Cloud Computing

Computation as Utility

Computer utilities

• Leonard Kleinrock, ARPANET, 1969:• ”We will probably see the spread of computer

utilities, which like electricity will service individual homes and offices.”

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Leonard with an Interface Message Processor, the first generation of routers

ARPANET was the precursor to the internet

Why Utility?

• Ok, you have made your Android quizz game, but how many servers do you need to support?– 1? 10? 1.000?– Depends on no. of users, and usage patterns

• And what about resilience of the servers?– Put them under my desk?– Backup?

• Computation as a utility– Electricity and water I pay per usage

– How many spare CPU cycles do you have at home?

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Utilization problem

• Either you– Waste hardware resources or– Cannot provide service during peaks–

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Cloud Definitions

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Ambrust et al.

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Buyya et al.

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Vaquero et al.

• Based up review of a lot of definitions:

• Clouds are a large pool of easily usable and accessible virtualized resources (such as hardware, development platforms and/or

services). These resources can be dynamically re-configured to adjust to a variable load (scale), allowing also for an optimum

resource utilization. This pool of resources is typically exploited by a pay-per-use model in which guarantees are offered by the

Infrastructure Provider by means of customized SLAs.

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Comparing?

• Similarities? Differences?

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Clouds are a large pool of easily usable and accessible virtualized resources (such as hardware, development platforms and/or services). These resources can be dynamically re-configured to adjust to a variable load (scale), allowing also for an optimum resource utilization. This pool of resources is typically exploited by a pay-per-use model in which guarantees are offered by the Infrastructure Provider by means of customized SLAs.

NIST characteristics

• Comparing

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A key enabling technology:Virtualization

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Credits

• Some slides from– E6998 - Virtual Machines

Lecture 2CPU Virtualization

• Scott Devine• VMware, Inc.

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What is it?

• vir•tu•al (adj): – existing in essence or effect, though not in actual

fact

• Example– ScummVM is a program which allows you to run

certain classic graphical point-and-click adventure games, provided you already have their data files. The clever part about this: ScummVM just replaces the executables shipped with the games, allowing you to play them on systems for which they were never designed!

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A Physical Machine• Hardware

– Processors, devices, memory, etc.

• Software– Built to the given hardware (Instruction Set Architecture, e.g.

x86)– Built to given OS (App. Programming Interface, e.g. Win XP)– OS controls hardware

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A Virtual Machine• Hardware Abstraction

– Virtual processor, memory, devices, etc.

• Virtualization Software– Indirection: Decouple hardware and OS– Multiplex physical hardware across guest VMs

Enabling technology

• Virtualization allows cloud providers to rent you a machine easily and quickly

– No buying equipment, no installing OS, no hooking network cables

– Just launch a new VM…• Typically through a web interface

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Example: Amazon EC2

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Example: DigitalOcean

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Example: Private Cloud/ESXi

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One thing for sure…

• Terminology is victim of branding and trends

– Droplet? Instance? Container?

–

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Service Models & Operations

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Service Models

• SaaS: Software as a service– End user applications accessible in the cloud, typically

through web browsers or mobile apps– Exercise: Give examples

• PaaS: Platform as a service– Programming libraries, services, tools allowing

applications to be build utilizing cloud features– Exercise: Give examples

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Service Models

• IaaS: Infrastructure as a Service– Provide virtual processing and storage capacity, i.e.

the actual computing infrastructure

– Exercise: Give examples

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Comparing

• Why are some cloud service models much easier to spot than others?

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Example: NetFlix

• Adrian Cockcroft / GOTO 2012

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http://gotocon.com/dl/goto-aar-2012/slides/AdrianCockcroft_GloballyDistributedCloudApplicationsAtNetflix.pdf

Deployment models

• Examples– Public cloud: Give me an example– Private cloud: Give me an example

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Obstacles/Opportunities

• Armbrust et al.– Business Continuity and Service Availability

• If your cloud provider fails – you fail

– Data Lock-in• Storage using propriatary API (Amazon S3 etc.) makes

‘getting your data back’ hard

– Data Confidentiality/Auditability• Who peeks into my data?

– Data Transfer Bottlenecks• Sending data is costly. Shipping disks are cheaper!

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Obstacles/Opportunities

• Ambrust et al.– Performance Unpredictability

• Multiple VMs (one the same physical machine) can limit IO – i.e. cross-VM penalties

– Scaleable Storage• Storage is not as easily scaled as other resources

– ? Is this an issue of yesterday?

– Bugs in Large Scale Dist. Systems• How do you debug?• NetFlix: Monkeys and Gorillas

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Obstacles/Opportunities

• Ambrust et al.– Scaling Quickly

• What to do with idling machines? Shutting down means longer time to start...

– Reputation Fate Sharing• Spamming -> black listed IP addresses.• Will you overtake these?

– Software Licensing• Pay as you go licenses for commercial SW

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Operations

• Architecture ofcloud provider

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