Well, we have already learned a lot about SD-WAN, but in order to continue our
studies,
it's about time that we start logging into these devices, performing some basic
configuration,
and seeing all of these concepts in action.
Well, in order to do that, we're going to need an SD-WAN environment.
And unlike some other environments, this is very difficult for us to do
physically.
And minimum, the controllers have to be virtual, but generally speaking,
spinning up a large-scale
environment in a separate, isolated lab infrastructure is not going to be what
most of us are doing.
Now, if you have access to that, absolutely fantastic take advantage of it.
But for the rest of us, we're probably going to want to spin this up in a
virtual environment.
What we're going to use for the rest of this course is a platform known as
Cisco Modeling Labs or CML.
CML is Cisco's version of these lab virtualization platforms that exist out
there in the world.
There are several of these platforms available.
Some of them are open source and therefore are free.
Some of them have enterprise-level licenses, which we have to pay for to get
support.
Cisco Modeling Labs is one that is going to require us to purchase a paid
subscription.
So it comes with a one-year license by default, we can certainly purchase
multiple years.
And fortunately, there is a personal version of this because if we first of all
look at the price of the enterprise edition,
it's going to make us question the sanity of me suggesting that we all purchase
this together.
CML has a personal edition, which again, the enterprise is built for
corporations to have very large-scale,
high-performance lab environments, usually for the sake of testing,
production, and comparing production to what the lab is doing.
But for us, we just need personal. Now, there's personal and then there's also
personal plus licenses.
And the only difference between these is that with personal, we get up to 20
devices, with personal plus, we get up to 40.
For the sake of this course, we're really only going to need the personal
license.
However, certainly, if you want to be able to spin up larger-scale environments
, we go with the personal plus.
So why are we going with CML versus some of the other platforms?
The primary reason for this is because Cisco includes licenses within CML.
So if we want to spin up our own virtual environment in another platform, we
must procure licenses.
And so we're going to have to go purchase those licenses anyways from Cisco in
order to be on the up and up
and make sure that we're doing everything properly.
And as a result, we might as well just purchase CML, and therefore we're given
the licenses.
And very importantly, it includes SDWAN device types.
So I can go to my list of images and I can deploy a validator, I can deploy a
controller, or a manager, or an SDWAN edge.
And so all of that is baked into CML.
It's sort of the easy button for us as far as spinning up an SDWAN environment.
So yes, there are other options.
If we don't want to go with CML, that's perfectly fine.
Maybe you already have a virtual environment that you've spent a lot of time
building up and creating.
And you're fully welcome to continue to use that, especially if you've already
gotten SDWAN up and running
in those environments, even though it can be pretty tricky to get them running,
it is certainly possible.
And maybe you want to continue using that, and that's perfectly fine.
Or if the cost of CML is prohibitive, again, we've got to procure those
licenses in some fashion anyways,
so chances are it's going to be more expensive to go a different route.
Anyways, however, again, there are other options.
So what would happen is that as we create lab challenges in this course, these
lab challenges are going to come with a CML download.
And so this is why I'm going to recommend using CML, because then we can just
simply import the CML file into our environment,
and we wouldn't need to create it ourselves.
However, if we want to use a different platform, we simply have to convert this
file, which there's no automatic way of doing that,
at least at the time of this video, but you could certainly deploy your own
version of that topology into your environment.
The interfaces will look different, the IP addressing scheme might look a
little bit different.
However, in the end, you'll be able to spin up the same topology, so it's just
a matter of deploying a topology that works for you,
and then over the course of time, once the initial configuration is made,
you'll be able to just do all of the other challenges by paying attention to
what has changed in the topologies.
So let's talk hardware, because we are going to need to deploy this,
and we have two different options of deploying CML.
We can do baremetal, and this is going to just require a dedicated server, not
a virtual environment, we're not deploying it as a VM,
we're simply installing it onto a server.
That is certainly one option, not one we usually do, because it's just a lot
easier to spin up a virtual machine,
especially if we already have a virtual environment.
However, if we want to dedicate resources to this, or that matter, if we just
don't have access to a virtual environment very easily,
then we might just want to deploy this onto using the baremetal deployment.
The other option is with VMware ESXi, which is their hypervisor product.
Now, one note here is that there is a free version of VMware, however, it doesn
't allow for us to scale up the resource usage of the virtual machine.
So I believe it's eight VCPUs we get when we're talking about the free version,
it might even be four, this is on a per VM basis, by the way.
And so when we are looking at this, we probably want to get a basic license,
which will allow us to scale up the resources a little bit more.
So if we already have an ESXi environment, then we are in good shape.
If we need to spin one up, we can start with the free version, and just be
aware that the virtual machine won't boot if it is over provisioned from a
resource's perspective.
Now, what resources do we need?
Well, when we're looking at this from a virtual machine perspective or bare
metal either way, we're looking at needing specific amounts of VCPUs.
I would recommend 16 VCPUs to be deployed onto the virtual machine, and I would
also recommend 64 gig of RAM, although I would go a little bit higher than this
if possible.
So maybe 96 gig if it's available, but 64 will suffice for what we're doing
here.
This will just allow us to have like multiple labs turned on at the same time,
potentially, as well as building out larger topologies.
So generally speaking, scaling up these resources means that we can have larger
topologies in general, but this isn't going to be strictly required for what we
do within the course.
It's just a matter of allowing you to be able to spin up your own topologies
and play around with the configuration.
Now, once again, if you are planning to do this via baremetal, then just apply
all of these resource requirements to the baremetal server itself to make sure
that it has the proper resources needed to spin up our environment.
So essentially the way CML works is when we create an environment and we deploy
an image, let's say that this is a manager, for example, well, this is going to
require so many VCPUs and so much gig of memory.
And then I'm going to want to configure a validator.
Well, same thing.
It's going to require some VCPU counts and memory.
A lot of the controllers, for example, take two VCPUs and two gig of memory.
But then if I want to deploy an edge device, well, this actually requires five
gig of memory.
And so we see how we can very quickly eat through, for example, if we only
deploy 16 or 32 gig of RAM, it's not going to carry us very far, especially if
we're not going to do that.
So that's very far, especially if we deploy multiple edges, which is at a
minimum, we're going to want to in our environment.
But if we want three or four, that's going to very quickly consume all of our
memory.
So that is how it ends up working is each one of these sort of creates its own
virtual machine on the back end, which consumes the resources that's being
deployed onto the primary virtual machine itself being CML.
So the only other thing to consider is the license count.
Again, we covered this earlier, but just pay attention to whether personal or
personal plus is your preference.
Personal, again, is going to be plenty for this course.
You're only going to need to upgrade to personal plus if you want to make sure
that you've got the ability to play multiple labs or very large topologies.
We could start with personal and upgrade to personal plus later if that's the
route we decide to go.
So that's it for CML. Let's go ahead and fire it up and make sure we understand
how to get it deployed, how to get it purchased, how to get it licensed, and
then from there we'll be able to do some basic configuration.