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 multiplexing

2. Leveraging existing investment– Companies may already build private

clouds for other businesses

3. 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 service

6. 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