A Java Spring and PostgreSQL project with CRUD API operations, containerized setup, OpenAPI-compliant documentation, pre-filled data, and Python Locust load tests for high concurrency simulation in Dockerized environments.

1. 請實作一個 Java Spring Framework project 可對 PostgreSQL 做存取 POST /item GET /item?id=** Reference : https://github.com/bezkoder/docker-compose-spring-boot-postgres

2. https://swagger.io/specification/ 請參考 OpenAPI 3.0 的規範 實作輸出 API Specification https://springdoc.org/

3. 在 Database 內存放上萬筆資料

4. 使用 python locust 對 GET API 做壓力測試 模擬五百位使用者同時呼叫, 產出測試報告 Reference: https://locust.io/

Load parameters into shell environments

• source .env

• docker compose up -d

Make sure using docker ps command to check, app, postgres, python, 3 container is up

Demo App Home Page: http://localhost:8080

• docker compose exec python-env python ./script/tests_post_get_method.py

Result

• docker compose exec postgresdb psql -U $POSTGRESDB_USER -d $POSTGRESDB_DATABASE -c "SELECT t.* FROM public.items t LIMIT 5;"

After step 2., it should have 5 data in the table.

Result

Truncate table

• docker compose exec postgresdb psql -U $POSTGRESDB_USER -d $POSTGRESDB_DATABASE -c "TRUNCATE TABLE items;"

swagger-ui

• URL: http://localhost:8080/swagger-ui/index.html

Result

api-docs

• URL: http://localhost:8080/v3/api-docs

Result

• Python Method with multi-processing
  • docker compose run python-env python ./script/insert_data_python.py

Result

• Or you can use helper script Import Table to save your time
  • ./script/import_table.sh

• docker compose exec postgresdb psql -U $POSTGRESDB_USER -d $POSTGRESDB_DATABASE -c "SELECT COUNT(*) FROM public.items;"

Result

For CLI

• docker compose exec python-env /bin/bash -c "locust -f ./script/locust_items_test.py --headless --users 500 --spawn-rate 100 -H http://app:8080 --run-time 10m"

For WebUI

• docker compose exec python-env /bin/bash -c "locust -f ./script/locust_items_test.py --users 500 --spawn-rate 100 -H http://app:8080 --run-time 10m"
• URL: http://localhost:8089

• Machine: 2022 MacBook Air M2
• CPU: 8-core
• RAM: 24 GB
• Operating System: macOS 13.4.1
• Test Conditions:
  • Users: 500 simulated users
  • Spawn Rate: 100 users/sec
• Results:
  • Requests Per Second (RPS): 164.8
• Note: Performance metrics are specific to the mentioned machine and setup, and may vary on different hardware or configurations.

Other reports can be found in here: ./doc/locust_500_user_report/

• docker compose down --rmi all

Some helper scripts to make life easier

• Load Database Table: ./script/import_table.sh
• Export Database Table: ./script/export_table.sh
• Simple Test POST Script: ./script/tests_post_method.sh
• Simple Test GET Script: ./script/tests_get_method.sh