Part 1: Cloud Native Development, Microservices and the Architecture of our Covid-19 Data Parser¶

Agenda¶

In this section you will learn:

An overview of Covid-19 data analytic web application

• Quick summary
  • Data source & format
  • Data Parser
  • REST APIs endpoints
• Microservices
  • Why microservices?
  • Orchestration with Kubernetes

Our application has been developed in Java and Spring Boot framework. It provides us with a number of API endpoints for retrieving covid-19 data per region, country, dates and periods. It comes with a number of containerised microservices, including 2 x data parsers for positive cases and mortality rates per country, and a User Interface for displaying data, as well as invoking those APIs through a number of sample functions.

As you can see from the slide, data is fetched from Johns Hopkins University's repo (which is an authentic source of covid-19), and is stored in our local data repository.
Here is a list of sample API endpoints as we'll test them out shortly.

Prerequisites¶

Spring Boot v2.2 - https://spring.io/guides/gs/spring-boot/

OpenJDK v11 - https://openjdk.java.net/install/

(Optional) Apache Netbeans IDE v12 - https://netbeans.apache.org/download/

Node.js v14 - https://nodejs.org/en/download/

Docker Latest - https://docs.docker.com/engine/install/

Minikube Latest - https://kubernetes.io/docs/tasks/tools/install-minikube/

CodeReady Containers - https://developers.redhat.com/products/codeready-containers

(Optional) OpenShift v4.3 on IBM Cloud - https://www.ibm.com/cloud/openshift

Microservices¶

By the end of this series, you'll have a microservices application with 4 x containers running in your Kubernetes/OpenShift cluster.

• Data Parser written in Java.
• UI frontend written in Java to generate HTML and Node.js.
• Analytical application wrtittn in Python Flask.
• Data Visulization application written in Node.js