Now before we dive deeper into this section
and into working with AWS,
there actually are a couple of things I wanna clarify.
First, if you wanna learn a bit more about the AWS basics,
you can visit our webpage academind.com,
click on browse by topic and go to the AWS sectioned here.
Here you find some AWS resources we get
and especially this Basics playlist,
might be interesting to you.
You also find a link to that playlist attached.
There I get you started with AWS in general,
we talk about a couple of core concepts,
which have nothing to do with containers
but which will help you understand AWS a bit better.
Especially this AWS, VPC and subnets,
part might be interesting to you
since you will see these VPCs and subnets in action
throughout this section here.
So, this is optional
but you might wanna go through this
in case you're wondering what we're working with
and why we're using all these things we are using.
Of course you can also adjust follow along
without that greater knowledge.
But if you consider using AWS for yourself
then I definitely recommend you pick up these basics.
Now, that's AWS in general.
Now, I also briefly wanna explain
this Fargate thing in greater detail.
We did create our first cluster and run our first container
in this task which uses this Fargate thing,
this Fargate runtime, you could say.
Now, this is AWS specific,
and it simply means that AWS will run this container
in an environment where it only creates this server
on which the container runs when it's needed kind of,
of course it does this in a very efficient and fast way,
but it will ensure that we don't always
have a EC2 Instance,
as server up and running,
but only when we need it.
And that server is also fully managed for us,
so that we don't need to worry about updates
or anything like this.
The task size which we can choose down there,
then simply specifies how much memory and CPU
is available for our container when it executes.
And here we by default use the smallest possible choices,
of course, if you are using this in production,
you might wanna consider using more powerful settings here,
but of course the more powerful settings you choose here
the higher your costs will be.
So, for the demo purposes here
the smallest settings will do.
Now of course,
if you use the smallest possible settings here,
this means that if you got a lot of incoming requests,
your container will be up and running handling them.
But at some point, these resources might not suffice.
AWS, ECS then also offers
something which is called Auto Scaling,
where it would actually create
more than one running container at the same time,
with these tasks sizes to help you scale up
and have more containers handling incoming requests.
So, in addition to choosing higher memory
and CPU values here,
you could also configure this scaling later
to be able to handle more workload with your container.
That's all not something we need here in this course
and for this demo application,
I just want to clarify what this ECS
and this Fargate thing is about,
and what you should watch out for
if you wanna dive into AWS deeper
and if you plan on using this for your own real application.
Of course also check out the AWS, ECS
and Fargate documentations in that case.
With that, we don't need to change anything at the moment,
I just wanted to briefly mention this
to ensure that we're all on the same page
and these values are no mystery to you.