Auto Shop

Auto Shop is made up of 4 individual microservices written in python using the flask framework: Attached below is the architectural breakdown.

• PortalService: The frontend of application storefront allowing you to view order or purchase items
• ProductManagement: Flask API communicating with MongoDB Atlas to fetch all and individual products.
• OrderManagement: Flask API communicating with MongoDB Atlas to store purchased orders and generate orderId upon purchase
• NotificationGateway: Flask API built using Mailjet to send email when purchase is made

How do I run the Autoshop?

Prerequisites:

1. Create Free MongoDB Atlas Account: https://www.mongodb.com/cloud/atlas/register
2. Create MongoDB Cluster: https://www.mongodb.com/docs/guides/atlas/cluster/
3. Create Free MailJet Account: https://app.mailjet.com/signup?lang=en_US
4. Python 3 Installed: https://www.python.org/downloads/
5. Fork repository and clone onto your machine

What next?

1. You will need to store your mongodb username, password, and cluster in the OrderManagement, ProductManagement, and NotificationGateway {service}/src/.env file

MONGO_USERNAME=
MONGO_PASSWORD=
MONGO_CLUSTER=

2. You will need to store your Mailjet API Key and Session in your NotificationGateway {service}/src/.env file

MAILJET_API_KEY=
MAILJET_API_SECRET=
MAILJET_SENDER_MAIL=

3. Create a virtualenv in the root of the project then activate it

python3 -m venv venv
source venv/bin/activate

4. In order to successfully run each microservice, you will need to open 4 terminal windows
5. cd into each service and run the following. This will install the required dependencies each service needs into your virtual environment

pip install -r requirements.txt

6. run each service with the following

python3 app.py

7. Open PortalService in https://127.0.0.1:5001

Running GitActions:

In the forked repository, you will need to:

1. Add DOCKER_USERNAME, and DOCKER_PASSWORD to your Settings > Secrets & Variables > Actions.
2. With a push to the main branch, git actions will trigger CI/CD Pipeline to build docker images
3. Script can be found in .github/workflows/automation.yaml

Running in Kubernetes:

The below will create the namespace app with the deployments and services needed to run the application

$ cd kubernetes/
$ kubectl apply -f autoshop-deployment.yaml

To then view the application in the browser run

$ kubectl port-forward svc/portal 5001:5001 -n app

Running locally with python:

you will need to cd into each service and run

$ opentelemetry-instrument python3 app.py

Running Docker Compose:

To run in docker reference the following docker-compose.yaml by running

$ docker-compose up