UWA Git Good Presentation

Demonstration files to build and deploy a sample Python Flask web application to Docker Hub and Amazon Web Services (AWS).

Assumptions

• You will need a Docker Hub account.
• You will need to create a Docker Access Token and add it as a secret to your GitHub repository. Please see the reference Build and push Docker images in the REFERENCES.md file.
• You will need an Amazon Web Services Account.
• All AWS resources are used in this repository fall under the AWS Free Tier, however if you do deploy this to your AWS account, you are responsible for any costs incurred.
• You already have the default Amazon S3 Bucket used by AWS CodePipeline.
• The Amazon EC2 web server will be deployed in the default VPC of your AWS account. If you are deploying this for a production environment, it is recommended to create a new VPC.
• All AWS resources are deployed in the Asia Pacific (Sydney) ap-southeast-2 Region.
• You will need to have setup the connector between GitHub and AWS. More information can be found here.

Automated GitHub Actions

Please see the table below for an overview of the implemented GitHub actions, these files can be found the following directory: .github/workflows/

GitHub Action File Name	Description	Affected Branches	Event Type
push_to_docker_hub.yml	Runs unit tests, build and pushes the Docker container to Docker Hub	main	Push to single branch
python_linting.yml	Run Python PEP 8 formatting over the codebase and creates an new pull request if the linting fails. An example can be seen here: #17	main and develop	Push to multiple branches
python_unit_tests.yml	Runs pytest unit tests against the codebase	main and develop	New Pull Requests

AWS CodePipeline Pipeline

Overview

A pipeline has been created that runs unit tests of the codebase and deploys the Python Flask web application to an Amazon EC2 instance. The pipeline is executed when changes are made to the main branch.

Deploying the Pipeline

1. Login to the AWS Management Console.

2. Change your Region to ap-southeast-2 (Sydney) (if you haven't already).

3. Once logged in, navigate to the AWS CloudFormation Console.

4. Create a new Stack with new resources.

5. Choose the Upload a template file option and upload the following file pipeline/pipeline.yml, then press Next.

6. Enter the following for the Stack name: UWA-Git-Good-Presentation-Pipeline

7. Enter the GitHub connector ARN for the GitHubConnectionArn parameter.

8. Enter the name of the Amazon S3 bucket used by AWS CodePipeline for the PipelineAmazonS3Bucket parameter.

9. Press Next.

10. Press Next again.

11. Scroll down to the bottom of the page and select the I acknowledge that AWS CloudFormation might create IAM resources checkbox, then press Create stack.

12. Once the pipeline stack has been deployed, it will automatically deploy the Python Flask web application to AWS.

Installation

Run the following commands to download and install the required Python Dependencies:

sudo apt install python3-flask -y
sudo pip3 install -r requirements.txt

Code Linting

To run linting over the code, run the following commands in Visual Studio Code:

1. Press F1.

2. Search for Python: Run Linting.

3. Press CTRL + ~ to open the inbuilt Terminal.

4. Select PROBLEMS and address the identified linting issue(s).

Running Unit Tests

To run all unit tests, run the following command:

python3.10 -m pytest tests/

If you want to print the tests standard output to the screen, run the following command:

python3.10 -m pytest -s tests/

Local Development

Complete this section if you want to develop and run the code locally.

Running the Web Application

Run the following command to start the web application:

flask run

Docker Container Development

Complete this section if you want to build and run a Docker container

Build Docker Container

To build the Python web application Docker Container, run the following command:

docker build -t uwagitgoodwebapp .

Run Docker Container

To run the Python web application Docker Container, run the following command:

docker run -it --rm -p 80:5000 uwagitgoodwebapp:latest

Web Application Usage

The usage commands are slightly different when running the code locally or using a Docker container. Follow the instructions based on how you plan to run the code.

Local Usage

Follow this section if you are going to run the Python code on your local machine and not use a Docker container:

Main Webpage

Open a web browser and navigate to:

http://127.0.0.1:5000/

or open a Terminal and run the following command:

curl -X GET http://127.0.0.1:5000/

Greeter API - Default Response

Open a web browser and navigate to:

http://127.0.0.1:5000/greeter

or open a Terminal and run the following command:

curl -X GET http://127.0.0.1:5000/greeter

Greeter API - Custom Response

Open a web browser and navigate to:

http://127.0.0.1:5000/greeter?name=test

or open a Terminal and run the following command:

curl -X GET http://127.0.0.1:5000/greeter?name=test

You can change the value of name to any string value of your choosing.

Docker Container Usage

Follow this section if you are going to run the Python code as a Docker container:

Main Webpage

Open a web browser and navigate to:

http://127.0.0.1/

or open a Terminal and run the following command:

curl -X GET http://127.0.0.1/

Greeter API - Default Response

Open a web browser and navigate to:

http://127.0.0.1/greeter

or open a Terminal and run the following command:

curl -X GET http://127.0.0.1/greeter

Greeter API - Custom Response

Open a web browser and navigate to:

http://127.0.0.1/greeter?name=test

or open a Terminal and run the following command:

curl -X GET http://127.0.0.1/greeter?name=test

You can change the value of name to any string value of your choosing.

AWS Lab Cleanup

If you have deployed the AWS CodePipeline pipeline in your AWS account, follow the instructions to delete and cleanup your AWS account:

1. Login to the AWS Management Console.

2. Change your Region to ap-southeast-2 (Sydney) (if you haven't already).

3. Once logged in, navigate to the AWS CloudFormation Console.

4. Select the UWA-Git-Good-Presentation-Webserver stack, press Delete then Delete stack.

5. Once the UWA-Git-Good-Presentation-Webserver stack has been deleted, select the UWA-Git-Good-Presentation-Pipeline stack, press Delete then Delete stack.

6. Navigate to the Amazon S3 Console.

7. Empty the default Amazon S3 Buckets used by AWS CloudFormation and AWS CodePipeline.