All right, hi everybody and welcome back to the channel.
My name is Bradley Knapp, and I'm one of the Product Managers here at IBM Cloud,
and what I want to talk with you guys about today
is a question that we get fairly commonly
when folks are starting their cloud journey
and starting to learn about cloud,
and that's, "What is IaaS?"
I read about cloud, I see this IaaS thing everywhere,
what does it actually mean?
And, so, "IaaS" is an acronym, and so it's broken into 2 parts:
the first part, the "I", that's "infrastructure".
And, so, if you think of cloud
as being just some other dude's computer,
running somewhere else,
that's the infrastructure part.
And, so, that infrastructure, if it's not cloud -
it could be running in a data center somewhere,
it can be running in a closet somewhere,
your laptop or your desktop is infrastructure.
And then the "a.a.S." piece is "as-a-Service".
That's the billing method, that's the way that you consume it.
And there are other kinds of as a service.
You've got "PaaS", Platform as a Service,
you have "SaaS", Software as a Service.
There's lots of different kinds of things that you can consume as-a-Service
but very specifically what we want to talk about
is the "I", it's the infrastructure.
And so I've got this diagram written out over here
because infrastructure really falls into three
main categories, right.
The first category is going to be compute, that's where the
processors are that's where the actual lifting and computing gets done. The
second piece which is storage kind of falls into three main buckets and lots
of smaller buckets on top of it because there's different kinds of storage. And
then the third piece, the piece that ties everything together
that's our network piece. And so we're gonna draw this one over here because
without network you can't do anything, network is how the compute talks to the
storage and that's how the compute talks to the other compute. And so like I said
we can break this down into different pieces and so in the
compute side I've got three things called out up here, the first one is kind
of I've just got a labeled compute, its general purpose compute, right. This is
your normal web server or application server, it can really be whatever general
purpose kind of computing needs you have. The second two are, or the second and the
third really are more specific right. So GPU is
is a graphics processor, that's a very very high speed processor that's used in
conjunction with a traditional processor for specific kinds of workloads right.
This is gonna be your machine learning and your AI. And then the third piece, HPC,
that's high-performance computing. So there's specific kinds of workloads that
had very specific requirements as far as frequency which is your clock speed and
the number of cores that are required where you have to have lots of power
packed into a very, very, very small footprint, that's gonna be your HPC. And
likewise on the storage side you've got different kinds of storage because you
have different storage needs. The most commonly used one is gonna be object
storage. Object storage is a little bit lower performance but it's relatively
inexpensive and that's for your general purpose storage right. What goes into
object storage? Well you can have things like pictures, you can have documents, you
can have really whatever you want can go into that object storage, it's where all
of the data and all of the graphics on the web server that's all hiding
in object storage. And then the second and the third piece that I've got called
out here, block and file, these are specific kinds of storage, specific kinds
of network storage, and they attach in very specific ways. Block storage
attaches with iSCSI, file storage attaches with NFS, it's the way that they
mount into the actual compute itself. And there are specific kinds of applications
that require block storage or file storage because each of them has their
own features and benefits. And so to talk about how we pull all of these things
together we need to talk about the network, because network has two main
components that matter. And so what I want you to do is I want you to think of
your network as a pipe, right. And so a network can be a small pipe, that would
be like a pipe measured in megabits so you can't press much data through it. Or
it can be a very large pipe, that very large pipe that would be measured in
gigabits per second. And so the more data you need to push simultaneously the
larger pipe you need and the more bandwidth you need. The second way that
we measure network traffic is how much data gets pushed through this pipe over
a set period of time. Normally it's billed by the
month but it could also be billed by the minute, by the second, or maybe even by
the day, or by the week. And so to take all of this and tie all this together, I
want to use an example of something that requires some specialty components right,
we're going to talk a little bit about an AI workload. And so if you think about
an AI workload where you're going to do automatic visual recognition of pictures.
Let's say that you have a billion pictures down here in object storage
that you are then going to use to train your model that's running on these GPU
servers, and so you take that billion pictures and since a billion is a lot
and pictures are very large you have to push them through a really big pipe, that's
your network pipe up into the GPU server but the GPU server doesn't have any
storage inherent to it. So that GPU server is actually going to take and
write that into block. And it's going to write that data back and forth, and back
and forth until the model is done. Once it's trained it's going to take all of
the data that we pushed up here and all of the results and it's going to write
all of that back down into object storage. Why object storage? Because
again, it's less expensive, it's a good archiving solution. And so you're pushing
a ton of data through these pipes while they're turned on and then once you're
done you get rid of them. And so the second piece that I want to talk about
is the "as-a-Service" piece, this is the way that you consume. And so when we talk
about as-a-Service there are kind of four things that really, really matter in
this model and the first one is that offerings that are consumed as-a-Service
are generally speaking shared. And so by shared I mean they're multi-tenant, many
people use the same offering, we just take and carve it up and make it
available to multiple different customers simultaneously. So that's the
first piece of as-a-Service. The second piece is the hourly or monthly piece.
This is talking about how we bill. In the case of compute, it could be a
certain number of cents, or certain of dollars per hour, or per month. In the
case of storage, we would bill out in the amount of data that's stored in a given
month, so that would be cents per gigabyte per month. In the case of
network, there are two different metrics we
about earlier right. The size of the pipe you would pay per month charge for that,
and then the amount of data that goes through it again measured in gigabytes
per month, or cents per gigabytes per month. So that's our billing metric. And
then the third piece, and this is a very important one, is that there are no
contracts involved in an as-a-Service model, or there aren't necessarily
contracts. There can certainly be them but they're generally advantageous to
you. By no contracts we mean that you don't have to agree to use something for
a set amount of time, you use it for as long as you need it and then you get rid
of it. And so rather than a checkmark for no contracts I'm just gonna put a little
X there. You only use it to when you need it, it's on demand. And then the last
piece, and this is probably the most important as-a-Service offerings are
self service. That means that you can go out to a website, you punch in your
information, your payment details, click the Go button and that as-a-Service
offering is going to be provisioned and delivered to you. It's not something that
takes days or weeks or months to set up and configure, it's one that can be
provided in minutes or hours. Thanks for stopping by today. If you have any
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