*1. Application Description*

This project is a simple full-stack web application deployed on Kubernetes.
It allows users to submit names through a web interface and store them in a PostgreSQL database.
The system consists of:


A frontend (static HTML interface)

A backend API built with Node.js (Express)


A PostgreSQL database running as a StatefulSet with persistent storage


The backend provides REST endpoints:


POST /add → adds a name to the database


GET /names → retrieves all stored names



2. Containers Used
Backend (Node.js)


Image: docker-app-backend:latest


Purpose: Handles API requests and communicates with the database


Database (PostgreSQL)


Image: postgres:15


Purpose: Stores application data persistently



3. Kubernetes Objects
Namespace


Name: myapp


Used to isolate all application resources


Deployment


Name: backend


Runs the Node.js backend


Ensures availability and automatic restart of the backend container


StatefulSet


Name: db


Runs PostgreSQL


Provides stable identity and persistent storage


PersistentVolume (PV)


Stores PostgreSQL data on node storage


PersistentVolumeClaim (PVC)


Automatically created via StatefulSet


Requests storage for database persistence


Services
backend-service (NodePort)


Exposes backend externally


Accessible at:
http://localhost:30007


db service (ClusterIP)


Enables internal communication between backend and database


Backend connects using hostname: db



4. Networking


Kubernetes DNS allows communication between differents components of the application using service names. Backend communicates with database using db and external users access backend via NodePort service



5. Persistent Storage
PostgreSQL uses:
PersistentVolume (PV) and PersistentVolumeClaim (PVC)

Using these ensures that data is not lost after pod restart and application state is preserved


6. Container Configuration
Backend


Port: 3000


Database connection:


Host: db


User: user


Password: password


Database: mydb




Database


Port: 5432


This uses persistent volume for data storage


7. Preparation
Build backend image:
docker build -t docker-app-backend ./backend

8. Deployment
Apply all Kubernetes resources:
kubectl apply -f namespace.yamlkubectl apply -f deployment.yamlkubectl apply -f service.yamlkubectl apply -f statefulset.yamlkubectl apply -f db-service.yaml

9. Checking Application Status
kubectl get all -n myappkubectl get pods -n myappkubectl get svc -n myapp

10. Accessing the Application
Backend API:
http://localhost:30007
Frontend:
Open frontend/index.html in a browser

11. Stopping the Application
kubectl delete -f deployment.yamlkubectl delete -f service.yamlkubectl delete -f statefulset.yamlkubectl delete -f db-service.yamlkubectl delete namespace myapp

12. Removing All Resources
kubectl delete namespace myapp

13. Used Resources


Kubernetes Documentation: https://kubernetes.io/docs/


Docker Documentation: https://docs.docker.com/


PostgreSQL Docker Image


Node.js Express Framework



14. Use of Artificial Intelligence
Artificial intelligence tools were used to:


Assist with debugging deployment issues


Improve configuration of Kubernetes objects


Help structure the project and documentation


All implementation, testing, and understanding were performed independently.

15. Summary
This project demonstrates:


Containerized web application architecture


Kubernetes Deployment and StatefulSet usage


Persistent storage with PVC


Internal service communication using DNS


External access using NodePort


The application is fully functional and can store and retrieve data using a Kubernetes-based backend and database. AI was use strictly for learninf concepts and debugging, all coding and implementation was done independently.