Spring Boot Product Catalog

With Embedded Database(Mongo)

With External Database(Mongo) support

With Docker and Docker Compose ready containerization

The README covers on the operational part of Catalog. For more details on the code level walkthrough / developer point of view, please contact developer.

Note

  • Only Mongo is supported as external Database
  
  				Or
  
  • Embedded Mongo is supported, which is non-persistent and data is lost, thus eliminating the need for external for demo runs and unit tests.

Instant local set-up - Refer to Local Environment SetUp

Overview

The idea is to build a single production grade Spring Boot Jar with the following

  • Restful APIs for Product Catalog management - Create, Update, View, Delete Products.

Tech / Framework used

  --> Docker Image to host the Jar. (Will be added soon - with pre built jar inside docker image)
  			
  --> Spring Boot - 2.2.4 Release
		
        • Mongo
        
        • JPA
        
        • OpenAPI Swagger UI
        
        • Logbook Splunk style HTTP logging

Build using maven

	cd <to project root folder>
	mvn clean install
	
The maven build should place the catalog-${CATALOG_VERSION}.jar inside the target folder.

Build Docker Image

After Maven Build. Build the Docker Image with the following command

    docker build -t catalog:latest .

Verify docker image with

    docker images

Run Catalog : Java

	cd <to project root folder>/target
	
Below command will start the Catalog, please pass the database connection details along (default values shown below)
    java \
  -DMONGODB_HOST=localhost \
  -DMONGODB_PORT=27017 \
  -DMONGODB_USERNAME=catalog \
  -DMONGODB_PASSWORD=Catalog!234 \
  -DMONGODB_DATABASE=catalog \
  -jar catalog-0.0.1-SNAPSHOT.jar

Application URLs

	HTTP
		a) http://localhost:8080/ - To access the Swagger pertaining to APIs for Product Catalog

Run Catalog Boot : Docker

To run the container :

  docker run --name catalog -p 8080:8080 \
        -e ENV MONGODB_HOST=localhost \
        -e MONGODB_PORT=27017
        -e MONGODB_USERNAME=root
        -e MONGODB_PASSWORD=Root!234
        -e MONGODB_DATABASE=catalog \
        -d catalog:latest

All the below mentioned configurables / properties (under Available Profiles section) can be passed as Docker Container environment variables and will be set accordingly.

Run Catalog : Docker Compose

To run the docker-compose : For externalizing database into different containter, using their corresponding official dockerhub images.

docker-compose up or docker-compose -d (For deamonizing the processes)

If -d was used, then after the containers startup, logs can be verified by the following command (the same command can be used in new terminal / command prompt window in case -d wasn't used)

docker logs --follow catalog_catalog_1

Once all containers are started successfully, the "docker ps" output should look something similar to below.

CONTAINER ID   IMAGE                   COMMAND                  CREATED          STATUS                   PORTS                                              NAMES
2cc0e92ebf50   catalog:latest          "/bin/bash /appln/sc…"   5 minutes ago    Up 2 minutes (healthy)   0.0.0.0:8080->8080/tcp                             catalog_catalog_1
718dea9898f0   mongo:latest         "/docker-entrypoint.…"   5 minutes ago    Up 3 minutes (healthy)   0.0.0.0:27017->27017/tcp                             catalog_mongodb_1

For mapping volumes i.e. having persistent container data, follow these steps.

1) Create the following directories (These are custimizable to match docker-compose.yml volumes definitions)

    container/persistence/mongo

2) Uncomment the volumes section under Mongo

Test Case - 1

Open http://localhost:8080 in browser (Preferably Chrome)

1. Get Product Details

      Request
            ID : 13860428
   
      Response
          {
              "id": 13860428,
              "name": "The Big Lebowski (Blu-ray)",
              "current_price": null
          }
   

   Notice the name returned is from RedSky API Response "The Big Lebowski (Blu-ray)" and price is null as there is no price persisted yet, which will be done in #2 and reverified in #4 below.

2. Post new Product Pricing Request

        {
            "id": 13860428,
            "name": "Placeholder Name - from Database",
            "current_price": {
            "value": 13.49,
            "currency_code": "USD
        }
   

3. Post new Product Pricing Request

        {
            "id": 123456,
            "name": "RedSky Non existant - from Database",
            "current_price": {
            "value": 33.49,
            "currency_code": "USD
            }
        }
   

4. Get Product Details

      Request
            ID : 13860428
   
      Response
          {
              "id": 13860428,
              "name": "The Big Lebowski (Blu-ray)",
              "current_price": {
              "value": 13.49,
              "currency_code": "USD"
              }
          }
   

   Notice the name returned is from RedSky API Response "The Big Lebowski (Blu-ray)" and not from database "Placeholder Name - from Database"

5. Get Product Details

   Request
        ID : 123456
   
   Response
        {
            "id": 123456,
            "name": "RedSky Non existant - from Database",
            "current_price": {
            "value": 33.49,
            "currency_code": "USD
            }
        }
   

   Notice the name returned is NOT from RedSky API Response as its not found on RedSky and from database "RedSky Non existant - from Database"