- So in this lesson, we're gonna look
at the different types of cloud services.
We'll look at the cloud deployment models
and really the main value proposition of cloud computing.
First, we have IaaS, infrastructure as a service.
The capabilities offered
to the consumer is rapid on-demand provisioning
of processing, storage, networks
and other fundamental computing resources.
Consumers could then deploy
and run operating systems like Linux and Windows
and applications like SQL Server and SharePoint,
sometimes from a third-party marketplace
of partner vendors as well.
Here, we can see the IaaS model at Amazon Web Services.
AWS is the largest
and they have the highest rating from Gartner.
In their particular quadrant,
there are five times bigger than their next competitor.
So as we can see here,
we have four main foundation services
that they provide as IaaS.
The compute services,
which can be, obviously, compute instances
of Linux and Windows,
or it could be serverless code like Lambda.
They offer storage, which can be blocked storage,
either hard disk drives or solid state drives.
They also have object storage with S3.
They have different databases, SQL structured databases
and non SQL databases
like document style like DynamoDB.
And then they have their networking.
So they provide their own network infrastructure
which is supported
by extremely fast network attached storage, RAID arrays.
And they're in the process of going from 10 gigabit ethernet
to 100 gigabit ethernet in all of their data centers.
So also in networking would what we call content delivery
or content distribution networking.
So similar to what we get with Akamai,
they have what's called CloudFront.
So they're getting that content, that streaming video
that streaming audio, let's say,
from Spotify or Hulu or Netflix,
they're getting it as close to the consumer
as possible cashed in Redis memory only storage.
So that's the main foundation services.
You might add a fifth foundation service
of machine learning.
All of them were kind of doing that now, making
that fifth category machine learning,
but notice that with IaaS,
as a consumer, as a customer,
I'm responsible for everything above that.
I get my pointer.
So right here this is kind
of the demarcation point right here,
where I'm going across here,
so I'll just leave it right there.
So everything above that
is gonna be the consumer's responsibility.
We decide how we're gonna encrypt the data.
Is it gonna be on the client side,
are we gonna use the actual service
like the storage service S3 to do our encryption,
are we gonna use a global key management service to do it?
How do we protect our network?
We implement the firewall, we choose the operating system,
we configure the network,
the virtual private cloud, or VNet, virtual network,
we configure the various firewalls.
We are going to choose the applications
that we're gonna run.
If we're gonna run a database application
or something else, we have to update it and patch it
and put the service packs on there.
We're responsible for our data.
So that's really infrastructure as a service
of really definitive and well-defined demarcation
between the customer responsibility and the provider
or the CSP in this case, Amazon Web Services.
So platform as a service is the next service type,
offers capability to build or buy applications
onto the cloud infrastructure.
It uses a variety of programming languages,
libraries, services, and tools that are supported
by the cloud provider.
So they provide the SDKs to the developer.
They also provide the computing power
that we need to do the application development.
The customer of platform as a service
will control the deployed applications
and often the configuration settings
for the application hosting environment.
Different providers will support .NET, Java,
Ruby, Python Go, JSON, YAML and more.
Amazon Web Services has examples of their offerings.
LightSail, for example, is kind of a monthly charge
to have your website.
Kind of when you register a domain name through GoDaddy,
they'll give you the opportunity to have your own website
for 1999 a month,
all this bells and whistles that go with it,
that's kind of LightSail's version.
Aurora DB is their document style database.
A highly scalable global Lambda would be functions
as a service up at the cloud.
Elastic Beanstalk would be their full blown
platform as a service development solution.
And then CloudFront is their content delivery networking.
and all of the other cloud providers Microsoft Azure,
Google Cloud Platform, IBM Cloud,
they all have their own versions
of all these different services.
So here at AWS, PaaS or platform as a service,
obviously this can be more of a managed service
where AWS takes responsibility for the operating system
and the network configuration
and even managing the platform and application.
So you don't have to worry about any updates
or upgrades or service packs or things like that,
all you do is you just make the decisions,
what type of encryption you're gonna use
and what type of data.
And you may or may not allow them to do the firewall,
it depends on how well managed that service is.
One thing about platform as a service is it really varies
depending upon the service that you're using
of how managed it is, okay?
So the demarcation point can be a more
of a gray area, depending upon the particular service
that you're using.
Software as a service is
where the customer uses the service provider's applications
running entirely on a cloud infrastructure.
The applications are accessible from various client devices
through either a thin client interface,
such as a web browser, or maybe some programmed interface,
maybe onsite custom interface.
There are possible exceptions to this rule,
but for the most part, the entire application runs
in the cloud.
So for example Office 365,
where you're just rendering an XML on the client side,
that word document or Excel spreadsheet,
there may be some user specific applications
or user profiles,
but for the most part, it's all running in the cloud.
Some common use cases
for SaaS would be CRM, customer relationship management
enterprise resource planning, ERP,
community services, billing services, and taxation services,
analytics, okay, business analytics,
personal storage services like Dropbox and Box
and others and security services.
So for example, a security service that you would use
with a SaaS is often called a CASB, C-A-S-B,
a cloud access security broker.
And then of course, we have everything as a service.
Database as a service,
functions as a service, communications as a service,
business process as a service,
security as a service, which we call sec as a service
or MSSP, managed security service providers,
and of course, unfortunately, malware as a service.
We have cloud deployment models.
Now the model that you choose will depend
on various factors, your business strategy,
your objectives, regulation, and governance,
your costs and forecasted budgets, your risk treatment,
how do you handle, what is your risk appetite
for certain data types and certain assets,
and new technologies
and green initiatives may drive the cloud deployment model
that you use.
Public cloud is provisioned for open use
by the general public.
This is what we think of
when we use Microsoft Azure, for example.
It may be owned, managed, and operated
by a business, academic or government organization
or some combination of them, yet it exists on the premises
of the cloud provider.
And public typically means it's accessible
over the internet.
A private cloud deployment is basically provisioned
for exclusive use
by a single organization, comprising multiple consumers.
It may be owned, managed, and operated by an organization,
a third party, or a combination of those three.
It offers the same benefits of a public cloud,
but you're not giving up any control,
any privacy and security.
So typically a private cloud, maybe
an air-gapped private subnet, or private VNet up
at a cloud provider
or the private cloud could be on-premises, okay, air-gapped
and not connected to the internet, or if it is just
in a very protected select way
as maybe necessary due to regulations
of your data, like HIPAA, for example.
Remember a private clouds may exist on or off premises.
Community cloud is provisioned for exclusive use
by a specific community of consumers from organizations
that have a shared concern.
They're often owned and operated by one or more
of the organizations in the community, a third party
or some combination of them.
Common examples would be healthcare, finance communities.
AWS has what's called GovCloud for the US government, okay?
It could be insurance companies.
And again, GovCloud AWS is a prime example
of a community cloud.
Hybrid cloud is a combination
of two or more distinct cloud infrastructures,
private, community, or public that remain unique entities.
This is the most popular solution is a hybrid cloud
because often organizations will burst up
to the cloud during their most busy retail.
So for example, between October and December
in the US, during the holidays, they'll burst up
and use cloud resources, okay,
that's a hybrid cloud and bursting is a common usage
of hybrid cloud, or maybe for disaster recovery purposes
or maybe through the transition of moving data
from the on premises data center to the cloud,
for that particular transition,
you'll have a hybrid cloud solution.
Organizations may need
to keep certain resources internal and private
for mission criticality or for regulatory reasons.
Often will burst up, like I said.
And of course, Outposts from AWS is kind
of what we call hybrid as a service.
So AWS allows you to kind of emulate
and replicate their cloud environment, their hardware
and their software and their hypervisors
on your site, okay?
Now hybrid as a service is not an official term,
it's one I kind of made up, it won't be on the exam,
but remember, simply using software as a service
like Office 365, if you're using that,
that doesn't make you a hybrid cloud, okay?
It's a combination of public
and or private and or community.
The value propositions of cloud would be cost, okay?
Some consumers that can experience 50% savings or higher
by moving from the data center
to the cloud, eliminating all those upfront costs,
cabling, cooling power, racks, servers,
employees, labor, certifications,
all those things, reducing due the economy of scale
of the cloud provider,
just taking advantage of the multitenancy
and the hypervisor capabilities.
They have a pay-as-you-go and pay-as-you-use model.
So if you're bursting up, you're only paying
for when you're using it.
Agility and elasticity are also a value propositions.
Companies can leverage the infrastructure
for speed, experimentation, innovation,
respond to competitors, unlimited scalability,
dynamic provisioning and deprovisioning
of all the different resources
and you can also shift and pool resources as needed
at the cloud provider, so preventing cost overruns.
On-demand access.
Okay, if you have an internet connection,
you can typically access the cloud all over the world.
Online portal with all the cloud providers,
you can use the online portal
or you can use some type of command line interface
or software development kit, or other tools.
You can have limited or no interaction with a human being,
it can be all automated, if you wanna do it that way.
And of course, we're leveraging
for content delivery networking,
we're leveraging these edge locations
in cities all over the country and all over the world.
Auto Scaling, monitoring your applications,
automatically scaling up or scaling down as needed.
Simple setup for scaling up web services for containers,
for code running in the cloud,
you can auto scale a wide variety of things.
So you can scale up to a certain defined amount
and then if you're not using it,
you can scale back automatically.
So Auto Scaling really kind of ties into elasticity,
but you can have auto scaling plans not just for instances
of Windows and Linux, but also fleets of instances,
tasks that are running in the cloud, database tables,
indexes, all those types of objects, even containers.
Security is a value proposition.
Cloud providers spend a lot
of time securing their data centers.
They're highly secure environments
and they're very difficult to actually get into it.
Most people that work for these companies
like Google or Amazon or Microsoft will rarely set foot
in their cloud data centers.
These are some of the most secure locations in the world.
They're nondescript locations, difficult to find.
You can find them with OSINT Tools,
but they're difficult to find,
it's not like a flashing neon light or anything.
There are 24/7 security staffing.
They use multifactor authentication and biometrics,
continuous monitoring,
and auditing both a logical and physical,
automated change control,
and automatic configuration control
and then bastion services to access everything.