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 questions, please drop us a line below in
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