- [Alana] So, you're now ready for the next exercise.
This is where we put all the pieces
of what we learned together.
If you took the first class in the series,
you'll already be familiar with CodeCommit,
CodeBuild, and CodePipeline, and in this course,
you spent time learning about CodeDeploy and CloudFormation.
So, if we're using all of these services,
what could this lab possibly be about?
Well, you might have already guessed it.
You'll be automating the creation
of an entire CI/CD pipeline.
Here's how this will work.
I'll provide you the template that I showed
in the Automation of a Pipeline video.
You'll upload this template to CloudFormation,
and it will provision every piece of your pipeline,
including CodeCommit, CodeBuild, and CodeDeploy.
It will also kickstart your pipeline initially.
Take a look at the template and try to understand
each resource that gets created.
You can also see some of the CloudFormation features
that Raf mentioned earlier, such as the Parameters section.
For example, one of the parameters is an AMI ID
for the EC2 instance.
Instead of you specifying an Amazon Machine Image,
or AMI ID, the template grabs the latest AMI ID
from AWS Systems Manager Parameter Store,
so you don't have to worry about choosing the wrong AMI.
After you provision the template,
you'll look at the pipeline that CodePipeline created
and check the output of the pipeline,
which is the application on your EC2 instance,
in this case, a website that shows a blog.
The other output of the pipeline is your acceptance test.
We've populated the CodeCommit repository
with a buildspec that shows the acceptance tests
we'll be performing on this application.
I'll display that same file on screen.
As you can see, we're getting the IP address of the server,
using cURL to get data from that IP address,
and the result we should get is the index.html page,
when we go to look at the output of this test.
That'll tell us that the website is reachable.
From there, you'll make a change to the index.html file
in the repository, which will kick off
the pipeline once again.
You'll then check the results of that pipeline by verifying
the code on your instance was changed.
Once again, feel free to post in the forums
if you run into any issues.
All right, let's get started with Exercise 3.