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- Let's first review the
definition of cloud computing.

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So the National Institute of Standards

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and Technology here in the US,

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otherwise known as NIST,

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got together with industry
leaders some years ago

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and came up with an official
definition of cloud computing,

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and through a number of different drafts,

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they were able to simplify

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and distill it down to
its real core essence,

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and first, we have characteristics.

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The characteristics of cloud
computing would be one,

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that services or features

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or resources are retrieved via on-demand,

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that they are available

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to us by us asking for them directly,

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so I can go to a service

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and ask for a virtual machine

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or a storage volume or some
other type of resource,

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and get it when I ask for it.

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I get it at the time I make
that demand or request.

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And so on-demand really is

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one of the core pieces of cloud computing

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that gives rise to a level of automation

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and flexibility and agility
that we've never had before,

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and a level of automation

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that we perhaps have never had before.

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The other characteristic
would be broad network access,

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meaning that the resources

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that we have within the
cloud can communicate

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with each other across the network,

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that we can get to them
across the network,

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that we have access to the Internet.

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The third characteristic
would be resource pooling.

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In some cases we have
multitenant environments, right?

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There may be many cases

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that we have a multitenant environment,

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and there are some cases

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where we can actually have
a single tenant environment,

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but if you were to zoom out
and look at the big picture,

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and you would see that even
though our virtual machine

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or our physical server might
be a single tenant environment,

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the rack is shared with other
machines that are powering

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or providing services to other customers,

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and then of course, the data center itself

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is shared by numerous customers.

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The power, the cooling,

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the network, and so on,

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are all shared, so resource
pooling is really the way

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that cloud computing can offer
the services that it does

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at the prices that it offers them at.

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The fourth characteristic
would be rapid elasticity.

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So elasticity speaks to the idea

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that resources can grow and shrink.

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They can grow vertically,

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they can grow horizontally,

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but rapid elasticity means

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that if we need more storage
now than we needed an hour ago,

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if we need, suddenly need
more capacity in our API

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or our database today
than we needed yesterday,

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that we can get that
capacity quickly and easily,

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and the on-demand nature allows for that.

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So rapid elasticity, the ability

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to scale when we need to scale.

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And then, lastly, we
have a measured service.

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And that's just a fancy way
of saying pay-as-you-go.

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So when we take the elastic compute cloud

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or EC2 for example, if we ran a machine,

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a virtual instance, for let's say an hour,

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then we pay for an hour.

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If we run it for two hours,
we pay for two hours.

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So we pay for what we use,

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and within AWS, the trick

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to really achieving the most cost savings

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or the most cost-effective solutions

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is to use what we really need, right?

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So we pay for what we use,

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it's our job to use what we really need

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and no more and we'll talk
more about that later on.

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Now in terms of service models,

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many of these we've heard before I'm sure,

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starting with infrastructure
as a service or IaaS.

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Infrastructure as a service

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is essentially those
fundamental lower level

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sort of raw building blocks
such as raw computing

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or storage volumes, right?

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So we can build our application on top

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of Amazon's compute power and
storage and networking tools.

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Then we have platform as a service.

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In many cases within AWS,

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we can offload the operational burdens

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of the tools such as
databases, for example, to AWS.

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And so when certain things like that,

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databases, the management of databases

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like relational databases,

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NoSQL and graph databases,

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and other services, when those
are kind of abstracted away,

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that's when it crosses
into platform as a service,

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and we are leveraging that
platform to run our applications.

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And then lastly, as far service models go,

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we have software as a service.

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And that's generally what
most of us are building.

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We are leveraging the infrastructure

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and platforms that AWS provides
to build our own software.

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So that's the definition
of cloud computing,

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that we can go to Amazon to the API,

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to the management console,

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and we can ask for a virtual machine,

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and we can get a virtual
machine on demand,

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and that virtual machine
has access to a network,

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we can communicate with the Internet,

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and we can get that virtual machine

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at a low price because millions

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of customers are pooling their resources

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and allowing AWS to offer those
things at those low prices.

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And if we need to go from one EC2 instance

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to 100 to 1000, we can do that.

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We can scale rapidly very easily.

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If we need our underlying storage volumes

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to go from one gig to one
terabyte to a petabyte,

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in a short period of time,

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we can do that as well,

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and no matter how we make use of AWS,

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we pay for what we use.

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So that's the definition
of cloud computing

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and we will be talking more about this

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and putting all of this into
context throughout this course.