Armbrust et al: A view of cloud computing

Cloud Computing- Both the applications delivered as services over the internet and the hardware and systems software in the data centers that provide those services.

Iaas- Infrastructure as a Service

Saas- Software as a Service

Paas- Platform as a Service

How are they related?
Saas makes up the software (applications delivered over the internet) aspect of cloud computing while Iaas and Paas make up the hardware (low level infrastructure and higher-level platform). This article in particular describes Iaas and Paas as more alike than than different, so it groups them together.

What is a private cloud versus a public cloud? How do they differ? 
"When a cloud is made available in a pay-as-you-go manner to the general public, we call it a public cloud; the service being sold is utility computing. We use the term private cloud to refer to internal data centers of a business or other organization, not made available to the general public, when they are large enough to benefit from the advantages of cloud computing that we discuss here." (p.51)

What do the authors state as the key necessary enabler of cloud computing? 
 They say that the "construction and operation of extremely large-scale, commodity-computer data centers at low-cost locations was the key necessary enabler of cloud computing."

Summarize the use cases that favor utility computing over conventional hosting. 
1. Demand for a service varies with time. Example: Having a data center with the equipment to handle its peak utilization which only happens a few days a month. This leads to under utilization the rest of the time. This would allow my company to save money and only use what I need.

2. Demand is unknown in advance. Example: A website is launched and gets a high amount of traffic initially, but dies down in time. It can then be reduced once it slows. Same idea, I only use what I need.

3. When an organization needs to perform batch analytics, they can use cost associativity of cloud computing to finish computations faster. Example: Using 1000 EC2 machines rather than a single machine for 1000 hours. This saves a vast amount of time but then saves money in the long run by not needing to have the 1000 machines once it is over.