batch analysis is needed to finish
computationally faster
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15. Top 10 Obstacles and Opportunities
for
Cloud Computing

16. 1. Business Continuity and Service Availability
• Large companies will be reluctant to migrate to CC without a
business continuity strategy. (The Linkup Example)
• Opportunity: Use Multiple Cloud Providers
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17. 2. Data Lock-In
• Concern about the difficulty of extracting data from the cloud
is preventing some organizations from adopting cloud
computing. ) (Dallas Example)
• May flatten CC providers profit, but
 Increased quality of services and prevent customers jump to
lower cost services
 Enables Hybrid Cloud Computing: the use of the same software
infrastructure in an internal data center and in a public cloud.
This expands the CC market.
Opportunity: Standardization of APIs s.t. SaaS developer could
deploy services and data across multiple cc providers so that
the failure of a single company would not take all copies of
customer data with it.
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18. 3. Data Confidentiality/Auditability
• In cloud, responsibilities are divided among:
– Cloud user : responsible for app-level security
– Cloud vendor (provider): physical security
– Any third party vendor that users rely on for security-
sensitive software or configurations
 Technical responsiblities for the security of
Amazon E2C > Azura > Google AppEngine
The lower the level of abstraction
exposed to the user
the more responsibility goes with it
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19. Protection in Cloud
From Outside Attacks From Inside Attacks From Cloud Provider
Opportunity: The
user responsibility can
be outsourced to
third parties who sell
security services
Solution: Virtulization
but not all resources
are virtualized and not
all virtualization
enviroment are bug-
free
3. Data Confidentiality/Auditability
Solution: Courts,
User level encryption
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20. 4. Data Transfer Bottlenecks
• Applications are data-intensive and internet
transfer cost is high.
Ship 10TB from Berkeley to Amazon
Takes 45 days over internet
Takes less than 1 day by shipping.
Opportunity: Ship disks
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21. 5. Performance Unpredictability
• Multiple VM can share CPUs and main memory well in
cloud computing. But network and disk I/O sharing is
more problematic.
Opportunity 1: Improve architectures and operating systems to
efficiently virtualize interrupts and I/O channels.
The use of flash memory will decrease I/O interference.
• Many HPC applications need to ensure that all the
threads of a program are running simultaneously.
Opportunity 2 : Offer “Gang Scheduling” (an algorithm for parallel
systems schedules related threads or processes to run simultaneously on
different processors)
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22. 6. Scalable Storage
Open Research Question
• To create a storage system that
– Meet existing programmer expectations in regard
to durability, high availability, and the ability to
manage and query data.
– Combine them with the cloud advantages of
scaling arbitrarily up and down on demand.
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23. 7. Bugs in Large-Scale Distributed Systems
• Debugging must occur at scale in the production
data centers because these bugs can not be
reproduced in smaller configurations.
– Many traditional SaaS providers developed their
infrastructure without using VMs
– Level of virtualization may take it possible to capture
valuable information in ways that are implausible
without Vms.
Opportunity: reliance on virtual machines in
cloud computing
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24. 8. Scaling Quickly
• Pay-as-you-go applies with the bytes used on storage and on
network bandwidth.
 Google AppEngine: automatically scales in response to load increases
and decreases, and user is charged by the cycles used.
 AWS charges by the hour for the number of instances user occupy.
Opportunity: automatically scale up and down in
response to load without violating SLA. Good for
resources as well as money.
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25. 9. Reputation Fate Sharing
• One customer’s bad behaivor can affect the
reputation of others using the same cloud.
Opportunity: reputation-guarding services
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26. 10. Software Licensing
• CC providers relied on Open source software
in part because the licensing model for
commercial software is not good match to
utility computing.
Ex: Microsoft and Amazon offers pay-as-you-go software
licensing for MS Win and Win SQL server on EC2.
• MS Windows : $0.15/h vs. Open source: $0.10
• IBM software: $0.38/h - $6.39/h
Opportunity: Open source remains popular or
commercial companies changes their licensing structure
to better fit Cloud Computing.
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27. Conclusion
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28. Thank
you!
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