Above the Clouds: A Berkley View of Cloud Computing Ambrust et al. RAD Lab (supported: google, amazon, microsoft, etc.) CIS6000 Paper Presentation: Mohammad Naeem School of Computer Science (SOSC) University of Guelph 1

gist of the paper 2 NO---Cloud Computing (CC) makes technical and economic sense there May be some issues though

focal points o background o advantages o reasons for later/potential success o becoming cloud computing provider: guideline o moving to clouds: conditions for o utility computing: classes o cloud computing: economic of o moving to cloud : economics of o critical obstacles and opportunities o recommendations 3

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 o The data center’s hardware and software as a cloud 4

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advantages o adding to the attractiveness of software service o availability of an abundant amount of hardware o under and over provisioning avoided o quick results (1000 computers working on the same task simultaneously) 6

conditions for moving to clouds o 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) 7

types of utility computing amazon web services microsoft azure google apple engine Computation model X86 instruction set architecture CLRpre-defined application structure & framework storage model block store to augmented key/blob store SQL data servicesMega-store/big table networking model declarative specification of IP level topology programmer- defined application components fixed typology to accommodate 3- tier web app structure 8

types of utility computing google app engine microsoft Azure EC2 highest-level lowest-level  possibility of multilayered architecture with the above stacked upon each other… 9 EC2-looks like physical hardware, users can control the entire software stack up the kernel Clean separation between storage And computation tier, automatic scalability and handling of failover

reasons for later/potential success o hardware o illusion of infinite computing resources o elimination of upfront commitment by users o 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 10

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 11

reasons for later/potential success o large-scale commodity-computer data center o technology 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) 12

cloud computing: economic logic o CC has fine-grained economic model--- so trade-off decisions flexible o CC can track changes in hardware cost and pass them through to the customer 13

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 elasticity ξ Transference of risk 14

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- 15

o Visitors receiving poor performance during the peak load permanently lost 16

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) 17

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) 18

top 10 obstacles to cloud computing 19

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 than Until the attack last for 32 hours but then it would be detected--- (kind of speculative) 20

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--- 21

top 10 obstacles to cloud computing  data confidentiality and auditability o CCs essentially use public networks so more exposed to attacks o 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--- 22

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 23

critical review 24 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-

references 25 1.Armbrust et al., “Above the clouds: a Berkeley view of cloud computing”, 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 online 4.

26 Thanks