team-devvopps

System Architecture

Microservices

The backend consists of 3 independent Spring Boot microservices behind an API Gateway:

• api-gateway (port 8080): Routes all incoming requests to the appropriate service
• user-service (port 8081): User management
• course-service (port 8082): Mock TUM course database (source of truth for university courses)
• roadmap-service (port 8083): Personalized learning roadmap generation and tracking

Each service has:

• Its own PostgreSQL database (userdb, coursedb, roadmapdb)
• Independent entity models with auto-created schema
• REST API endpoints

Entity Relationships: See the UML diagram in /server/docs/ for complete data model and relationships.

---

Running with Kubernetes (Recommended)

The fastest way to run the entire stack. Requires Docker Desktop with Kubernetes enabled.

Prerequisites

• Docker Desktop with Kubernetes enabled
  • Docker Desktop → Settings → Kubernetes → Enable Kubernetes → Apply & Restart

1. Verify Kubernetes is running

kubectl get nodes
# Expected: docker-desktop   Ready   control-plane

2. Build images and deploy

make k8s-deploy

This builds all 5 Docker images and applies all Kubernetes manifests automatically. Waits until all pods are ready.

3. Check status (optional)

make k8s-status

5. Access the application

• React Client: http://localhost:30000
• API Gateway: http://localhost:30080

Tearing down

make k8s-down

---

Running with Docker Compose

Runs the full stack with a single command. No Kubernetes required.

Prerequisites

• Docker Desktop (must be open and running)

Start the full stack

make docker-up

Access the application

• React Client: http://localhost:3000
• API Gateway: http://localhost:8080

Stop

make docker-down

Reset the database

make docker-reset

---

Running Locally (Development)

For active development without Docker for the services.

Prerequisites

• Docker Desktop (for PostgreSQL only)
• Miniconda or Anaconda
• Java 25 (included in conda environment)

1. Setup environment

conda env create -f environment.yml
conda activate team-devvopps

2. Start PostgreSQL

conda activate team-devvopps
cd server
docker-compose up

This starts PostgreSQL on port 5432 with 3 databases: userdb, coursedb, roadmapdb.

3. Start Spring Boot services

make dev

All 4 services start in the background. Logs are written to logs/ directory:

tail -f logs/user-service.log
tail -f logs/api-gateway.log

To stop all services:

make dev-stop

Services available at:

• API Gateway: http://localhost:8080
• user-service: http://localhost:8081
• course-service: http://localhost:8082
• roadmap-service: http://localhost:8083

4. Start the frontend

conda activate team-devvopps
cd client
npm install
npm run dev

Frontend available at: http://localhost:3000

5. Populate course database (first time only)

conda activate team-devvopps
cd server/course-service
python3 fetch_and_seed_courses.py   # macOS/Linux
python fetch_and_seed_courses.py    # Windows

Fetches ~930 courses from the TUM Campus Online API into coursedb. Only needs to be run once.

Reset local database

cd server
docker-compose down
docker volume rm server_postgres_data

Then repeat steps 2–5.