Spring PetClinic Application with the Elastic Stack

The PetClinic application contains a few components (See architecture diagram at the bottom for details):

• The React frontend web application
• The Node.js Express application acting as a proxy for the React web application.
• The Spring Boot backend application.
• The Python application for address lookup from an Elasticsearch cluster.

A Docker Compose allows the user to run the application, backed with MySQL as the data layer, with Elastic APM and Beat instrumentation enabled. The following services are deployed:

• Pet Clinic via embedded Tomcat with REST API. Instrument with Elastic Java Agent.
• React UI for Pet Clinic using above. Instrument with Elastic RUM Agent.
• Elasticsearch
• Kibana
• MySQL

Running Petclinic with the Elastic Stack

ES_VERSION=8.1.0 docker-compose -f docker-compose.yml up

Running petclinic locally for development

See instructions for each of the components of the application.

First of all, set your Elasticsearch cluster information inside the script bin/setAPMenv.sh and run the script. All the components rely on the environment variables to connect to your Elasticsearch cluster.

• Start the Spring Boot backend

	git clone https://github.com/tuurleyck/spring-petclinic.git
	cd spring-petclinic
	./mvnw spring-boot:run

• Start the Python address finder

	cd spring-petclinic/address_resolver/src
	pip3 install gunicorn json-logging-py
	pip3 install --no-cache-dir -r requirements.txt
  python3 data_load.py
	gunicorn --config gunicorn.conf --log-config logging.conf -b :5000 server:app

• Start the node.js proxy application

	cd spring-petclinic/frontend/server
	npm install
	npm start

• Start the React frontend

	cd spring-petclinic/frontend/client
	npm install
	npm start

Understanding the Spring Petclinic application with a few diagrams

See the presentation here

Application Architecture: