D4 Platform, Security and Integration

Repository: d4-platform-devops

Project: Healthcare Monitoring System

This repository contains the platform, security, deployment, logging, monitoring and integration work for Group D: Healthcare Monitoring System. The main purpose of D4 is to make sure the full healthcare monitoring system can run securely, connect with all other groups, and be monitored properly during testing and deployment.

1. What D4 Is Responsible For

D4 is not mainly responsible for collecting sensor data, building the AI model, or designing the doctor dashboard. Those parts are handled by D1, D2 and D3.

D4 is responsible for making the full system:

Secure
Deployable
Connected
Observable
Maintainable
Easy to test end-to-end

In simple terms:

D4 makes sure the whole healthcare monitoring system can be started, secured, connected, logged, monitored and tested as one working platform.

2. Team Responsibilities

The full project is divided into four main groups.

Group	Area	Main Responsibility
D1	Device and Edge Systems	Collect vital signs from wearable or edge devices and send data securely
D2	Data and Intelligence	Analyze time-series data, detect anomalies and generate risk scores
D3	System Engineering and Interaction	Build doctor dashboard, patient interface and alert viewing interface
D4	Platform, Security and Integration	Secure, deploy, monitor and integrate the whole system

3. D4 Main Deliverables

D4 should deliver the following main outputs:

Dockerized system setup
Keycloak authentication system
JWT-based API protection
Secure environment configuration
Logging structure
Prometheus metrics collection
Grafana monitoring dashboard
Integration testing with D1, D2 and D3
Deployment documentation
Final system run guide

4. Recommended System Architecture

Wearable / Edge Device
        |
        |  Vital signs data
        v
MQTT Broker / API Gateway
        |
        v
Backend API Service  <------>  Keycloak Authentication
        |
        v
PostgreSQL Database
        |
        v
Anomaly Detection Service
        |
        v
Doctor Dashboard / Patient Interface

Monitoring Layer:
Backend API + Database + Services
        |
        v
Prometheus
        |
        v
Grafana

5. D4 Technology Stack

Area	Tool	Purpose
Containerization	Docker	Package services into containers
Multi-service setup	Docker Compose	Run backend, database, Keycloak, Prometheus and Grafana together
Authentication	Keycloak	Login, user management and role-based access control
API Security	JWT	Secure backend APIs using access tokens
Database	PostgreSQL	Store patient readings, users, alerts and system data
Metrics	Prometheus	Collect system and application metrics
Dashboards	Grafana	Visualize system health and metrics
Logging	Backend logger / Docker logs	Track important system events and errors
Deployment	Docker / optional Kubernetes	Run the system on another machine or server

6. Expected Repository Structure

A recommended structure for this repository is shown below.

d4-platform-devops/
│
├── README.md
├── docker-compose.yml
├── .env.example
├── .gitignore
│
├── docs/
│   ├── architecture.md
│   ├── authentication.md
│   ├── deployment.md
│   ├── monitoring.md
│   ├── logging.md
│   ├── security.md
│   └── testing.md
│
├── keycloak/
│   ├── realm-export.json
│   └── README.md
│
├── prometheus/
│   ├── prometheus.yml
│   └── README.md
│
├── grafana/
│   ├── dashboards/
│   │   └── healthcare-monitoring-dashboard.json
│   ├── provisioning/
│   │   ├── dashboards/
│   │   └── datasources/
│   └── README.md
│
├── scripts/
│   ├── start.sh
│   ├── stop.sh
│   ├── reset.sh
│   └── test-health.sh
│
└── tests/
    ├── auth-test.md
    ├── integration-test.md
    └── security-test.md

This exact structure can be changed later depending on how D1, D2 and D3 organize their repositories.

7. Services to Run

The full system may include these services.

Service	Description	Owner
Backend API	Receives vitals, stores data and exposes APIs	D2 / D4 integration
Frontend Dashboard	Doctor or patient interface	D3 / D4 integration
PostgreSQL	Main database	D4
Keycloak	Authentication and user roles	D4
Prometheus	Metrics collector	D4
Grafana	Monitoring dashboard	D4
MQTT Broker	Receives device data from D1	D1 / D4 integration
AI Service	Detects anomalies and risk level	D2 / D4 integration

8. Dockerization Plan

Dockerization means packaging each service so that the system can run without manually installing many dependencies.

8.1 Services to Dockerize

Minimum required services:

backend
frontend
postgres
keycloak
prometheus
grafana

Optional services:

mqtt-broker
anomaly-detection-service
nginx-reverse-proxy

9. Example Docker Compose Structure

The final docker-compose.yml should follow a structure similar to this.

version: "3.9"

services:
  postgres:
    image: postgres:16
    container_name: hms-postgres
    restart: unless-stopped
    environment:
      POSTGRES_DB: ${POSTGRES_DB}
      POSTGRES_USER: ${POSTGRES_USER}
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
    ports:
      - "5432:5432"
    volumes:
      - postgres_data:/var/lib/postgresql/data
    networks:
      - hms-network

  keycloak:
    image: quay.io/keycloak/keycloak:latest
    container_name: hms-keycloak
    restart: unless-stopped
    command: start-dev
    environment:
      KEYCLOAK_ADMIN: ${KEYCLOAK_ADMIN}
      KEYCLOAK_ADMIN_PASSWORD: ${KEYCLOAK_ADMIN_PASSWORD}
    ports:
      - "8080:8080"
    networks:
      - hms-network

  prometheus:
    image: prom/prometheus:latest
    container_name: hms-prometheus
    restart: unless-stopped
    volumes:
      - ./prometheus/prometheus.yml:/etc/prometheus/prometheus.yml
    ports:
      - "9090:9090"
    networks:
      - hms-network

  grafana:
    image: grafana/grafana:latest
    container_name: hms-grafana
    restart: unless-stopped
    environment:
      GF_SECURITY_ADMIN_USER: ${GRAFANA_ADMIN_USER}
      GF_SECURITY_ADMIN_PASSWORD: ${GRAFANA_ADMIN_PASSWORD}
    ports:
      - "3000:3000"
    volumes:
      - grafana_data:/var/lib/grafana
    networks:
      - hms-network

volumes:
  postgres_data:
  grafana_data:

networks:
  hms-network:
    driver: bridge

This is a base structure. Backend, frontend, MQTT and AI services can be added after D1, D2 and D3 finalize their service details.

10. Environment Variables

Create a .env.example file like this.

# PostgreSQL
POSTGRES_DB=healthcare_monitoring
POSTGRES_USER=hms_user
POSTGRES_PASSWORD=change_this_password

# Keycloak
KEYCLOAK_ADMIN=admin
KEYCLOAK_ADMIN_PASSWORD=change_this_password
KEYCLOAK_REALM=healthcare-monitoring
KEYCLOAK_CLIENT_BACKEND=hms-backend
KEYCLOAK_CLIENT_FRONTEND=hms-dashboard

# JWT
JWT_ISSUER=http://localhost:8080/realms/healthcare-monitoring
JWT_AUDIENCE=hms-backend

# Grafana
GRAFANA_ADMIN_USER=admin
GRAFANA_ADMIN_PASSWORD=change_this_password

# Backend
BACKEND_PORT=5000
FRONTEND_PORT=3001

Important rule:

Never commit the real .env file to GitHub.

Only commit .env.example.

11. Authentication and Authorization

Authentication means verifying who the user is.

Authorization means deciding what that user is allowed to do.

D4 should implement authentication using Keycloak.

12. Keycloak Setup

12.1 Realm

Create one Keycloak realm:

healthcare-monitoring

A realm is like a separate authentication space for this project.

12.2 Clients

Create clients for the services that need login.

Client	Purpose
`hms-backend`	Backend API token validation
`hms-dashboard`	Doctor or patient dashboard login
`hms-mobile-app`	Optional patient mobile app login

12.3 Roles

Create the following roles:

Role	Purpose
`PATIENT`	Can view only own health data
`DOCTOR`	Can view assigned patients and alerts
`ADMIN`	Can manage users and system settings

13. Role-Based Access Control

Feature	Patient	Doctor	Admin
View own vitals	Yes	No	Yes
View assigned patient vitals	No	Yes	Yes
View all system users	No	No	Yes
View alerts	Own only	Assigned patients	All
Manage users	No	No	Yes
View monitoring dashboard	No	Optional	Yes
Change system configuration	No	No	Yes

14. JWT Security Flow

The login and API access flow should work like this.

1. User opens dashboard
2. Dashboard redirects user to Keycloak login
3. User enters username and password
4. Keycloak returns an access token
5. Dashboard sends API requests with the access token
6. Backend validates the token
7. Backend checks the user role
8. Backend allows or blocks the request

Example API request:

GET /api/patients/P001/vitals
Authorization: Bearer <access_token>

Backend must reject requests when:

Token is missing
Token is expired
Token is invalid
User role is not allowed
User is trying to access another patient without permission

15. Suggested Protected API Routes

Route	Allowed Role
`GET /api/patients/me`	`PATIENT`
`GET /api/patients/{id}/vitals`	`DOCTOR`, `ADMIN`, assigned `PATIENT`
`GET /api/alerts`	`DOCTOR`, `ADMIN`
`POST /api/vitals`	Authorized device or backend service
`POST /api/admin/users`	`ADMIN`
`GET /api/metrics-summary`	`ADMIN`
`GET /health`	Public or internal only
`GET /metrics`	Prometheus only

16. Secure Data Handling

Healthcare systems handle sensitive data. This project may be a university project, but the system should still follow good security practices.

16.1 Sensitive Data Examples

patientId
patient name
age
deviceId
heart rate
temperature
SpO2 level
risk score
alert status
doctor notes
login details
access tokens

16.2 Rules for Handling Sensitive Data

Do not hardcode passwords
Do not commit .env files
Do not log passwords
Do not log full JWT tokens
Do not expose patient data to the wrong role
Validate all incoming data
Use HTTPS in production
Use secure MQTT settings if MQTT is used
Keep database credentials private

17. Data Validation Rules

D4 should help define validation rules with D1 and D2.

Example vital sign payload:

{
  "patientId": "P001",
  "deviceId": "DEV001",
  "heartRate": 96,
  "temperature": 37.4,
  "spo2": 98,
  "timestamp": "2026-05-01T10:30:00Z"
}

Suggested validation:

Field	Rule
`patientId`	Required, must match known patient
`deviceId`	Required, must match registered device
`heartRate`	Must be within realistic range
`temperature`	Must be within realistic range
`spo2`	Must be between 0 and 100
`timestamp`	Required, valid date-time format

Invalid data should be rejected before saving to the database.

18. MQTT or Device Data Security

If D1 uses MQTT, D4 should help secure it.

Recommended MQTT rules:

Disable anonymous publishing
Use username and password for devices
Use separate topics for each patient or device
Validate device ID in backend
Do not trust incoming device data blindly
Use TLS if possible

Example topics:

hms/devices/DEV001/vitals
hms/devices/DEV002/vitals
hms/patients/P001/alerts

19. Logging

Logging means recording important events so the team can debug problems.

19.1 Events to Log

The backend should log:

Server started
Database connected
User login success or failure
Unauthorized API access attempt
New vital signs received
Invalid data rejected
Anomaly detected
Alert generated
Alert sent to dashboard
API error
Database error

19.2 Good Logging Example

[INFO] Backend server started on port 5000
[INFO] Database connected successfully
[INFO] Vitals received for patientId=P001 deviceId=DEV001
[WARN] Invalid temperature rejected for patientId=P001
[WARN] Unauthorized access attempt on /api/admin/users
[ERROR] Database insert failed for vitals record

19.3 Bad Logging Example

[ERROR] Login failed for username=nimal password=123456
[INFO] JWT token = eyJhbGciOiJIUzI1NiIsInR5cCI...

Do not log passwords or full access tokens.

20. Prometheus Metrics

Prometheus collects system and application metrics.

The backend should expose a /metrics endpoint.

Example metrics:

http_requests_total
http_request_duration_seconds
backend_errors_total
vitals_received_total
invalid_vitals_total
alerts_generated_total
active_patients_total
anomalies_detected_total

20.1 Example Prometheus Configuration

Create prometheus/prometheus.yml.

global:
  scrape_interval: 15s

scrape_configs:
  - job_name: "hms-backend"
    static_configs:
      - targets: ["backend:5000"]

  - job_name: "prometheus"
    static_configs:
      - targets: ["localhost:9090"]

Update the target after the backend service name and port are finalized.

21. Health Checks

Each service should have a simple health check.

Recommended backend route:

GET /health

Example response:

{
  "status": "ok",
  "database": "connected",
  "timestamp": "2026-05-01T10:30:00Z"
}

Health checks help confirm whether the system is running correctly.

22. Grafana Dashboard

Grafana should be used to visualize metrics collected by Prometheus.

22.1 Recommended Dashboard Panels

System-level panels:

Backend status
API request count
API error count
API response time
Database connection status
CPU usage
Memory usage

Healthcare-specific panels:

Total vital signs received
Invalid data count
Active patients
Alerts generated
Anomalies detected
Device disconnection count

23. Alerts and Notifications

The actual medical alert logic belongs mostly to D2 and D3. However, D4 should support alert delivery, logging and security.

D4 responsibilities related to alerts:

Secure alert APIs
Log alert events
Ensure only authorized users can view alerts
Provide metrics for alert counts
Support dashboard real-time alert delivery if needed

Example alert data:

{
  "alertId": "A001",
  "patientId": "P001",
  "type": "HIGH_HEART_RATE",
  "severity": "HIGH",
  "message": "Heart rate is above the safe threshold",
  "timestamp": "2026-05-01T10:40:00Z"
}

24. Integration with D1

D1 handles device and edge systems.

D4 must coordinate with D1 to finalize:

Device ID format
Patient ID format
MQTT topic format
Vital signs data format
Device authentication method
Data validation rules
Test data generation method

Questions for D1:

1. What sensor values will be sent?
2. What is the exact JSON format?
3. Will data be sent through MQTT, HTTP or both?
4. How often will data be sent?
5. Will each device have a unique device ID?
6. How should invalid sensor readings be handled?

25. Integration with D2

D2 handles data intelligence and anomaly detection.

D4 must coordinate with D2 to finalize:

Database schema requirements
Anomaly detection service endpoint
Risk score format
Alert generation format
Metrics for anomaly detection
Backend integration method

Questions for D2:

1. What input data does the model need?
2. What output does the model produce?
3. Will anomaly detection run as a separate service?
4. Should D2 service expose an API?
5. What fields should be stored in PostgreSQL?
6. How should risk scores be represented?

26. Integration with D3

D3 handles dashboard and user interaction.

D4 must coordinate with D3 to finalize:

Login flow
Dashboard protected routes
API endpoints needed by frontend
User roles and permissions
Real-time alert method
Token handling in frontend

Questions for D3:

1. What pages require login?
2. What pages are for doctors?
3. What pages are for patients?
4. What pages are for admins?
5. Does the dashboard need real-time alerts?
6. How will the frontend store and send the access token?

27. Testing Plan

27.1 Authentication Testing

Test	Expected Result
Login as patient	Patient can access own data
Login as doctor	Doctor can access assigned patient data
Login as admin	Admin can access admin features
Call API without token	Request is rejected
Call API with invalid token	Request is rejected
Patient tries to access another patient	Request is rejected

27.2 Integration Testing

Test	Expected Result
Send sample vitals from D1	Backend receives data
Save vitals to PostgreSQL	Data appears in database
D2 analyzes vitals	Risk score or anomaly result is generated
Alert is generated	Alert appears in backend
D3 dashboard shows data	Doctor can view patient data
Prometheus collects metrics	Metrics appear in Prometheus
Grafana displays dashboard	Graphs update correctly

27.3 Deployment Testing

Test	Expected Result
Clone repository on new machine	Repo downloads correctly
Create `.env` file	Environment variables load correctly
Run `docker compose up`	Services start successfully
Open Keycloak	Login page works
Open Grafana	Dashboard works
Open Prometheus	Targets are visible
Stop services	Containers stop safely

28. Quick Start Guide

28.1 Clone the Repository

git clone https://github.com/Healthcare-Monitoring-System/d4-platform-devops.git
cd d4-platform-devops

28.2 Create Environment File

cp .env.example .env

Then edit .env and replace default passwords.

28.3 Start Services

docker compose up -d

28.4 Check Running Containers

docker ps

28.5 Stop Services

docker compose down

28.6 Reset Volumes

Use this only if you want to delete stored database and Grafana data.

docker compose down -v

29. Default Local Ports

Service	URL
Keycloak	`http://localhost:8080`
Prometheus	`http://localhost:9090`
Grafana	`http://localhost:3000`
PostgreSQL	`localhost:5432`
Backend API	`http://localhost:5000`
Frontend	`http://localhost:3001`

Ports may change depending on final backend and frontend setup.

30. Documentation Files to Add

D4 should add these documents inside the docs/ folder.

File	Purpose
`architecture.md`	Explain full system architecture
`authentication.md`	Explain Keycloak, roles and JWT flow
`deployment.md`	Explain Docker Compose setup
`monitoring.md`	Explain Prometheus and Grafana
`logging.md`	Explain logging rules
`security.md`	Explain secure data handling
`testing.md`	Explain final test cases

31. D4 ClickUp Task Breakdown

Section 1: System Architecture and Integration Planning

Owner: Person 1

Tasks:

Identify all services in the full system
Define data flow between D1, D2, D3 and D4
Create system architecture diagram
Define API and MQTT communication points
Define data ownership between groups
Confirm integration assumptions with all teams

Section 2: Authentication and Authorization

Owner: Person 1

Tasks:

Define user roles
Define role permissions
Set up Keycloak realm
Create Keycloak clients
Create test users
Configure role mapping
Add JWT validation plan
Test login for patient, doctor and admin
Document authentication flow

Section 3: Dockerization

Owner: Person 2

Tasks:

Create base docker-compose.yml
Add PostgreSQL container
Add Keycloak container
Add Prometheus container
Add Grafana container
Add backend container after backend is available
Add frontend container after dashboard is available
Add shared Docker network
Add persistent volumes
Test full startup

Section 4: Secure Data Handling

Owner: Person 2

Tasks:

Define sensitive data
Create .env.example
Add .env to .gitignore
Move secrets to environment variables
Define input validation rules
Define MQTT security rules
Define database security rules
Document secure handling practices

Section 5: Logging

Owner: Person 3

Tasks:

Define logging requirements
Define log levels
Add backend logging plan
Add authentication event logs
Add vital data event logs
Add error logs
Ensure sensitive data is not logged
Document logging examples

Section 6: Prometheus Metrics

Owner: Person 3 and Person 4

Tasks:

Add Prometheus to Docker Compose
Create prometheus.yml
Define backend /metrics endpoint requirements
Define metrics names
Track API requests
Track errors
Track vitals received
Track alerts generated
Test Prometheus target status

Section 7: Grafana Dashboard

Owner: Person 4

Tasks:

Add Grafana to Docker Compose
Connect Grafana to Prometheus
Create system monitoring dashboard
Create healthcare metrics dashboard
Add API request panel
Add error count panel
Add vitals count panel
Add alert count panel
Export dashboard JSON

Section 8: Alerts and Notifications Support

Owner: Person 5

Note: Medical alert logic is mainly D2 and D3. D4 only supports alert security, delivery, logging and monitoring.

Tasks:

Define alert data format with D2 and D3
Secure alert APIs
Add alert metrics
Add alert logs
Test alert visibility by role
Document alert integration flow

Section 9: Final Integration Testing

Owner: Person 5

Tasks:

Test D1 to backend data flow
Test backend to database flow
Test D2 anomaly detection flow
Test backend to D3 dashboard flow
Test Keycloak login
Test JWT protected APIs
Test Prometheus metrics
Test Grafana dashboard
Record final test results

Section 10: Documentation

Owner: Person 5

Tasks:

Write setup guide
Write deployment guide
Write authentication guide
Write monitoring guide
Write security guide
Write integration testing guide
Add screenshots where needed
Prepare final presentation points for D4

32. Final Demo Checklist

Before final submission, confirm these points.

[ ] System starts using docker compose up
[ ] PostgreSQL container runs correctly
[ ] Keycloak login works
[ ] Patient, doctor and admin roles exist
[ ] Backend rejects invalid JWT tokens
[ ] Backend protects role-based API routes
[ ] Environment variables are used for secrets
[ ] Logs show important system events
[ ] Sensitive data is not exposed in logs
[ ] Prometheus collects metrics
[ ] Grafana displays dashboard panels
[ ] D1 sample data reaches backend
[ ] D2 anomaly result is received
[ ] D3 dashboard can show patient data or alerts
[ ] Final documentation is complete

33. Common Problems and Fixes

Problem: Docker containers are not starting

Check logs:

docker compose logs

Check if ports are already used:

sudo lsof -i :8080
sudo lsof -i :3000
sudo lsof -i :5432

Problem: Keycloak page is not loading

Check whether the Keycloak container is running:

docker ps

Check Keycloak logs:

docker compose logs keycloak

Problem: Grafana cannot connect to Prometheus

Inside Docker Compose, Grafana should use the service name:

http://prometheus:9090

Not:

http://localhost:9090

Problem: Backend cannot connect to PostgreSQL

Inside Docker Compose, backend should connect using the service name:

postgres

Not:

localhost

Example database host:

DB_HOST=postgres

34. Git Workflow

Recommended workflow:

git pull origin main

git checkout -b feature/keycloak-setup

# Make changes

git add .
git commit -m "Add Keycloak setup documentation"
git push origin feature/keycloak-setup

Then create a pull request to merge into main.

35. Contribution Rules

Keep secrets out of GitHub
Use clear commit messages
Update documentation when configs change
Test Docker Compose before pushing
Use meaningful file names
Do not break other teams' integration points
Keep D1, D2 and D3 informed when changing ports, APIs or data formats

36. Final D4 Summary

D4 is the platform backbone of the Healthcare Monitoring System.

The final D4 result should prove that:

The system can run using Docker, authenticate users using Keycloak, secure APIs using JWT, protect sensitive patient data, log important events, collect metrics using Prometheus, display monitoring dashboards using Grafana and support end-to-end integration with D1, D2 and D3.

37. GHCR And Kubernetes Deployment

This repository now includes a deployable D4 Keycloak image and Kubernetes manifests.

Docker image: ghcr.io/healthcare-monitoring-system/d4-platform-devops:latest
Workflow: .github/workflows/docker-image.yml
Kubernetes base: infra/k8s/base
Deployment guide: docs/K3S_ARGOCD_DEPLOYMENT.md
Argo CD application: d2-data-intelligence/infra/argocd/d4-platform-devops-application.yaml
Live Argo CD source path: d2-data-intelligence/infra/k8s/d4-platform-devops

The Kubernetes service name is keycloak. Other pods in the d2 namespace can use:

http://keycloak:8080

For the droplet demo, Keycloak is exposed on NodePort 30080:

http://SERVER_IP:30080

38. Useful References

Docker documentation: https://docs.docker.com/
Docker Compose documentation: https://docs.docker.com/compose/
Keycloak documentation: https://www.keycloak.org/documentation
Prometheus documentation: https://prometheus.io/docs/introduction/overview/
Grafana documentation: https://grafana.com/docs/
JWT introduction: https://jwt.io/introduction

Name		Name	Last commit message	Last commit date
Latest commit History 44 Commits
.github/workflows		.github/workflows
development		development
grafana/dashboards		grafana/dashboards
infra/k8s/base		infra/k8s/base
.dockerignore		.dockerignore
.gitignore		.gitignore
Dockerfile		Dockerfile
EC2_K3S_OPERATIONS.md		EC2_K3S_OPERATIONS.md
README.md		README.md
final_test_results.md		final_test_results.md

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D4 Platform, Security and Integration

1. What D4 Is Responsible For

2. Team Responsibilities

3. D4 Main Deliverables

4. Recommended System Architecture

5. D4 Technology Stack

6. Expected Repository Structure

7. Services to Run

8. Dockerization Plan

8.1 Services to Dockerize

9. Example Docker Compose Structure

10. Environment Variables

11. Authentication and Authorization

12. Keycloak Setup

12.1 Realm

12.2 Clients

12.3 Roles

13. Role-Based Access Control

14. JWT Security Flow

15. Suggested Protected API Routes

16. Secure Data Handling

16.1 Sensitive Data Examples

16.2 Rules for Handling Sensitive Data

17. Data Validation Rules

18. MQTT or Device Data Security

19. Logging

19.1 Events to Log

19.2 Good Logging Example

19.3 Bad Logging Example

20. Prometheus Metrics

20.1 Example Prometheus Configuration

21. Health Checks

22. Grafana Dashboard

22.1 Recommended Dashboard Panels

23. Alerts and Notifications

24. Integration with D1

25. Integration with D2

26. Integration with D3

27. Testing Plan

27.1 Authentication Testing

27.2 Integration Testing

27.3 Deployment Testing

28. Quick Start Guide

28.1 Clone the Repository

28.2 Create Environment File

28.3 Start Services

28.4 Check Running Containers

28.5 Stop Services

28.6 Reset Volumes

29. Default Local Ports

30. Documentation Files to Add

31. D4 ClickUp Task Breakdown

Section 1: System Architecture and Integration Planning

Section 2: Authentication and Authorization

Section 3: Dockerization

Section 4: Secure Data Handling

Section 5: Logging

Section 6: Prometheus Metrics

Section 7: Grafana Dashboard

Section 8: Alerts and Notifications Support

Section 9: Final Integration Testing

Section 10: Documentation

32. Final Demo Checklist

33. Common Problems and Fixes

Problem: Docker containers are not starting

Problem: Keycloak page is not loading

Problem: Grafana cannot connect to Prometheus

Problem: Backend cannot connect to PostgreSQL

34. Git Workflow

35. Contribution Rules

36. Final D4 Summary

37. GHCR And Kubernetes Deployment

38. Useful References

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