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