Waiting List APP

About the Application

This is a waiting list application that is used to put customers of a restaurant on a waiting list. I used the java framework Spring Boot and to store the data of the customers and restaurant I used MongoDB. Several endpoints have been created and all the API's are documented using Swagger2 which you can find below.

Demo

How to build

To run this application you must do the following below.

• Clone this repository
• Have node and npm installed locally on your machine
• Make sure that you are using JDK 11, 13, or 15 and have Maven installed.
• Once the application is succesfully build you can run it with one of these two methods.

docker-compose -up .

or run:

mvn spring-boot:run  

Installation

To install the application run npm install which will download all the packages and dependencies for the application.

To Run Application Front End

To run this app locally run npm start which Runs the app in the development mode.\ Open http://localhost:3000 to view it in the browser. The page will reload if you make edits.\ You will also see any lint errors in the console.

Environment Variable

You will need to set these environment variables when running locally

How to test

There are two tests in this application one that tests all the endpoints in the backend called Waitlist App Tests and another test called Integration Test that tests both the front end and backend. To run both tests you would first need the front end running for the Integration tests the command to run the front end is below and once the that is done you will be able to run both tests together using another command below.

to run the front end:

npm start

run both tests together:

mvn test

Load Testing

Load testing is set up using Locust. To have locust running ensure that python or python3 is installed on your machine and that pip is installed as well. Once those are installed you must then install locust using the command below.

To install locust

pip install locust

To run locust

locust -f loadTesting.py --host=http://localhost:8080

Configure Mongo Atlas Database

To set up your own database you must first create an Atlas account. Once that is done create a cluster select your preferred cloud provider and region enter your cluster name and deploy that cluster. The next step is to add your current IP address to set up a connection. Then create a new username and password to access your database and collections to your cluster. After that is all done download MongoDB Compass which allows you to connect to your database and create new collections.

For a more detailed explanation follow this link https://docs.atlas.mongodb.com/getting-started/.

Setting up Feature Flags

• To set up any of your own customer feature flags you must first create an account on Optimizely https://www.optimizely.com/rollouts-signup/?utm_campaign=asa-react-flags-video.
• • Once that is done you must install the Install the Optimizely React SDK the command to install it is below.

    npm install --save @optimizely/react-sdk

• You then create a feature flag and instantiate Optimizely in your React App
• Once this is set up you will be able to create your own feature flag and set it up.
• For more information here is a link to a tutorial on implementing a feature flag in your react app. https://www.youtube.com/watch?v=A8eoGwDhz0k

Here are some endpoints you can call:

Get information about customer, table, and restaurant.

• Get all customers http://localhost:8080/Customer/findAllCustomers.
• Get customer by id http://localhost:8080/Customer/findAllCustomers/{id}
• Get all tables in restaurant http://localhost:8080/Table/findAllTables
• Get table by id http://localhost:8080/Table/findAllTables/{id}
• Get all restaurants http://localhost:8080/Restaurant/findAllRestaurants
• Get restaurant by id http://localhost:8080/Restaurant/findAllRestaurants/{id}
• Get number of customers http://localhost:8080/Customer/customerCount

To add a new customer, table, or restaurant.

• http://localhost:8080/Customer/addCustomer
• http://localhost:8080/Table/addTable
• http://localhost:8080/Restaurant/addRestaurant

To view the Swagger2 API docs

• http://localhost:8080/swagger-ui.html#