-: All right, my friends, that's pretty much it.
We've set up everything we need to set up for Kubernetes
at least in our development local environment.
We're now gonna start thinking
about how we can take this application
and deploy it off to a production environment instead,
such as AWS or Google Cloud.
Now, before I show you a diagram that's gonna walk through
the series of steps that we're going to use to deploy this,
just one quick last thing.
Again, if you're seeing the not secure message up here,
totally fine in a development environment.
We're going to eventually fix this
in the production environment.
But again, in development, no issue whatsoever.
Okay, so let's walk through our deployment steps.
So the first thing we're going to do
is create a GitHub repository.
We're gonna create a GitHub repo.
We'll also create a GI repo locally on our local machine
and then push all of our code up to GitHub.
After that, we're gonna set up a Travis CI project
to tie in with our GitHub repo as well.
So we're going to use a very similar
Travis CI focused deployment method as we did previously
on both of our Elastic Beanstock projects.
Travis CI is going to be in charge of building our images
and pushing them off to Docker Hub.
And then after that, we're going to use Travis CI
to also deploy our application to a Kubernetes cluster.
You can use other CI environments
if you choose to, in general, maybe not in this course.
I recommend you do use Travis along with me.
But in general, you could use other deployment
or other CI environments such as Circle CI if you choose to.
They were just as well as Travis.
Just in this course, I chose to use Travis
because in general it's a very reliable service
which makes it quite appropriate for a course.
After that, we're gonna set up a Google Cloud project.
So again, we're not going to deploy
this Kubernetes application to AWS.
We're going to using Google Cloud instead.
And I've got a whole slide that I'm gonna show you
in this video in like one or two minutes
that's going to outline the reasons that we're swapping
from AWS over to Google Cloud.
Again, trust me, very good reasons that we're going to use
Google Cloud here as opposed to AWS.
Now, something that's very important,
and this is really the main point of this entire lecture,
is that in order to deploy this application
off to Google Cloud, you will need to enable billing
on a Google Cloud account.
And that means that you need a credit card
or some type of payment card that is accepted
by Google Cloud.
Now, if you are in some country
that does not have access to Google Cloud,
unfortunately you're probably not going to able to walk
through these deployment steps
but that is just kind of the reality of the situation.
Now, the billing aspect here is rather important
to mention this time around. because unlike
the Elastic Beanstock stuff where we paid $0
if you were in the free tier or you paid very little
if you were outside the free tier,
unfortunately this Kubernetes project is going to encourage
just a little bit of billing and it probably
is going to be for the most part unavoidable.
Now, I wanna very quickly show you a calculator
that you can use to get an idea of how much
you're going to be paying for this Kubernetes project
that we're going to set up.
Just so you know, I put like all the Travis CI stuff
up here, even though It kind of makes sense to create
the Google project first.
I put all the Travis CI stuff earlier up here
to just to minimize the amount of time
that we have to have this Kubernetes cluster
up and running and causing you to have to pay money.
So I am very much conscious of the fact that
you probably don't wanna be paying a lot of money
to learn all this stuff.
Now, if you wanna get a good idea on how much
you're going to be paying, you can do a Google search
for Google Cloud cost calculator.
Like so, you'll find the first result here
which is products slash calculator.
And then on this page, we can very quickly get an idea
of exactly how much money you might be paying
over a short period of time
that you might be running this application.
So on this page, and I'm gonna zoom in a little bit here
just to make sure it's very legible,
you can select Kubernetes engine at the top.
And then under Kubernetes engine,
we're going to be running three separate notes.
We're going to be using the standard instance type
so you can leave that as the same.
So I'm gonna scroll down, leave everything else the same
and I'm gonna click Add to Estimate.
I will then find the persistent disc section.
On here we're going to have one persistent disc
that's gonna have like two gigabytes of space.
Two like so, so you can add in a two
and then a click Add to Estimate.
And then you can also find load balancing right here.
We're going to have one forwarding rule
and we're going to at best be transferring
about one gigabyte, like absolute no way
we're going to actually be doing one gigabyte here.
I guess you could go down to megabyte if you want to.
And we could probably say like something like
a 100 megabytes is probably much more realistic.
And then you can add that as an estimate as well.
So if you look at the total price for all this thing,
it comes out to around $42 per month.
Now, if you're running this for only one day
because the billing here is like on a per minute basis
or something like that.
So if you go through all the Kubernetes videos
in this course in like one day,
then you're going to paying about $42 divided by 30.
So that's something like, I don't know, a $1.40
or something like that total.
So $1.40 if you get through everything in here in 24 hours.
If you get through it faster and shut everything down,
you'll be paying even less.
So in general, probably not gonna be paying
anywhere near $42 as long as you complete
all this content in a reasonable amount of time.
I just want you to be aware that you are gonna be paying
at least some tiny amount of money here.
And you do really need to make sure
that you absolutely clean up all these instances
after you get through this content,
especially if you like quit halfway through.
You need to be making sure that you close everything down.
And, of course, at the end of the Kubernetes section,
I'll give you a very detailed video
on how you clean all this stuff up as well.
Okay, so that's my spiel on pricing.
Now, we're gonna a little bit long here
so let's take a quick pause and when we come back
to the next section, we're gonna talk a little bit
about why we're making use of Google Cloud over AWS.
So quick pause and we'll cover that in the next section.