236 lines
3.7 KiB
Markdown
236 lines
3.7 KiB
Markdown
*1. Application Description*
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This project is a simple full-stack web application deployed on Kubernetes.
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It allows users to submit names through a web interface and store them in a PostgreSQL database.
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The system consists of:
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A frontend (static HTML interface)
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A backend API built with Node.js (Express)
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A PostgreSQL database running as a StatefulSet with persistent storage
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The backend provides REST endpoints:
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POST /add → adds a name to the database
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GET /names → retrieves all stored names
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2. Containers Used
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Backend (Node.js)
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Image: docker-app-backend:latest
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Purpose: Handles API requests and communicates with the database
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Database (PostgreSQL)
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Image: postgres:15
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Purpose: Stores application data persistently
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3. Kubernetes Objects
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Namespace
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Name: myapp
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Used to isolate all application resources
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Deployment
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Name: backend
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Runs the Node.js backend
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Ensures availability and automatic restart of the backend container
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StatefulSet
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Name: db
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Runs PostgreSQL
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Provides stable identity and persistent storage
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PersistentVolume (PV)
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Stores PostgreSQL data on node storage
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PersistentVolumeClaim (PVC)
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Automatically created via StatefulSet
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Requests storage for database persistence
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Services
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backend-service (NodePort)
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Exposes backend externally
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Accessible at:
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http://localhost:30007
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db service (ClusterIP)
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Enables internal communication between backend and database
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Backend connects using hostname: db
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4. Networking
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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
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5. Persistent Storage
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PostgreSQL uses:
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PersistentVolume (PV) and PersistentVolumeClaim (PVC)
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Using these ensures that data is not lost after pod restart and application state is preserved
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6. Container Configuration
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Backend
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Port: 3000
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Database connection:
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Host: db
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User: user
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Password: password
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Database: mydb
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Database
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Port: 5432
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This uses persistent volume for data storage
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7. Preparation
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Build backend image:
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docker build -t docker-app-backend ./backend
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8. Deployment
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Apply all Kubernetes resources:
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kubectl apply -f namespace.yamlkubectl apply -f deployment.yamlkubectl apply -f service.yamlkubectl apply -f statefulset.yamlkubectl apply -f db-service.yaml
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9. Checking Application Status
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kubectl get all -n myappkubectl get pods -n myappkubectl get svc -n myapp
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10. Accessing the Application
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Backend API:
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http://localhost:30007
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Frontend:
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Open frontend/index.html in a browser
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11. Stopping the Application
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kubectl delete -f deployment.yamlkubectl delete -f service.yamlkubectl delete -f statefulset.yamlkubectl delete -f db-service.yamlkubectl delete namespace myapp
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12. Removing All Resources
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kubectl delete namespace myapp
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13. Used Resources
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Kubernetes Documentation: https://kubernetes.io/docs/
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Docker Documentation: https://docs.docker.com/
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PostgreSQL Docker Image
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Node.js Express Framework
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14. Use of Artificial Intelligence
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Artificial intelligence tools were used to:
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Assist with debugging deployment issues
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Improve configuration of Kubernetes objects
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Help structure the project and documentation
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All implementation, testing, and understanding were performed independently.
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15. Summary
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This project demonstrates:
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Containerized web application architecture
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Kubernetes Deployment and StatefulSet usage
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Persistent storage with PVC
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Internal service communication using DNS
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External access using NodePort
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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. |