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Above the Clouds: A Berkley View of Cloud Computing

Ambrust et al.RAD Lab (supported: google, amazon, microsoft, etc.)

CIS6000Paper Presentation: Mohammad Naeem

School of Computer Science (SOSC)University of Guelph

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gist of the paper

NO---Cloud Computing (CC) makes technical and economic sense there

May be some issues though

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focal points

o backgroundo advantageso reasons for later/potential successo becoming cloud computing provider: guidelineo moving to clouds: conditions foro utility computing: classeso cloud computing: economic ofo moving to cloud : economics ofo critical obstacles and opportunitieso recommendations

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outline

data center

= hardware+

system

software

application

software

(simple software

installation

& m, control

over versioning)

o utility computing (selling date center resources)

o SaaS --- software as a service

oThe data center’s hardware and software as a cloud

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advantages

o adding to the attractiveness of software serviceo availability of an abundant amount of hardwareo under and over provisioning avoidedo quick results (1000 computers working on the same task simultaneously)

conditions for moving to cloudso demand varies with time (over-provisioning leads to under-utilization of resources)

o demand unknown in advance (a web start-up needing to support a sudden spike followed by a reduction in load)

o cost-associativity in case of batch-analytic (organizations that perform batch analytics can use the cost associativity of CC to finish the computation faster)

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types of utility computingamazon web services

microsoft azure

google apple engine

Computation model

• X86 instruction set architecture

• CLR • pre-defined application structure & framework

storage model • block store to augmented key/blob store

• SQL data services • Mega-store/big table

networking model

• declarative specification of IP level topology

• programmer-defined application components

• fixed typology to accommodate 3-tier web app structure

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types of utility computing

google app enginemicrosoft Azure

EC2

highest-level

lowest-level

possibility of multilayered architecture with the above stacked upon each other…

EC2-looks like physicalhardware, users can control the entire software stack up the kernel

Clean separation between storageAnd computation tier, automatic scalability and handling of failover

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reasons for later/potential success

o hardwareo illusion of infinite computing resourceso elimination of upfront commitment by userso payment for resources on short-term basis

“past attempts failed because one or two of these features were missing”

Intel Computing Services: - contract, - long-term use than per hour

EC2 --- sells -1.0-GHs x 86 ISA slices for 10 cents per hour

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reasons for later/potential success

o physical infrastructure

“large-scale commodity computer data centers at low-cost location

5 to 7 decrease in cost of”

Electricity Network bandwidth Operations Software Hardware Coupled with statistical multiplexing

o

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reasons for later/potential successolarge-scale commodity-computer data centerotechnology trends & new applications

mobile interactive applications (real time services)

parallel batch processing (batch-processing, analytic jobs)

business analytic (growth of decision support processing)

computing-extensive desktop applications (MATLAB, Mathematica)

earth-bound services (analytic for long-term financial decisions)

cloud computing: economic logic

o CC has fine-grained economic model--- so trade-off decisions flexibleo CC can track changes in hardware cost and pass them through to the customer

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cloud computing: economic logic

“converting capital cost to economic cost”(cleverly) rephrased as“you pay as you go”

o economic sense of CC captured in two fancy terms/concepts

ξ elasticityξ Transference of risk

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cloud computing: economic logic

o elasticity (in acquisition and de-acquisition of resources)

resource addition/removal at fine-grained level so better matching of resources to workload---

users do resource-provisioning for peek-utilization with CC waste of idle resources avoidable---

more effective tackling of over/under provisioning-

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o Visitors receiving poor performance during the peak load permanently lost

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cloud computing: economic logic

o transference of risk (risk of misestimating workload shifted from service operator to cloud vendor)

the cloud vendor may charge a premium (higher use cost per server-hour compared to 3-years purchase cost)

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moving services to clouds: feasibility

pay separately per resource (e.g., CPU-bounded jobs can benefit for paying for CPU separately)

power cooling & physical plant cost (cost double when amortised over building life-time)

operations cost (operations handled by the cloud, lower for managed environments)

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top 10 obstacles to cloud computing

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top 10 obstacles to cloud computing

Availability of service o multiple clouds --- wouldn’t this add to cost?o the complex calculations say

DDoS would cost the attacker more thanUntil the attack last for 32 hours but then it would be detected--- (kind of speculative)

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top 10 obstacles to cloud computing

data lock-in o APIs for CCs proprietary (i.e., not standardized

yet)---so difficulty extracting data and programs from one site to run on another---

o solution: standardise APIs for clouds

“race-to-the-bottom” of cloud pricing flattening profit for CC providers-

authors arguments: quality of service, standardization of APIs enabling the use of same software for private as well as public clouds---

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top 10 obstacles to cloud computing

data confidentiality and auditability o CCs essentially use public networks so more

exposed to attackso lack of auditability and Accountability Act

regulation in CCs

“my sensitive corporation data will never be in the cloud”

authors arguments: same measures e.g., encrypted storage, virtual local area network, and network middleboxes(firewalls, packet filters) as used in in-house IT environment can be employed---

recommendations

o scalability VMs (horizontal scalability of VMs) Application software (needs to rapidly scale-up as well scale-

down, pay for use licensing model)

o infrastructure software (needs to aware of running on VMs, billing built in from the beginning)

o hardware systems To be designed at the scale of container Processors should work with VMs Flash memory added LAN/WAN switches/routers to be improved in bandwidth and cost

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critical review

o overly optimistic/unrealistic view/expectations of/from CLOUD COMPUTING-

o “how CC makes technical sense” aspect not rigorously treated

o Overestimation of economic benefit-probably no real data available to back that up-

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references

1. Armbrust et al., “Above the clouds: a Berkeley view of cloud computing”, 20092. Powell John, “Cloud computing: what it is and what it means for education” 3. Vaquero et al., “A break in the clouds: towards a cloud definition”, CCR online4. http://www.youtube.com/watch?v=IJCxqoh5ep4

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Thanks