lecture 2: introduction to cloud computing

Lecture 2: Introduction to Cloud Computing

Xiaowei Yang (Duke University)

Roadmap• What is Cloud Computing?

• Why now, not then?

• Classes of Cloud Computing

• Cloud Computing Economics: why does it make sense?

• Obstacles and (research) opportunities

What is cloud computing• Applications run on clouds (Software

as a Service)• Hardware and system software in the

datacenters that provide the services– An old concept: computing as a utility• No need to purchase your hardware• Pay-as-you-go

Cloud Computing = SaaS + UtilityComputing – PrivateClouds

• Private– A business’s internal datacenters– No public access– Name a few companies that own private

clouds• Public– Pay-as-you-go public services– Name a few public cloud providers

Who’s whom

Is Cloud Computing Win-Win?

• SaaS advantages to providers– Simple management and maintanence– Centralized control over versioning

• SaaS Advantages to users– Always on service– Easy data sharing and collaboration– Robust data storage– Simple management–…

• Advantages of utility computing to users– On demand scaling (elasticity)– No up-front commitment– Pay-as-you-go reduces provisioning risk

Examples–When Animoto made its service available

via Facebook, it experienced a demand surge that resulted in growing from 50 servers to 3500 servers in three days. … After the peak subsided, traffic fell to a level that was well below the peak.

• With traditional computing buy servers idle servers• With cloud computing pay during peaks

release afterwards

Incentives for cloud providers

1. Making money– Wholesale (10,000s) at a larger scale is 5-7

times cheaper than retail at a medium size (100s - 1000s)

– Resource multiplexing2. Leveraging existing investment– Companies may already build private clouds

for other businesses3. Defend a franchise– Migrating existing customers to a cloud

4. Attacking an incumbent– Google vs MS

5. Leveraging customer relationships– E.g. IBM– Preserving relationships by offering a

branded cloud computing service6. Becoming a platform– More customers more $$

Why now?• Two enablers:– New business model: pay-as-you-go with

no contract• Intel Computing Service in 2000-2001

required a contract and longer-term use and failed• Customers do not like commitment

– New applications• Mobile + cloud• Parallel batch processing: tons of data today• Analytics• Compute-intensive desktop applications

Classes of Utility Computing• Infrastructure as a service (IaaS)– Thin API, close to bare metal – Virtual machines with customized guest OSes– Applications run on virtual machines using OS

APIs– E.g. Amazon EC2

• Platform as a service (PaaS)– Sandbox environment with specific platform APIs– E.g. Google AppEngine

• A mixture of both– Microsoft Azure

Economic benefits• Elasticity– Peak demand: 500 servers– Average demand: 300 servers

– Q: when does it make sense to use a cloud?

Reducing underprovisioning risk

• Poor performance turns customers away

Real world examples• Target uses AWS• Other retailers use it during holiday

seasons

Rule of Thumb• UserHourscloud x (revenue – Costcloud)

>= UserHoursdatacenter * (revenue – Costdatacenter/Utilization)

• Why Costdatacenter/Utilization?• Do UserHourscloud ==

UserHoursdatacenter

Comparing costs

When not to use a cloud?• Utilization = 100%

• Shipping large amount of data

Obstacles and Opportunities• Availability– Single point of failure• Mega-Cloud to improve reliability• Elasticity to defend against DoS attacks

– Ex. 500,000 bots at $0.03 per bot, 1GB/s attack traffic

– Victim: $360 per hour in bandwidth and $100 of computation, (500 bots per instance)

– Attack must last long (>32 hours) – Make bots detectable

Obstacles and Opportunities• Data Lock-in– Not a pure technical problem–Marketing strategy– Standardarization

• Data confidentiality and auditability– Technical challenge– Encryption would help

Obstacles and Opportunities• Data transfer bottlenecks– Need creative solutions• FedEx• Keep data local to a cloud• Cheap long haul bandwidth by reducing high-

end router cost– 2/3 of bandwidth cost is from routers

Obstacles and Opportunities

• Performance variation caused by I/O sharing–More research

Obstacles and opportunities• Scalable storage– Research to build scalable storage systems

• Bugs– Debuggers, tracers

• Scaling quickly– Research

• Reputation fate sharing– Spammers used EC2– All services sharing their IP addresses got

blacklisted– Research

Obstacles and opportunities• Software licensing– Not pure technical challenges• Commercial software’s licensing model not

good for utility computing– One time purchase vs pay-as-you-go

– Opportunities• New licensing models• New sales models• Open source software!

Summary• What is cloud computing– SaaS + Utility Computing – Private Cloud

• Enablers– Business models– New applications

• Advantages• Economic benefits• Challenges and opportunities– Technical– Non-technical