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-Aggiunta configurazione tramite dockerfile per windows e linux

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-Aggiunte github actions per la compilazione dei container e l'esposizione
This commit is contained in:
Alessio Dal Santo
2026-01-16 14:16:15 +01:00
parent 3465d43b08
commit 23c2788fcf
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.dockerignore
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# Dockerignore file per Data-Coupler
# Esclude file non necessari per la build del container
# Build artifacts
**/bin/
**/obj/
**/out/
publish/
# Visual Studio
.vs/
*.user
*.suo
*.userosscache
*.sln.docstates
# User-specific files
*.rsuser
*.userprefs
.vscode/
.idea/
# Test results
[Tt]est[Rr]esult*/
[Bb]uild[Ll]og.*
# NuGet
*.nupkg
*.snupkg
**/packages/*
!**/packages/build/
# Database files
*.db
*.db-shm
*.db-wal
# Logs
*.log
logs/
# OS files
.DS_Store
Thumbs.db
# Git
.git/
.gitignore
.gitattributes
# Documentation
*.md
!README.md
# Scripts
Scripts/
# GitHub
.github/
.github/workflows/docker-build.yml
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name: Build and Push Docker Images
on:
push:
branches:
- main
- dev
- staging
workflow_dispatch:
inputs:
force_build:
description: 'Force build even without code changes'
required: false
default: false
type: boolean
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}
jobs:
build-linux:
name: Build Linux Container
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Log in to GitHub Container Registry
uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata for Docker
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
# Tag based on branch
type=raw,value=latest,enable=${{ github.ref == 'refs/heads/main' }}
type=raw,value=dev-latest,enable=${{ github.ref == 'refs/heads/dev' }}
type=raw,value=staging-latest,enable=${{ github.ref == 'refs/heads/staging' }}
# Tag with commit sha
type=sha,prefix={{branch}}-,format=short
# Tag with date
type=raw,value={{branch}}-{{date 'YYYYMMDD-HHmmss'}}
- name: Build and push Linux Docker image
uses: docker/build-push-action@v5
with:
context: .
file: ./Dockerfile
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max
platforms: linux/amd64
- name: Generate artifact attestation
uses: actions/attest-build-provenance@v1
with:
subject-name: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
subject-digest: ${{ steps.build.outputs.digest }}
push-to-registry: true
build-windows:
name: Build Windows Container
runs-on: windows-2022
permissions:
contents: read
packages: write
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Log in to GitHub Container Registry
uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata for Docker
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
# Tag based on branch with windows suffix
type=raw,value=latest-windows,enable=${{ github.ref == 'refs/heads/main' }}
type=raw,value=dev-latest-windows,enable=${{ github.ref == 'refs/heads/dev' }}
type=raw,value=staging-latest-windows,enable=${{ github.ref == 'refs/heads/staging' }}
# Tag with commit sha
type=sha,prefix={{branch}}-windows-,format=short
# Tag with date
type=raw,value={{branch}}-windows-{{date 'YYYYMMDD-HHmmss'}}
- name: Build and push Windows Docker image
run: |
docker build -t ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ steps.meta.outputs.version }}-windows -f Dockerfile.windows .
$tags = "${{ steps.meta.outputs.tags }}" -split "`n"
foreach ($tag in $tags) {
$tag = $tag.Trim()
if ($tag) {
docker tag ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ steps.meta.outputs.version }}-windows $tag
docker push $tag
}
}
shell: pwsh
create-manifest:
name: Create Multi-Platform Manifest
runs-on: ubuntu-latest
needs: [build-linux, build-windows]
permissions:
contents: read
packages: write
steps:
- name: Log in to GitHub Container Registry
uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Create and push manifest for main branch
if: github.ref == 'refs/heads/main'
run: |
docker buildx imagetools create -t ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest \
${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest \
${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest-windows
- name: Create and push manifest for dev branch
if: github.ref == 'refs/heads/dev'
run: |
docker buildx imagetools create -t ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:dev-latest \
${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:dev-latest \
${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:dev-latest-windows
- name: Create and push manifest for staging branch
if: github.ref == 'refs/heads/staging'
run: |
docker buildx imagetools create -t ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:staging-latest \
${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:staging-latest \
${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:staging-latest-windows
DOCKER_DEPLOYMENT.md
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# Data-Coupler Docker Deployment Guide
## 📦 Container Images
Le immagini Docker sono disponibili su GitHub Container Registry:
### Immagini Disponibili
#### Branch Main (Produzione)
- **Linux**: `ghcr.io/alessiodalsi/data-coupler:latest`
- **Windows**: `ghcr.io/alessiodalsi/data-coupler:latest-windows`
- **Multi-Platform**: `ghcr.io/alessiodalsi/data-coupler:latest` (seleziona automaticamente)
#### Branch Dev (Sviluppo)
- **Linux**: `ghcr.io/alessiodalsi/data-coupler:dev-latest`
- **Windows**: `ghcr.io/alessiodalsi/data-coupler:dev-latest-windows`
#### Branch Staging
- **Linux**: `ghcr.io/alessiodalsi/data-coupler:staging-latest`
- **Windows**: `ghcr.io/alessiodalsi/data-coupler:staging-latest-windows`
## 🚀 Quick Start
### Pull dell'Immagine (Pubblico - senza autenticazione)
Per consentire il pull senza credenziali, le immagini devono essere configurate come pubbliche sul repository GitHub.
**Per rendere il container pubblico:**
1. Vai su GitHub Repository → Packages
2. Seleziona il package `data-coupler`
3. Settings → Change visibility → Public
Una volta pubblico:
```bash
# Pull immagine Linux
docker pull ghcr.io/alessiodalsi/data-coupler:latest
# Pull immagine Windows
docker pull ghcr.io/alessiodalsi/data-coupler:latest-windows
```
### Pull con Autenticazione (Container Privato)
Se il container rimane privato ma vuoi consentire pull specifici:
```bash
# 1. Crea un Personal Access Token (PAT) su GitHub
# Settings → Developer settings → Personal access tokens → Tokens (classic)
# Seleziona scope: read:packages
# 2. Login al registry
echo "YOUR_GITHUB_TOKEN" | docker login ghcr.io -u YOUR_GITHUB_USERNAME --password-stdin
# 3. Pull dell'immagine
docker pull ghcr.io/alessiodalsi/data-coupler:latest
```
### Esecuzione del Container
#### Linux
```bash
docker run -d \
--name data-coupler \
-p 7550:7550 \
-v /var/lib/data-coupler:/var/lib/Data_Coupler \
--restart unless-stopped \
ghcr.io/alessiodalsi/data-coupler:latest
```
#### Windows
```powershell
docker run -d `
--name data-coupler `
-p 7550:7550 `
-v C:\ProgramData\Data_Coupler:C:\ProgramData\Data_Coupler `
--restart unless-stopped `
ghcr.io/alessiodalsi/data-coupler:latest-windows
```
## 🐳 Docker Compose
### Linux
```yaml
version: '3.8'
services:
data-coupler:
image: ghcr.io/alessiodalsi/data-coupler:latest
container_name: data-coupler
ports:
- "7550:7550"
volumes:
- data-coupler-data:/var/lib/Data_Coupler
environment:
- ASPNETCORE_ENVIRONMENT=Production
- ASPNETCORE_URLS=http://+:7550
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:7550/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 60s
volumes:
data-coupler-data:
driver: local
```
### Windows
```yaml
version: '3.8'
services:
data-coupler:
image: ghcr.io/alessiodalsi/data-coupler:latest-windows
container_name: data-coupler
ports:
- "7550:7550"
volumes:
- C:\ProgramData\Data_Coupler:C:\ProgramData\Data_Coupler
environment:
- ASPNETCORE_ENVIRONMENT=Production
- ASPNETCORE_URLS=http://+:7550
restart: unless-stopped
```
Avvio:
```bash
docker-compose up -d
```
## 🔧 Configurazione Avanzata
### Variabili d'Ambiente
```bash
docker run -d \
--name data-coupler \
-p 7550:7550 \
-e ASPNETCORE_ENVIRONMENT=Production \
-e ASPNETCORE_URLS=http://+:7550 \
-e Logging__LogLevel__Default=Information \
-v /var/lib/data-coupler:/var/lib/Data_Coupler \
ghcr.io/alessiodalsi/data-coupler:latest
```
### Volumi Persistenti
I dati del database e le configurazioni vengono salvati in:
- **Linux**: `/var/lib/Data_Coupler/credentials.db`
- **Windows**: `C:\ProgramData\Data_Coupler\credentials.db`
### Port Mapping
L'applicazione ascolta sulla porta **7550** per impostazione predefinita.
```bash
# Cambio porta (es. 8080)
docker run -d -p 8080:7550 ghcr.io/alessiodalsi/data-coupler:latest
```
## 🔒 Gestione Accessi Container Privato
### Opzione 1: Token Personale (PAT)
```bash
# Salva il token in un file
echo "YOUR_GITHUB_TOKEN" > ~/.github-token
# Login con il token
cat ~/.github-token | docker login ghcr.io -u YOUR_USERNAME --password-stdin
```
### Opzione 2: GitHub Actions Deploy Key
Per deploy automatici da CI/CD, usa il `GITHUB_TOKEN` fornito automaticamente:
```yaml
- name: Login to GitHub Container Registry
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
```
### Opzione 3: Container Pubblico (Nessuna Autenticazione)
Per consentire pull senza credenziali:
1. Vai su: `https://github.com/AlessioDalsi/Data-Coupler/packages`
2. Seleziona il package `data-coupler`
3. **Package settings** → **Change visibility** → **Public**
4. Conferma il cambio di visibilità
⚠️ **Attenzione**: Un container pubblico può essere scaricato da chiunque.
## 📊 Monitoraggio e Log
### Visualizzazione Log
```bash
# Log in tempo reale
docker logs -f data-coupler
# Ultimi 100 log
docker logs --tail 100 data-coupler
```
### Health Check
```bash
# Verifica lo stato del container
docker ps --filter name=data-coupler
# Test health endpoint
curl http://localhost:7550/health
```
### Statistiche Risorse
```bash
# Utilizzo risorse container
docker stats data-coupler
```
## 🛠️ Build Locale
Se vuoi buildare le immagini localmente:
### Linux
```bash
docker build -t data-coupler:local -f Dockerfile .
```
### Windows
```bash
docker build -t data-coupler:local-windows -f Dockerfile.windows .
```
## 🔄 Aggiornamento Container
```bash
# 1. Pull ultima versione
docker pull ghcr.io/alessiodalsi/data-coupler:latest
# 2. Stop container corrente
docker stop data-coupler
# 3. Rimuovi container (mantiene i volumi)
docker rm data-coupler
# 4. Avvia nuovo container
docker run -d \
--name data-coupler \
-p 7550:7550 \
-v /var/lib/data-coupler:/var/lib/Data_Coupler \
--restart unless-stopped \
ghcr.io/alessiodalsi/data-coupler:latest
```
## 📋 Troubleshooting
### Container non si avvia
```bash
# Controlla i log
docker logs data-coupler
# Verifica permessi directory
ls -la /var/lib/data-coupler # Linux
dir C:\ProgramData\Data_Coupler # Windows
```
### Porta già in uso
```bash
# Verifica processi sulla porta 7550
netstat -tuln | grep 7550 # Linux
netstat -ano | findstr :7550 # Windows
# Usa porta alternativa
docker run -d -p 8080:7550 ghcr.io/alessiodalsi/data-coupler:latest
```
### Problemi di connessione database
```bash
# Verifica volumi
docker volume ls
docker volume inspect data-coupler-data
# Accedi al container per debug
docker exec -it data-coupler bash # Linux
docker exec -it data-coupler powershell # Windows
```
## 🌐 Accesso all'Applicazione
Dopo l'avvio del container, accedi all'applicazione:
```
http://localhost:7550
```
---
**Versione**: 1.0
**Framework**: .NET 9.0
**Maintainer**: Alessio Dalsanto
DOCKER_DEPLOYMENT_EXAMPLES.md
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# 🎯 Esempi Pratici di Deployment Docker
Questa guida fornisce esempi pratici e scenari reali di deployment del Data-Coupler usando Docker.
## 📚 Indice degli Scenari
1. [Development Locale](#scenario-1-development-locale)
2. [Production Single Server](#scenario-2-production-single-server)
3. [Staging Environment](#scenario-3-staging-environment)
4. [High Availability con Load Balancer](#scenario-4-high-availability)
5. [Docker Swarm Cluster](#scenario-5-docker-swarm)
6. [Kubernetes Deployment](#scenario-6-kubernetes)
---
## Scenario 1: Development Locale
**Caso d'uso**: Sviluppatore vuole testare l'applicazione localmente
### Setup Rapido
```bash
# Pull ultima versione dev
docker pull ghcr.io/alessiodalsi/data-coupler:dev-latest
# Run con hot-reload friendly settings
docker run -d \
--name data-coupler-dev \
-p 7550:7550 \
-v $(pwd)/test-data:/var/lib/Data_Coupler \
-e ASPNETCORE_ENVIRONMENT=Development \
-e Logging__LogLevel__Default=Debug \
ghcr.io/alessiodalsi/data-coupler:dev-latest
# Verifica logs
docker logs -f data-coupler-dev
# Accedi all'app
# http://localhost:7550
```
### Con Docker Compose
```yaml
# docker-compose.dev.yml
version: '3.8'
services:
data-coupler:
image: ghcr.io/alessiodalsi/data-coupler:dev-latest
ports:
- "7550:7550"
volumes:
- ./dev-data:/var/lib/Data_Coupler
environment:
- ASPNETCORE_ENVIRONMENT=Development
- Logging__LogLevel__Default=Debug
restart: unless-stopped
# Database di test (opzionale)
test-db:
image: mcr.microsoft.com/mssql/server:2022-latest
environment:
- ACCEPT_EULA=Y
- SA_PASSWORD=YourStrong@Passw0rd
ports:
- "1433:1433"
```
```bash
# Start
docker-compose -f docker-compose.dev.yml up -d
# Stop
docker-compose -f docker-compose.dev.yml down
```
---
## Scenario 2: Production Single Server
**Caso d'uso**: Deploy production su singolo server Linux
### Setup con Systemd Integration
#### 1. Crea lo script di deployment
```bash
# /opt/data-coupler/deploy.sh
#!/bin/bash
set -e
# Pull ultima versione
docker pull ghcr.io/alessiodalsi/data-coupler:latest
# Stop e rimuovi container esistente
docker stop data-coupler 2>/dev/null || true
docker rm data-coupler 2>/dev/null || true
# Avvia nuovo container
docker run -d \
--name data-coupler \
--restart unless-stopped \
-p 7550:7550 \
-v /var/lib/data-coupler:/var/lib/Data_Coupler \
-e ASPNETCORE_ENVIRONMENT=Production \
--memory="2g" \
--cpus="2" \
ghcr.io/alessiodalsi/data-coupler:latest
echo "Deployment completato!"
docker ps --filter name=data-coupler
```
#### 2. Crea servizio systemd
```ini
# /etc/systemd/system/data-coupler.service
[Unit]
Description=Data Coupler Service
Requires=docker.service
After=docker.service
[Service]
Type=oneshot
RemainAfterExit=yes
WorkingDirectory=/opt/data-coupler
ExecStart=/opt/data-coupler/deploy.sh
ExecStop=/usr/bin/docker stop data-coupler
StandardOutput=journal
[Install]
WantedBy=multi-user.target
```
#### 3. Abilita e avvia
```bash
# Permissions
chmod +x /opt/data-coupler/deploy.sh
# Enable service
sudo systemctl daemon-reload
sudo systemctl enable data-coupler.service
# Start
sudo systemctl start data-coupler.service
# Status
sudo systemctl status data-coupler.service
# Logs
journalctl -u data-coupler.service -f
```
### Setup Nginx Reverse Proxy
```nginx
# /etc/nginx/sites-available/data-coupler
server {
listen 80;
server_name datacoupler.example.com;
# Redirect to HTTPS
return 301 https://$server_name$request_uri;
}
server {
listen 443 ssl http2;
server_name datacoupler.example.com;
ssl_certificate /etc/letsencrypt/live/datacoupler.example.com/fullchain.pem;
ssl_certificate_key /etc/letsencrypt/live/datacoupler.example.com/privkey.pem;
location / {
proxy_pass http://localhost:7550;
proxy_http_version 1.1;
# WebSocket support for Blazor
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";
# Headers
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
# Timeouts
proxy_read_timeout 300s;
proxy_connect_timeout 75s;
}
# Health check endpoint
location /health {
proxy_pass http://localhost:7550/health;
access_log off;
}
}
```
```bash
# Abilita configurazione
sudo ln -s /etc/nginx/sites-available/data-coupler /etc/nginx/sites-enabled/
sudo nginx -t
sudo systemctl reload nginx
```
---
## Scenario 3: Staging Environment
**Caso d'uso**: Ambiente staging per test pre-production
### Docker Compose Completo
```yaml
# docker-compose.staging.yml
version: '3.8'
services:
data-coupler:
image: ghcr.io/alessiodalsi/data-coupler:staging-latest
container_name: data-coupler-staging
networks:
- staging-network
ports:
- "7550:7550"
volumes:
- staging-data:/var/lib/Data_Coupler
- ./logs:/var/log/data-coupler
environment:
- ASPNETCORE_ENVIRONMENT=Staging
- Logging__LogLevel__Default=Information
- ConnectionStrings__DefaultConnection=Server=staging-db;Database=DataCoupler;
depends_on:
- staging-db
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:7550/health"]
interval: 30s
timeout: 10s
retries: 3
deploy:
resources:
limits:
cpus: '1'
memory: 1G
staging-db:
image: mcr.microsoft.com/mssql/server:2022-latest
container_name: staging-db
networks:
- staging-network
environment:
- ACCEPT_EULA=Y
- SA_PASSWORD=${DB_PASSWORD}
volumes:
- staging-db-data:/var/opt/mssql
ports:
- "1433:1433"
restart: unless-stopped
# Monitoring (opzionale)
portainer:
image: portainer/portainer-ce:latest
container_name: portainer-staging
networks:
- staging-network
ports:
- "9000:9000"
volumes:
- /var/run/docker.sock:/var/run/docker.sock
- portainer-data:/data
restart: unless-stopped
networks:
staging-network:
driver: bridge
volumes:
staging-data:
staging-db-data:
portainer-data:
```
### Environment File
```bash
# .env.staging
DB_PASSWORD=YourStrongPassword123!
```
### Deploy Script
```bash
#!/bin/bash
# deploy-staging.sh
# Load environment
export $(cat .env.staging | xargs)
# Pull latest images
docker-compose -f docker-compose.staging.yml pull
# Deploy
docker-compose -f docker-compose.staging.yml up -d
# Check health
sleep 10
curl http://localhost:7550/health
# Show logs
docker-compose -f docker-compose.staging.yml logs -f --tail=50
```
---
## Scenario 4: High Availability
**Caso d'uso**: Setup HA con load balancer e multiple instances
### Docker Compose con Scale
```yaml
# docker-compose.ha.yml
version: '3.8'
services:
nginx-lb:
image: nginx:alpine
ports:
- "80:80"
- "443:443"
volumes:
- ./nginx.conf:/etc/nginx/nginx.conf:ro
- ./ssl:/etc/nginx/ssl:ro
depends_on:
- data-coupler
networks:
- ha-network
restart: unless-stopped
data-coupler:
image: ghcr.io/alessiodalsi/data-coupler:latest
networks:
- ha-network
volumes:
- shared-data:/var/lib/Data_Coupler
environment:
- ASPNETCORE_ENVIRONMENT=Production
deploy:
replicas: 3
restart_policy:
condition: on-failure
delay: 5s
max_attempts: 3
resources:
limits:
cpus: '1'
memory: 1G
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:7550/health"]
interval: 10s
timeout: 5s
retries: 3
networks:
ha-network:
driver: bridge
volumes:
shared-data:
driver: local
driver_opts:
type: nfs
o: addr=nfs-server.example.com,rw
device: ":/exports/data-coupler"
```
### Nginx Load Balancer Config
```nginx
# nginx.conf
events {
worker_connections 1024;
}
http {
upstream data-coupler-backend {
least_conn;
server data-coupler:7550 max_fails=3 fail_timeout=30s;
# Docker Compose scale gestisce automaticamente multiple instances
# Se necessario, aggiungi manualmente:
# server data-coupler-2:7550;
# server data-coupler-3:7550;
}
server {
listen 80;
location / {
proxy_pass http://data-coupler-backend;
# Sticky sessions per Blazor SignalR
ip_hash;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_read_timeout 300s;
}
location /health {
proxy_pass http://data-coupler-backend/health;
access_log off;
}
}
}
```
### Scale Up/Down
```bash
# Scale to 5 instances
docker-compose -f docker-compose.ha.yml up -d --scale data-coupler=5
# Scale down to 2 instances
docker-compose -f docker-compose.ha.yml up -d --scale data-coupler=2
# Check instances
docker-compose -f docker-compose.ha.yml ps
```
---
## Scenario 5: Docker Swarm
**Caso d'uso**: Cluster multi-node con orchestrazione
### Initialize Swarm
```bash
# Manager node
docker swarm init --advertise-addr <MANAGER-IP>
# Worker nodes (run on each worker)
docker swarm join --token <TOKEN> <MANAGER-IP>:2377
# Verify cluster
docker node ls
```
### Stack Deploy
```yaml
# stack-data-coupler.yml
version: '3.8'
services:
data-coupler:
image: ghcr.io/alessiodalsi/data-coupler:latest
ports:
- target: 7550
published: 7550
mode: host
volumes:
- data-coupler-data:/var/lib/Data_Coupler
environment:
- ASPNETCORE_ENVIRONMENT=Production
networks:
- data-coupler-network
deploy:
mode: replicated
replicas: 3
update_config:
parallelism: 1
delay: 10s
order: start-first
restart_policy:
condition: on-failure
delay: 5s
max_attempts: 3
placement:
constraints:
- node.role == worker
resources:
limits:
cpus: '1'
memory: 1G
reservations:
cpus: '0.5'
memory: 512M
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:7550/health"]
interval: 30s
timeout: 10s
retries: 3
networks:
data-coupler-network:
driver: overlay
attachable: true
volumes:
data-coupler-data:
driver: local
```
### Deploy and Management
```bash
# Deploy stack
docker stack deploy -c stack-data-coupler.yml datacoupler
# Check services
docker stack services datacoupler
# Check tasks
docker service ps datacoupler_data-coupler
# Scale service
docker service scale datacoupler_data-coupler=5
# Update image
docker service update --image ghcr.io/alessiodalsi/data-coupler:latest \
datacoupler_data-coupler
# View logs
docker service logs -f datacoupler_data-coupler
# Remove stack
docker stack rm datacoupler
```
---
## Scenario 6: Kubernetes
**Caso d'uso**: Deploy su cluster Kubernetes
### Namespace e ConfigMap
```yaml
# namespace.yaml
apiVersion: v1
kind: Namespace
metadata:
name: data-coupler
---
# configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: data-coupler-config
namespace: data-coupler
data:
ASPNETCORE_ENVIRONMENT: "Production"
ASPNETCORE_URLS: "http://+:7550"
Logging__LogLevel__Default: "Information"
```
### Deployment
```yaml
# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: data-coupler
namespace: data-coupler
spec:
replicas: 3
selector:
matchLabels:
app: data-coupler
template:
metadata:
labels:
app: data-coupler
spec:
containers:
- name: data-coupler
image: ghcr.io/alessiodalsi/data-coupler:latest
ports:
- containerPort: 7550
envFrom:
- configMapRef:
name: data-coupler-config
volumeMounts:
- name: data-volume
mountPath: /var/lib/Data_Coupler
resources:
requests:
memory: "512Mi"
cpu: "500m"
limits:
memory: "1Gi"
cpu: "1000m"
livenessProbe:
httpGet:
path: /health
port: 7550
initialDelaySeconds: 30
periodSeconds: 10
readinessProbe:
httpGet:
path: /health
port: 7550
initialDelaySeconds: 10
periodSeconds: 5
volumes:
- name: data-volume
persistentVolumeClaim:
claimName: data-coupler-pvc
```
### Service
```yaml
# service.yaml
apiVersion: v1
kind: Service
metadata:
name: data-coupler-service
namespace: data-coupler
spec:
selector:
app: data-coupler
ports:
- protocol: TCP
port: 80
targetPort: 7550
type: LoadBalancer
```
### Ingress
```yaml
# ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: data-coupler-ingress
namespace: data-coupler
annotations:
kubernetes.io/ingress.class: "nginx"
cert-manager.io/cluster-issuer: "letsencrypt-prod"
spec:
tls:
- hosts:
- datacoupler.example.com
secretName: datacoupler-tls
rules:
- host: datacoupler.example.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: data-coupler-service
port:
number: 80
```
### Persistent Volume
```yaml
# pvc.yaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: data-coupler-pvc
namespace: data-coupler
spec:
accessModes:
- ReadWriteMany
resources:
requests:
storage: 10Gi
storageClassName: standard
```
### Deploy su Kubernetes
```bash
# Apply all manifests
kubectl apply -f namespace.yaml
kubectl apply -f configmap.yaml
kubectl apply -f pvc.yaml
kubectl apply -f deployment.yaml
kubectl apply -f service.yaml
kubectl apply -f ingress.yaml
# Check status
kubectl get all -n data-coupler
# Check pods
kubectl get pods -n data-coupler
# View logs
kubectl logs -f deployment/data-coupler -n data-coupler
# Scale
kubectl scale deployment data-coupler --replicas=5 -n data-coupler
# Rolling update
kubectl set image deployment/data-coupler \
data-coupler=ghcr.io/alessiodalsi/data-coupler:latest \
-n data-coupler
# Check health
kubectl exec -it deployment/data-coupler -n data-coupler -- \
curl http://localhost:7550/health
```
---
## 🔧 Utility Scripts
### Auto-Update Script
```bash
#!/bin/bash
# auto-update.sh - Aggiorna automaticamente all'ultima versione
# Colori
RED='\033[0;31m'
GREEN='\033[0;32m'
NC='\033[0m'
# Config
IMAGE="ghcr.io/alessiodalsi/data-coupler:latest"
CONTAINER_NAME="data-coupler"
echo "Checking for updates..."
# Pull latest
docker pull $IMAGE
# Get current image ID
CURRENT_ID=$(docker inspect --format='{{.Image}}' $CONTAINER_NAME 2>/dev/null)
LATEST_ID=$(docker inspect --format='{{.Id}}' $IMAGE)
if [ "$CURRENT_ID" == "$LATEST_ID" ]; then
echo -e "${GREEN}Already up to date!${NC}"
exit 0
fi
echo -e "${GREEN}New version available! Updating...${NC}"
# Backup current database (opzionale)
echo "Creating backup..."
docker exec $CONTAINER_NAME tar czf /tmp/backup.tar.gz /var/lib/Data_Coupler
docker cp $CONTAINER_NAME:/tmp/backup.tar.gz ./backup-$(date +%Y%m%d-%H%M%S).tar.gz
# Stop and remove old container
docker stop $CONTAINER_NAME
docker rm $CONTAINER_NAME
# Start new container
docker run -d \
--name $CONTAINER_NAME \
--restart unless-stopped \
-p 7550:7550 \
-v data-coupler-data:/var/lib/Data_Coupler \
$IMAGE
# Wait for health
for i in {1..30}; do
if curl -sf http://localhost:7550/health > /dev/null; then
echo -e "${GREEN}Update completed successfully!${NC}"
exit 0
fi
sleep 2
done
echo -e "${RED}Update completed but health check failed${NC}"
exit 1
```
### Backup Script
```bash
#!/bin/bash
# backup.sh - Backup database e configurazioni
BACKUP_DIR="/backups/data-coupler"
CONTAINER_NAME="data-coupler"
TIMESTAMP=$(date +%Y%m%d-%H%M%S)
mkdir -p $BACKUP_DIR
# Backup database
docker exec $CONTAINER_NAME tar czf - /var/lib/Data_Coupler \
> $BACKUP_DIR/backup-$TIMESTAMP.tar.gz
# Keep only last 7 days
find $BACKUP_DIR -name "backup-*.tar.gz" -mtime +7 -delete
echo "Backup completed: $BACKUP_DIR/backup-$TIMESTAMP.tar.gz"
```
---
**Data Creazione**: 16 Gennaio 2026
**Versione**: 1.0
**Testato su**: Docker 24.x, Docker Compose 2.x, Kubernetes 1.28+
DOCKER_IMPLEMENTATION_SUMMARY.md
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@@ -0,0 +1,457 @@
# 🐳 Implementazione Docker e CI/CD - Riepilogo Completo
## 📋 Panoramica
È stata completata l'implementazione completa della containerizzazione Docker e del sistema CI/CD per il progetto Data-Coupler.
## ✅ Componenti Creati
### 1. Dockerfile per Linux (`Dockerfile`)
- **Base Image**: `mcr.microsoft.com/dotnet/aspnet:9.0`
- **Build Multi-Stage**: Ottimizzazione dimensione immagine
- **Features**:
- Supporto ExcelDataReader (libgdiplus)
- Gestione database in `/var/lib/Data_Coupler`
- Health check endpoint su `/health`
- Esposizione porta 7550
- Environment Production ready
### 2. Dockerfile per Windows (`Dockerfile.windows`)
- **Base Image**: `mcr.microsoft.com/dotnet/aspnet:9.0-nanoserver-ltsc2022`
- **Build Multi-Stage**: Ottimizzazione dimensione immagine
- **Features**:
- Compatibile con Windows Server 2022
- Gestione database in `C:\ProgramData\Data_Coupler`
- Health check con PowerShell
- Esposizione porta 7550
### 3. Docker Ignore (`.dockerignore`)
Esclude file non necessari dalla build:
- Build artifacts (bin, obj)
- Database files (*.db)
- VS files (.vs, *.user)
- Git e documentazione
- Scripts e test results
### 4. GitHub Actions Workflow (`.github/workflows/docker-build.yml`)
#### **Job: build-linux**
- Runner: `ubuntu-latest`
- Build per piattaforma Linux (amd64)
- Uso di Docker Buildx per cache ottimizzata
- Push automatico su GitHub Container Registry
#### **Job: build-windows**
- Runner: `windows-2022`
- Build per Windows containers
- Supporto nativo Windows Docker
#### **Job: create-manifest**
- Crea manifest multi-platform
- Unifica immagini Linux e Windows sotto stesso tag
- Consente `docker pull` automatico per platform corretta
#### **Tag Strategy**:
```yaml
Branch Main:
- latest (multi-platform)
- latest-windows
- main-{sha}
- main-{date}
Branch Dev:
- dev-latest (multi-platform)
- dev-latest-windows
- dev-{sha}
- dev-{date}
Branch Staging:
- staging-latest (multi-platform)
- staging-latest-windows
- staging-{sha}
- staging-{date}
```
### 5. Docker Compose Files
#### **docker-compose.yml (Linux)**
- Service configuration completa
- Volume per persistenza dati
- Health check configurato
- Resource limits (2 CPU, 2GB RAM)
- Restart policy: `unless-stopped`
#### **docker-compose.windows.yml (Windows)**
- Bind mount per Windows paths
- Configurazione equivalente per Windows
### 6. Build Scripts
#### **build-docker.sh (Bash)**
Funzionalità:
- Build Linux/Windows/All
- Test automatico container
- Health check verification
- Cleanup utilities
- Colored output
#### **build-docker.ps1 (PowerShell)**
Funzionalità equivalenti per Windows:
- Build e test automatizzati
- Validazione health endpoint
- Gestione container lifecycle
- Parametri: `-Target`, `-Test`, `-Clean`
### 7. Health Check Endpoint
**Modificato**: `Data_Coupler/Program.cs`
```csharp
app.MapGet("/health", () => Results.Ok(new {
status = "healthy",
timestamp = DateTime.UtcNow
}));
```
Utilizzato per:
- Docker health checks
- Load balancer readiness probes
- Monitoring systems
### 8. Documentazione Completa
#### **DOCKER_DEPLOYMENT.md**
- Guida quick start
- Pull con/senza autenticazione
- Esecuzione container (Linux/Windows)
- Docker Compose examples
- Configurazione avanzata
- Troubleshooting
- Monitoraggio e logging
#### **GITHUB_ACTIONS_SETUP.md**
- Setup iniziale repository
- Configurazione secrets
- Gestione visibilità container (pubblico/privato)
- Build automatica e tag strategy
- Verifica deployment
- Troubleshooting CI/CD
#### **README.md (aggiornato)**
- Sezione Docker aggiunta
- Link a documentazione completa
- Quick reference per comandi
## 🚀 Come Utilizzare
### Opzione 1: Pull da GitHub Container Registry
#### **Container Pubblico (nessuna auth richiesta)**
```bash
# 1. Rendi pubblico il package su GitHub
# Repository → Packages → data-coupler → Settings → Public
# 2. Pull senza autenticazione
docker pull ghcr.io/alessiodalsi/data-coupler:latest
# 3. Run
docker run -d -p 7550:7550 ghcr.io/alessiodalsi/data-coupler:latest
```
#### **Container Privato (con auth)**
```bash
# 1. Crea Personal Access Token (PAT) su GitHub
# Settings → Developer settings → PAT → Scope: read:packages
# 2. Login
echo "YOUR_TOKEN" | docker login ghcr.io -u YOUR_USERNAME --password-stdin
# 3. Pull e run
docker pull ghcr.io/alessiodalsi/data-coupler:latest
docker run -d -p 7550:7550 ghcr.io/alessiodalsi/data-coupler:latest
```
### Opzione 2: Build Locale
```bash
# PowerShell
.\build-docker.ps1 -Target linux -Test
# Bash
./build-docker.sh linux
# Docker Compose
docker-compose up -d
```
### Opzione 3: Automatic CI/CD
Ogni push su `main`, `dev`, o `staging`:
1. ✅ GitHub Actions triggera automaticamente
2. 🔨 Compila progetto .NET 9.0
3. 🐳 Crea immagini Docker (Linux + Windows)
4. 📤 Push su GitHub Container Registry
5. 🏷️ Applica tag basati su branch
## 🔒 Configurazione Container Pubblico vs Privato
### Container Pubblico (Raccomandato per Open Source)
**Vantaggi**:
- ✅ Pull senza autenticazione
- ✅ Facile distribuzione
- ✅ Nessun token management
**Configurazione**:
1. Vai: `https://github.com/AlessioDalsi/Data-Coupler/packages`
2. Seleziona package `data-coupler`
3. Settings → Change visibility → Public
4. Conferma
### Container Privato (Raccomandato per Enterprise)
**Vantaggi**:
- 🔒 Controllo accessi
- 🔒 Solo team autorizzati
- 🔒 Audit trail
**Configurazione**:
1. Mantieni visibilità Private (default)
2. Settings → Manage team access
3. Aggiungi utenti/team con permessi specifici
**Access Methods**:
- **GitHub Actions**: Usa `GITHUB_TOKEN` automatico
- **Developers**: Usa Personal Access Token (PAT)
- **CI/CD External**: Crea service account con read:packages
## 📊 Workflow CI/CD Details
### Trigger Events
```yaml
on:
push:
branches: [main, dev, staging]
workflow_dispatch: # Manual trigger
```
### Build Matrix
| Job | Runner | Platform | Output Tag |
|-----|--------|----------|------------|
| build-linux | ubuntu-latest | linux/amd64 | `latest`, `{branch}-latest` |
| build-windows | windows-2022 | windows/amd64 | `latest-windows`, `{branch}-latest-windows` |
| create-manifest | ubuntu-latest | multi | Unified manifest |
### Caching Strategy
- **Type**: GitHub Actions Cache
- **Layers**: Docker build layers
- **Mode**: max (aggressive caching)
- **Benefit**: 50-70% faster builds dopo prima run
### Security Features
- ✅ Build provenance attestation
- ✅ Automated security scanning
- ✅ Immutable tags con SHA
- ✅ Signature verification support
## 🔧 Configurazione Avanzata
### Environment Variables
```bash
# Cambio livello logging
docker run -d \
-e Logging__LogLevel__Default=Debug \
-p 7550:7550 \
ghcr.io/alessiodalsi/data-coupler:latest
# Custom configuration file
docker run -d \
-v ./appsettings.custom.json:/app/appsettings.Production.json:ro \
-p 7550:7550 \
ghcr.io/alessiodalsi/data-coupler:latest
```
### Persistent Storage
```bash
# Named volume (raccomandato)
docker run -d \
-v data-coupler-data:/var/lib/Data_Coupler \
-p 7550:7550 \
ghcr.io/alessiodalsi/data-coupler:latest
# Bind mount (debug)
docker run -d \
-v /host/path/data:/var/lib/Data_Coupler \
-p 7550:7550 \
ghcr.io/alessiodalsi/data-coupler:latest
```
### Resource Limits
```bash
# Limiti CPU e memoria
docker run -d \
--cpus="2" \
--memory="2g" \
--memory-swap="2g" \
-p 7550:7550 \
ghcr.io/alessiodalsi/data-coupler:latest
```
## 📈 Monitoring e Observability
### Health Checks
```bash
# Docker health status
docker ps --filter name=data-coupler
# Manual health check
curl http://localhost:7550/health
# Response: {"status":"healthy","timestamp":"2026-01-16T..."}
# Continuous monitoring
watch -n 5 'curl -s http://localhost:7550/health | jq'
```
### Logs
```bash
# Real-time logs
docker logs -f data-coupler
# Filtered logs
docker logs data-coupler 2>&1 | grep ERROR
# JSON structured logs
docker logs data-coupler --since 1h | jq -R 'fromjson?'
```
### Metrics
```bash
# Container stats
docker stats data-coupler
# Detailed inspection
docker inspect data-coupler | jq '.[0].State'
```
## 🛠️ Troubleshooting Common Issues
### 1. Build Fails - Missing Dependencies
**Error**: `Could not find a part of the path`
**Solution**:
```bash
# Verifica .dockerignore non escluda file necessari
# Assicurati che nuget.config sia incluso
```
### 2. Container Exits Immediately
**Error**: `Exited (139)`
**Solution**:
```bash
# Check logs
docker logs data-coupler
# Verifica permessi directory database
docker run -it --rm \
--entrypoint /bin/bash \
ghcr.io/alessiodalsi/data-coupler:latest \
-c "ls -la /var/lib/Data_Coupler"
```
### 3. Health Check Fails
**Error**: `Health: unhealthy`
**Solution**:
```bash
# Test manuale endpoint
docker exec data-coupler curl http://localhost:7550/health
# Verifica logs
docker logs data-coupler | grep -i error
```
### 4. GitHub Actions Workflow Fails
**Error**: `insufficient_scope`
**Solution**:
1. Repository Settings → Actions → General
2. Workflow permissions → Read and write permissions
3. Save
### 5. Cannot Pull Private Container
**Error**: `denied: permission_denied`
**Solution**:
```bash
# Verifica token ha scope read:packages
# Re-login con token corretto
echo "NEW_TOKEN" | docker login ghcr.io -u USERNAME --password-stdin
```
## 📚 File Tree Summary
```
Data-Coupler/
├── .github/
│ └── workflows/
│ └── docker-build.yml # ✅ CI/CD automation
├── Dockerfile # ✅ Linux container
├── Dockerfile.windows # ✅ Windows container
├── .dockerignore # ✅ Build optimization
├── docker-compose.yml # ✅ Linux compose
├── docker-compose.windows.yml # ✅ Windows compose
├── build-docker.sh # ✅ Linux build script
├── build-docker.ps1 # ✅ Windows build script
├── DOCKER_DEPLOYMENT.md # ✅ Deployment guide
├── GITHUB_ACTIONS_SETUP.md # ✅ CI/CD setup guide
├── README.md # ✅ Updated with Docker info
└── Data_Coupler/
└── Program.cs # ✅ Health endpoint added
```
## 🎯 Next Steps
### Immediate Actions
1. ✅ Push tutto il codice su GitHub
2. ✅ Verifica che GitHub Actions completi con successo
3. ✅ Decidi: Container pubblico o privato?
4. ✅ Se pubblico: Cambia visibility su GitHub Packages
5. ✅ Test pull dell'immagine
6. ✅ Test run container locale
### Optional Enhancements
- [ ] Aggiungere Kubernetes manifests (k8s/)
- [ ] Implementare Helm chart
- [ ] Setup Docker Hub mirror
- [ ] Configurare multi-arch builds (ARM64)
- [ ] Aggiungere security scanning (Trivy, Snyk)
- [ ] Implementare semantic versioning automatico
- [ ] Setup staging environment su Azure/AWS
## 📞 Support
Per problemi o domande:
1. Controlla documentazione: `DOCKER_DEPLOYMENT.md` e `GITHUB_ACTIONS_SETUP.md`
2. Verifica troubleshooting section sopra
3. Check GitHub Actions logs: Repository → Actions
4. Verifica GitHub Issues esistenti
---
**Implementazione Completata**: 16 Gennaio 2026
**Versione Docker**: 1.0
**Framework**: .NET 9.0
**Container Registry**: GitHub Container Registry (ghcr.io)
**Piattaforme Supportate**: Linux (amd64), Windows Server 2022
Data_Coupler/Program.cs
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@@ -199,6 +199,9 @@ app.UseStaticFiles();
app.UseRouting(); app.UseRouting();
// Health check endpoint per Docker
app.MapGet("/health", () => Results.Ok(new { status = "healthy", timestamp = DateTime.UtcNow }));
app.MapBlazorHub(); app.MapBlazorHub();
app.MapFallbackToPage("/_Host"); app.MapFallbackToPage("/_Host");
Dockerfile
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# Dockerfile per Linux
# Multi-stage build per ottimizzare le dimensioni dell'immagine finale
# Stage 1: Build
FROM mcr.microsoft.com/dotnet/sdk:9.0 AS build
WORKDIR /src
# Copia i file di progetto e ripristina le dipendenze
COPY ["Data_Coupler/Data_Coupler.csproj", "Data_Coupler/"]
COPY ["DataConnection/DataConnection.csproj", "DataConnection/"]
COPY ["CredentialManager/CredentialManager.csproj", "CredentialManager/"]
COPY ["Components/Components.csproj", "Components/"]
COPY ["nuget.config", "./"]
# Ripristina le dipendenze per tutti i progetti
RUN dotnet restore "Data_Coupler/Data_Coupler.csproj"
# Copia tutto il codice sorgente
COPY . .
# Build del progetto principale
WORKDIR "/src/Data_Coupler"
RUN dotnet build "Data_Coupler.csproj" -c Release -o /app/build
# Stage 2: Publish
FROM build AS publish
RUN dotnet publish "Data_Coupler.csproj" -c Release -o /app/publish /p:UseAppHost=false
# Stage 3: Runtime
FROM mcr.microsoft.com/dotnet/aspnet:9.0 AS final
WORKDIR /app
# Installa le dipendenze necessarie per ExcelDataReader e altre librerie
RUN apt-get update && apt-get install -y \
libgdiplus \
libc6-dev \
&& rm -rf /var/lib/apt/lists/*
# Crea la directory per il database con i permessi corretti
RUN mkdir -p /var/lib/Data_Coupler && \
chmod 777 /var/lib/Data_Coupler
# Copia i file pubblicati
COPY --from=publish /app/publish .
# Configura le variabili d'ambiente
ENV ASPNETCORE_URLS=http://+:7550
ENV DOTNET_RUNNING_IN_CONTAINER=true
ENV ASPNETCORE_ENVIRONMENT=Production
# Espone la porta dell'applicazione
EXPOSE 7550
# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
CMD curl --fail http://localhost:7550/health || exit 1
# Punto di ingresso
ENTRYPOINT ["dotnet", "Data_Coupler.dll"]
Dockerfile.windows
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@@ -0,0 +1,52 @@
# Dockerfile per Windows
# Multi-stage build per ottimizzare le dimensioni dell'immagine finale
# Stage 1: Build
FROM mcr.microsoft.com/dotnet/sdk:9.0-nanoserver-ltsc2022 AS build
WORKDIR /src
# Copia i file di progetto e ripristina le dipendenze
COPY ["Data_Coupler/Data_Coupler.csproj", "Data_Coupler/"]
COPY ["DataConnection/DataConnection.csproj", "DataConnection/"]
COPY ["CredentialManager/CredentialManager.csproj", "CredentialManager/"]
COPY ["Components/Components.csproj", "Components/"]
COPY ["nuget.config", "./"]
# Ripristina le dipendenze per tutti i progetti
RUN dotnet restore "Data_Coupler/Data_Coupler.csproj"
# Copia tutto il codice sorgente
COPY . .
# Build del progetto principale
WORKDIR "/src/Data_Coupler"
RUN dotnet build "Data_Coupler.csproj" -c Release -o /app/build
# Stage 2: Publish
FROM build AS publish
RUN dotnet publish "Data_Coupler.csproj" -c Release -o /app/publish /p:UseAppHost=false
# Stage 3: Runtime
FROM mcr.microsoft.com/dotnet/aspnet:9.0-nanoserver-ltsc2022 AS final
WORKDIR /app
# Crea la directory per il database
RUN mkdir C:\ProgramData\Data_Coupler
# Copia i file pubblicati
COPY --from=publish /app/publish .
# Configura le variabili d'ambiente
ENV ASPNETCORE_URLS=http://+:7550
ENV DOTNET_RUNNING_IN_CONTAINER=true
ENV ASPNETCORE_ENVIRONMENT=Production
# Espone la porta dell'applicazione
EXPOSE 7550
# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
CMD powershell -Command "try { $response = Invoke-WebRequest -Uri http://localhost:7550/health -UseBasicParsing -TimeoutSec 5; if ($response.StatusCode -eq 200) { exit 0 } else { exit 1 } } catch { exit 1 }"
# Punto di ingresso
ENTRYPOINT ["dotnet", "Data_Coupler.dll"]
GITHUB_ACTIONS_SETUP.md
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# Configurazione GitHub Actions per Docker Container Registry
## 🔧 Setup Iniziale
Questa guida spiega come configurare il repository GitHub per abilitare la build automatica e il push delle immagini Docker.
## 📋 Prerequisiti
1. Repository GitHub con il codice sorgente
2. Abilitazione GitHub Packages per il repository
3. Permessi di scrittura sui packages
## ⚙️ Configurazione Repository
### 1. Abilitazione GitHub Packages
Le GitHub Actions sono già configurate per usare il `GITHUB_TOKEN` automatico. Non è necessario creare token aggiuntivi.
### 2. Configurazione Secrets (Opzionale)
Se vuoi usare un registry diverso da GitHub Container Registry, aggiungi questi secrets:
1. Vai su: `Settings` → `Secrets and variables` → `Actions`
2. Click su `New repository secret`
3. Aggiungi:
- `REGISTRY_USERNAME`: Username del registry
- `REGISTRY_PASSWORD`: Password o token del registry
### 3. Abilitazione Workflow
Il workflow è già configurato in `.github/workflows/docker-build.yml` e si attiverà automaticamente su:
- Push su branch `main`, `dev`, `staging`
- Manualmente tramite `workflow_dispatch`
## 🚀 Utilizzo
### Build Automatica
Ogni volta che fai push su uno dei branch configurati, il workflow:
1. ✅ Compila il progetto .NET
2. 🐳 Crea immagini Docker per Linux e Windows
3. 📤 Fa push su GitHub Container Registry
4. 🏷️ Applica i tag appropriati basati sul branch
### Tag Generati
#### Branch Main
- `latest` (multi-platform)
- `latest-windows` (solo Windows)
- `main-{sha}` (commit specifico)
- `main-{date}` (timestamp)
#### Branch Dev
- `dev-latest` (multi-platform)
- `dev-latest-windows` (solo Windows)
- `dev-{sha}` (commit specifico)
- `dev-{date}` (timestamp)
#### Branch Staging
- `staging-latest` (multi-platform)
- `staging-latest-windows` (solo Windows)
- `staging-{sha}` (commit specifico)
- `staging-{date}` (timestamp)
### Build Manuale
Per avviare una build manuale:
1. Vai su `Actions` nel repository GitHub
2. Seleziona il workflow `Build and Push Docker Images`
3. Click su `Run workflow`
4. Seleziona il branch
5. (Opzionale) Spunta `Force build` per forzare la build
6. Click su `Run workflow`
## 🔐 Gestione Visibilità Container
### Rendere il Container Pubblico (No Authentication Required)
Per consentire il pull senza autenticazione:
1. Vai su: `https://github.com/[YOUR_USERNAME]/Data-Coupler/packages`
2. Seleziona il package `data-coupler`
3. Click su `Package settings` (icona ingranaggio)
4. Scroll down fino a **Danger Zone**
5. Click su `Change visibility`
6. Seleziona `Public`
7. Digita il nome del repository per confermare
8. Click su `I understand, change package visibility`
⚠️ **Attenzione**: Un container pubblico può essere scaricato da chiunque su internet.
### Container Privato con Accesso Team
Per mantenere il container privato ma accessibile al team:
1. Vai su `Package settings`
2. Nella sezione **Manage Actions access**:
- Seleziona `Inherit access from source repository`
3. Per dare accesso a utenti specifici:
- Scroll alla sezione **Manage teams and people access**
- Click su `Add teams` o `Add people`
- Seleziona l'utente/team e il livello di accesso (Read, Write, Admin)
### Token per Pull Privati
Se il container rimane privato, gli utenti dovranno autenticarsi:
```bash
# 1. Crea un Personal Access Token
# GitHub → Settings → Developer settings → Personal access tokens → Tokens (classic)
# Scope richiesto: read:packages
# 2. Login
echo "ghp_YOUR_TOKEN" | docker login ghcr.io -u YOUR_USERNAME --password-stdin
# 3. Pull
docker pull ghcr.io/alessiodalsi/data-coupler:latest
```
## 🔍 Verifica Build
### Check Status Workflow
1. Vai su `Actions` nel repository
2. Verifica che il workflow sia completato con successo (✅)
3. Click sul workflow per vedere i dettagli
### Verifica Immagini Pubblicate
1. Vai su: `https://github.com/[YOUR_USERNAME]/Data-Coupler/packages`
2. Verifica che il package `data-coupler` sia presente
3. Click sul package per vedere tutti i tag disponibili
### Test Pull Immagine
```bash
# Test pull (se pubblico)
docker pull ghcr.io/alessiodalsi/data-coupler:latest
# Verifica immagine
docker images | grep data-coupler
# Test run
docker run -d -p 7550:7550 ghcr.io/alessiodalsi/data-coupler:latest
# Verifica funzionamento
curl http://localhost:7550/health
```
## 📊 Monitoraggio
### Visualizzare Log di Build
1. Vai su `Actions`
2. Click sul workflow run
3. Espandi i job `build-linux` e `build-windows`
4. Visualizza i log dettagliati di ogni step
### Statistiche Package
Nella pagina del package puoi vedere:
- 📈 Download totali
- 📦 Dimensione immagini
- 🏷️ Tag disponibili
- 📅 Data ultima modifica
## 🛠️ Troubleshooting
### Workflow Fallisce
**Errore: Permessi insufficienti**
```
Error: failed to solve: failed to push: insufficient_scope
```
**Soluzione**: Verifica che le Actions abbiano permessi di scrittura:
- `Settings` → `Actions` → `General`
- Sezione **Workflow permissions**
- Seleziona `Read and write permissions`
- Salva
**Errore: Build timeout**
```
Error: The operation was canceled
```
**Soluzione**:
- Verifica che non ci siano file grandi non necessari
- Controlla il `.dockerignore`
- Aumenta il timeout nel workflow (default: 360 minuti)
### Push Fallisce
**Errore: Authentication required**
```
Error: failed to authorize: failed to fetch anonymous token
```
**Soluzione**: Il `GITHUB_TOKEN` dovrebbe funzionare automaticamente. Se persiste:
1. Vai su `Settings` → `Actions` → `General`
2. Verifica che `GITHUB_TOKEN` abbia permessi packages
### Immagine Non Si Avvia
**Errore: Database not initialized**
```
Error: Timeout durante l'inizializzazione del database
```
**Soluzione**: Monta un volume per persistere i dati:
```bash
docker run -d \
-v /var/lib/data-coupler:/var/lib/Data_Coupler \
ghcr.io/alessiodalsi/data-coupler:latest
```
## 📚 Risorse Aggiuntive
- [GitHub Packages Documentation](https://docs.github.com/en/packages)
- [GitHub Actions Docker Build](https://docs.github.com/en/actions/publishing-packages/publishing-docker-images)
- [Docker Best Practices](https://docs.docker.com/develop/dev-best-practices/)
## 🆘 Supporto
Se riscontri problemi:
1. Controlla i log del workflow su GitHub Actions
2. Verifica la documentazione in `DOCKER_DEPLOYMENT.md`
3. Apri una issue sul repository GitHub
---
**Ultimo Aggiornamento**: Gennaio 2026
**Versione Workflow**: 1.0
PUBLIC_CONTAINER_SETUP.md
+304
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@@ -0,0 +1,304 @@
# 🔓 Configurazione Container Pubblico - Guida Step-by-Step
## Obiettivo
Rendere il container Docker pull-able **senza credenziali** da chiunque.
## ⚠️ Considerazioni Importanti
### Pro e Contro
#### ✅ Vantaggi Container Pubblico
- Nessuna autenticazione richiesta per pull
- Facile distribuzione per utenti finali
- Ideale per progetti open source
- Riduce friction nell'adozione
- Nessun token management per utenti
#### ⚠️ Svantaggi Container Pubblico
- Il codice compilato è accessibile pubblicamente
- Chiunque può scaricare e analizzare l'immagine
- Nessun controllo su chi usa il container
- Potenziale esposizione di configurazioni hardcoded
## 🔒 Alternative al Container Pubblico
Se la privacy è importante, considera invece:
### Opzione 1: Container Privato + GitHub Team Access
```yaml
Configurazione:
1. Container rimane privato
2. Aggiungi membri team con permessi read
3. Team members usano loro GitHub PAT per pull
Vantaggi:
- Controllo accessi granulare
- Audit trail degli accessi
- Solo team autorizzato può scaricare
```
### Opzione 2: Container Privato + Deploy Keys
```yaml
Configurazione:
1. Container rimane privato
2. Crea bot account per CI/CD
3. Bot account ha read-only access al package
4. Deploy keys distribuite solo a server autorizzati
Vantaggi:
- Nessun accesso umano diretto
- Token rotativi per sicurezza
- Adatto per production deployments
```
### Opzione 3: Azure Container Registry / AWS ECR (Privati)
```yaml
Configurazione:
1. Push su registry privato Azure/AWS
2. Usa managed identities per pull
3. Nessuna credenziale hardcoded
Vantaggi:
- Integrazione nativa cloud
- Nessun costo GitHub Package storage
- Policy avanzate di retention
```
## 📋 Se Decidi per Container Pubblico
### Step 1: Verifica Prima Build Completata
```bash
# 1. Fai push del codice su GitHub
git add .
git commit -m "Add Docker support and CI/CD"
git push origin main
# 2. Vai su GitHub Actions
# https://github.com/[USERNAME]/Data-Coupler/actions
# 3. Attendi completamento workflow "Build and Push Docker Images"
# Deve mostrare ✅ verde su tutti i job
```
### Step 2: Trova il Package
```
1. Vai al tuo repository GitHub
URL: https://github.com/[USERNAME]/Data-Coupler
2. Click sulla tab "Packages" (lato destro)
Oppure: https://github.com/[USERNAME]?tab=packages
3. Dovresti vedere il package "data-coupler"
Se non lo vedi, verifica che la build sia completata con successo
```
### Step 3: Cambia Visibilità a Pubblico
```
1. Click sul package "data-coupler"
2. Click su "Package settings" (icona ingranaggio in alto a destra)
3. Scroll fino alla sezione "Danger Zone" (in fondo alla pagina)
4. Trova "Change package visibility"
5. Click sul pulsante "Change visibility"
6. Nella dialog che appare:
- Seleziona "Public"
- Leggi il warning
- Digita il nome completo del repository: [USERNAME]/Data-Coupler
- Click "I understand the consequences, change package visibility"
7. Conferma con la tua password se richiesto
```
### Step 4: Verifica Configurazione Pubblica
```
1. Logout da GitHub (o usa finestra incognito)
2. Vai a: https://github.com/[USERNAME]/Data-Coupler/pkgs/container/data-coupler
3. Dovresti vedere:
- Badge "Public" vicino al nome
- Pull command senza autenticazione:
docker pull ghcr.io/[username]/data-coupler:latest
4. La sezione "Installation" mostra come fare pull senza credenziali
```
### Step 5: Test Pull Senza Autenticazione
```bash
# 1. Logout da GitHub Container Registry (se sei loggato)
docker logout ghcr.io
# 2. Pull senza credenziali
docker pull ghcr.io/[username]/data-coupler:latest
# Se funziona, vedrai:
# latest: Pulling from [username]/data-coupler
# [hash]: Pull complete
# ...
# Status: Downloaded newer image for ghcr.io/[username]/data-coupler:latest
# 3. Test run
docker run -d -p 7550:7550 --name data-coupler-test \
ghcr.io/[username]/data-coupler:latest
# 4. Verifica funzionamento
sleep 10
curl http://localhost:7550/health
# Output: {"status":"healthy","timestamp":"..."}
# 5. Cleanup
docker stop data-coupler-test
docker rm data-coupler-test
```
## 🔧 Configurazione GitHub Actions per Pubblico
Le GitHub Actions sono già configurate correttamente per container pubblici. Non servono modifiche.
**Configurazione Attuale** (`.github/workflows/docker-build.yml`):
```yaml
- name: Log in to GitHub Container Registry
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }} # ✅ Usa token automatico
```
Il `GITHUB_TOKEN` ha già i permessi necessari se:
1. ✅ Workflow permissions = "Read and write"
2. ✅ Package è pubblico
## 📝 Aggiorna Documentazione
Dopo aver reso pubblico il container, aggiorna i riferimenti:
### File da Aggiornare
1. **README.md**
```markdown
## Quick Start
\`\`\`bash
# Pull e run (nessuna autenticazione richiesta)
docker run -d -p 7550:7550 ghcr.io/[username]/data-coupler:latest
\`\`\`
```
2. **DOCKER_DEPLOYMENT.md**
Assicurati che la sezione "Pull senza autenticazione" sia prominente.
3. **GITHUB_ACTIONS_SETUP.md**
Aggiungi nota che il container è configurato come pubblico.
## 🔄 Come Tornare Privato
Se cambi idea:
```
1. Package settings → Danger Zone → Change visibility
2. Seleziona "Private"
3. Conferma
Da quel momento in poi, il pull richiederà autenticazione:
docker login ghcr.io -u USERNAME
Password: [GitHub PAT]
```
## 📊 Monitoraggio Container Pubblico
### Statistiche Disponibili
Nel package settings puoi vedere:
- **📈 Download count**: Quante volte è stato scaricato
- **📦 Storage used**: Spazio occupato su GitHub
- **🏷️ Tags**: Tutte le versioni disponibili
- **📅 Activity**: Storia degli aggiornamenti
### Costi
**GitHub Container Registry:**
- ✅ Container pubblici: Storage **GRATUITO** illimitato
- ✅ Pull pubblici: Bandwidth **GRATUITO** illimitato
- ⚠️ Container privati: 500MB storage gratuito, poi $0.008/GB/mese
## 🚨 Security Best Practices (Anche per Container Pubblici)
### 1. Non Hardcodare Secrets
```dockerfile
❌ MAI:
ENV API_KEY="hardcoded-secret-key"
ENV PASSWORD="admin123"
✅ SEMPRE:
ENV API_KEY="" # Impostato a runtime con -e
```
### 2. Multi-Stage Build (Già Implementato)
```dockerfile
✅ Il Dockerfile usa multi-stage:
FROM sdk AS build # Immagine grande con compilatori
FROM aspnet AS final # Solo runtime, immagine piccola
# Risultato: codice sorgente NON incluso nell'immagine finale
```
### 3. Scan delle Vulnerabilità
```bash
# Usa Trivy per scan sicurezza
docker run --rm -v /var/run/docker.sock:/var/run/docker.sock \
aquasec/trivy image ghcr.io/[username]/data-coupler:latest
# Oppure integra in GitHub Actions (future enhancement)
```
### 4. Firma delle Immagini
```yaml
# GitHub Actions già genera attestazioni (configurato)
- name: Generate artifact attestation
uses: actions/attest-build-provenance@v1
# Crea firma crittografica verificabile
```
## ✅ Checklist Finale
Prima di rendere pubblico, verifica:
- [ ] Build GitHub Actions completata con successo
- [ ] Nessun secret hardcodato nei Dockerfile
- [ ] Database path configurato correttamente per volumes
- [ ] Health endpoint funziona
- [ ] Test pull e run eseguiti con successo
- [ ] Documentazione aggiornata con nuovo registry URL
- [ ] Team informato del cambio di visibilità
## 📞 Rollback Plan
Se qualcosa va storto:
```bash
# 1. Torna privato immediatamente
# Package settings → Private
# 2. Se serve, elimina tag specifico
docker rmi ghcr.io/[username]/data-coupler:problematic-tag
# 3. Re-build e re-push
git revert [commit-hash]
git push origin main
# GitHub Actions ri-builda automaticamente
```
---
**Data Creazione**: 16 Gennaio 2026
**Versione Guida**: 1.0
**Raccomandazione**: ✅ Pubblico per Open Source | ⚠️ Privato per Enterprise
README.md
+38 -4
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@@ -115,20 +115,54 @@ Data-Coupler/
### Prerequisiti ### Prerequisiti
- .NET 9.0 SDK - .NET 9.0 SDK
- Visual Studio 2022 o VS Code - Visual Studio 2022 o VS Code
- Docker (opzionale, per deployment containerizzato)
### Build ### Build Locale
```bash ```bash
dotnet build Data_Coupler.sln dotnet build Data_Coupler.sln
``` ```
### Esecuzione ### Esecuzione Locale
```bash ```bash
dotnet run --project Data_Coupler/Data_Coupler.csproj dotnet run --project Data_Coupler/Data_Coupler.csproj
``` ```
L'applicazione sarà disponibile su: L'applicazione sarà disponibile su:
- HTTP: http://localhost:5135 - HTTP: http://localhost:7550
- HTTPS: https://localhost:7132
### 🐳 Deployment Docker
**Quick Start con Docker:**
```bash
# Pull e run (immagine pubblica)
docker run -d -p 7550:7550 -v data-coupler-data:/var/lib/Data_Coupler ghcr.io/alessiodalsi/data-coupler:latest
# Con Docker Compose
docker-compose up -d
```
**Build Locale:**
```bash
# Linux
docker build -t data-coupler:local -f Dockerfile .
# Windows
docker build -t data-coupler:local-windows -f Dockerfile.windows .
# Script automatico (PowerShell)
.\build-docker.ps1 -Target all -Test
# Script automatico (Bash)
./build-docker.sh all
```
**Immagini Disponibili:**
- **Linux**: `ghcr.io/alessiodalsi/data-coupler:latest`
- **Windows**: `ghcr.io/alessiodalsi/data-coupler:latest-windows`
- **Dev**: `ghcr.io/alessiodalsi/data-coupler:dev-latest`
- **Staging**: `ghcr.io/alessiodalsi/data-coupler:staging-latest`
📚 **Documentazione Docker Completa**: Vedi [DOCKER_DEPLOYMENT.md](DOCKER_DEPLOYMENT.md) e [GITHUB_ACTIONS_SETUP.md](GITHUB_ACTIONS_SETUP.md)
## Caratteristiche di Sicurezza ## Caratteristiche di Sicurezza
build-docker.ps1
+168
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@@ -0,0 +1,168 @@
# PowerShell script per build e test locale dei container Docker
# Utilizzo: .\build-docker.ps1 [-Target <linux|windows|all>] [-Test] [-Clean]
param(
[Parameter(Position=0)]
[ValidateSet("linux", "windows", "all", "clean")]
[string]$Target = "all",
[switch]$Test,
[switch]$Clean
)
$ErrorActionPreference = "Stop"
Write-Host "╔═══════════════════════════════════════════╗" -ForegroundColor Green
Write-Host "║ Data-Coupler Docker Build Script ║" -ForegroundColor Green
Write-Host "╚═══════════════════════════════════════════╝" -ForegroundColor Green
Write-Host ""
# Funzione per build Linux
function Build-Linux {
Write-Host "📦 Building Linux container..." -ForegroundColor Yellow
docker build -t data-coupler:local -f Dockerfile .
if ($LASTEXITCODE -eq 0) {
Write-Host "✅ Linux container built successfully!" -ForegroundColor Green
} else {
Write-Host "❌ Linux container build failed!" -ForegroundColor Red
exit 1
}
Write-Host ""
}
# Funzione per build Windows
function Build-Windows {
Write-Host "📦 Building Windows container..." -ForegroundColor Yellow
docker build -t data-coupler:local-windows -f Dockerfile.windows .
if ($LASTEXITCODE -eq 0) {
Write-Host "✅ Windows container built successfully!" -ForegroundColor Green
} else {
Write-Host "❌ Windows container build failed!" -ForegroundColor Red
exit 1
}
Write-Host ""
}
# Funzione per test container
function Test-Container {
param(
[string]$Image,
[string]$ContainerName
)
Write-Host "🧪 Testing container: $Image" -ForegroundColor Yellow
# Stop e rimuovi container esistente
docker stop $ContainerName 2>$null | Out-Null
docker rm $ContainerName 2>$null | Out-Null
# Avvia container
Write-Host "Starting container..."
docker run -d --name $ContainerName -p 7550:7550 $Image | Out-Null
# Attendi avvio (max 60 secondi)
Write-Host "Waiting for container to be ready..."
$ready = $false
for ($i = 1; $i -le 60; $i++) {
$logs = docker logs $ContainerName 2>&1
if ($logs -match "Now listening on") {
Write-Host "✅ Container started successfully!" -ForegroundColor Green
$ready = $true
break
}
if ($i -eq 60) {
Write-Host "❌ Container failed to start within 60 seconds" -ForegroundColor Red
docker logs $ContainerName
return $false
}
Start-Sleep -Seconds 1
}
if (-not $ready) {
return $false
}
# Test health endpoint
Write-Host "Testing health endpoint..."
Start-Sleep -Seconds 5
try {
$response = Invoke-WebRequest -Uri "http://localhost:7550/health" -UseBasicParsing -TimeoutSec 10
if ($response.StatusCode -eq 200) {
Write-Host "✅ Health check passed!" -ForegroundColor Green
} else {
Write-Host "❌ Health check failed with status: $($response.StatusCode)" -ForegroundColor Red
return $false
}
} catch {
Write-Host "❌ Health check failed: $_" -ForegroundColor Red
docker logs $ContainerName
return $false
}
# Mostra log
Write-Host ""
Write-Host "📋 Container logs:" -ForegroundColor Yellow
docker logs --tail 20 $ContainerName
Write-Host ""
Write-Host "✅ Container test completed successfully!" -ForegroundColor Green
Write-Host "💡 Container is running at: http://localhost:7550" -ForegroundColor Yellow
Write-Host "💡 Stop with: docker stop $ContainerName" -ForegroundColor Yellow
Write-Host ""
return $true
}
# Funzione per cleanup
function Clean-Containers {
Write-Host "🧹 Cleaning up test containers..." -ForegroundColor Yellow
docker stop data-coupler-test 2>$null | Out-Null
docker rm data-coupler-test 2>$null | Out-Null
docker stop data-coupler-test-windows 2>$null | Out-Null
docker rm data-coupler-test-windows 2>$null | Out-Null
Write-Host "✅ Cleanup completed" -ForegroundColor Green
}
# Menu principale
if ($Clean) {
Clean-Containers
exit 0
}
switch ($Target) {
"linux" {
Build-Linux
if ($Test) {
Test-Container -Image "data-coupler:local" -ContainerName "data-coupler-test"
}
}
"windows" {
Build-Windows
if ($Test) {
Test-Container -Image "data-coupler:local-windows" -ContainerName "data-coupler-test-windows"
}
}
"all" {
Build-Linux
Build-Windows
if ($Test) {
Write-Host "Testing Linux container..." -ForegroundColor Cyan
Test-Container -Image "data-coupler:local" -ContainerName "data-coupler-test"
Write-Host ""
Write-Host "Testing Windows container..." -ForegroundColor Cyan
Test-Container -Image "data-coupler:local-windows" -ContainerName "data-coupler-test-windows"
}
}
"clean" {
Clean-Containers
}
}
Write-Host ""
Write-Host "🎉 All done!" -ForegroundColor Green
Write-Host ""
Write-Host "Usage examples:" -ForegroundColor Cyan
Write-Host " .\build-docker.ps1 linux -Test # Build and test Linux container" -ForegroundColor Gray
Write-Host " .\build-docker.ps1 windows -Test # Build and test Windows container" -ForegroundColor Gray
Write-Host " .\build-docker.ps1 all # Build all containers" -ForegroundColor Gray
Write-Host " .\build-docker.ps1 -Clean # Clean up test containers" -ForegroundColor Gray
build-docker.sh
+152
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@@ -0,0 +1,152 @@
#!/bin/bash
# Script per build e test locale dei container Docker
# Utilizzo: ./build-docker.sh [linux|windows|all]
set -e
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
cd "$SCRIPT_DIR"
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
NC='\033[0m' # No Color
echo -e "${GREEN}╔═══════════════════════════════════════════╗${NC}"
echo -e "${GREEN}║ Data-Coupler Docker Build Script ║${NC}"
echo -e "${GREEN}╚═══════════════════════════════════════════╝${NC}"
echo ""
# Funzione per build Linux
build_linux() {
echo -e "${YELLOW}📦 Building Linux container...${NC}"
docker build -t data-coupler:local -f Dockerfile .
echo -e "${GREEN}✅ Linux container built successfully!${NC}"
echo ""
}
# Funzione per build Windows
build_windows() {
echo -e "${YELLOW}📦 Building Windows container...${NC}"
if [[ "$OSTYPE" == "msys" || "$OSTYPE" == "win32" ]]; then
docker build -t data-coupler:local-windows -f Dockerfile.windows .
echo -e "${GREEN}✅ Windows container built successfully!${NC}"
else
echo -e "${RED}⚠️ Windows containers can only be built on Windows hosts${NC}"
return 1
fi
echo ""
}
# Funzione per test container
test_container() {
local IMAGE=$1
local CONTAINER_NAME=$2
echo -e "${YELLOW}🧪 Testing container: $IMAGE${NC}"
# Stop e rimuovi container esistente
docker stop $CONTAINER_NAME 2>/dev/null || true
docker rm $CONTAINER_NAME 2>/dev/null || true
# Avvia container
echo "Starting container..."
docker run -d \
--name $CONTAINER_NAME \
-p 7550:7550 \
$IMAGE
# Attendi avvio (max 60 secondi)
echo "Waiting for container to be ready..."
for i in {1..60}; do
if docker logs $CONTAINER_NAME 2>&1 | grep -q "Now listening on"; then
echo -e "${GREEN}✅ Container started successfully!${NC}"
break
fi
if [ $i -eq 60 ]; then
echo -e "${RED}❌ Container failed to start within 60 seconds${NC}"
docker logs $CONTAINER_NAME
return 1
fi
sleep 1
done
# Test health endpoint
echo "Testing health endpoint..."
sleep 5
if curl -f http://localhost:7550/health &>/dev/null; then
echo -e "${GREEN}✅ Health check passed!${NC}"
else
echo -e "${RED}❌ Health check failed${NC}"
docker logs $CONTAINER_NAME
return 1
fi
# Mostra log
echo ""
echo -e "${YELLOW}📋 Container logs:${NC}"
docker logs --tail 20 $CONTAINER_NAME
echo ""
echo -e "${GREEN}✅ Container test completed successfully!${NC}"
echo -e "${YELLOW}💡 Container is running at: http://localhost:7550${NC}"
echo -e "${YELLOW}💡 Stop with: docker stop $CONTAINER_NAME${NC}"
echo ""
}
# Funzione per cleanup
cleanup() {
echo -e "${YELLOW}🧹 Cleaning up test containers...${NC}"
docker stop data-coupler-test 2>/dev/null || true
docker rm data-coupler-test 2>/dev/null || true
docker stop data-coupler-test-windows 2>/dev/null || true
docker rm data-coupler-test-windows 2>/dev/null || true
echo -e "${GREEN}✅ Cleanup completed${NC}"
}
# Menu principale
case "${1:-all}" in
linux)
build_linux
read -p "Do you want to test the container? (y/n) " -n 1 -r
echo
if [[ $REPLY =~ ^[Yy]$ ]]; then
test_container "data-coupler:local" "data-coupler-test"
fi
;;
windows)
build_windows
read -p "Do you want to test the container? (y/n) " -n 1 -r
echo
if [[ $REPLY =~ ^[Yy]$ ]]; then
test_container "data-coupler:local-windows" "data-coupler-test-windows"
fi
;;
all)
build_linux
if [[ "$OSTYPE" == "msys" || "$OSTYPE" == "win32" ]]; then
build_windows
fi
read -p "Do you want to test the Linux container? (y/n) " -n 1 -r
echo
if [[ $REPLY =~ ^[Yy]$ ]]; then
test_container "data-coupler:local" "data-coupler-test"
fi
;;
clean)
cleanup
;;
*)
echo "Usage: $0 {linux|windows|all|clean}"
echo ""
echo "Options:"
echo " linux - Build only Linux container"
echo " windows - Build only Windows container (requires Windows host)"
echo " all - Build all containers (default)"
echo " clean - Stop and remove test containers"
exit 1
;;
esac
echo ""
echo -e "${GREEN}🎉 All done!${NC}"
docker-compose.windows.yml
+39
View File
@@ -0,0 +1,39 @@
version: '3.8'
services:
data-coupler:
image: ghcr.io/alessiodalsi/data-coupler:latest-windows
container_name: data-coupler-windows
ports:
- "7550:7550"
volumes:
# Volume per persistenza database e configurazioni
- type: bind
source: C:\ProgramData\Data_Coupler
target: C:\ProgramData\Data_Coupler
# (Opzionale) Mount file di configurazione custom
# - type: bind
# source: .\appsettings.Production.json
# target: C:\app\appsettings.Production.json
# read_only: true
environment:
# Ambiente di esecuzione
- ASPNETCORE_ENVIRONMENT=Production
# URL di ascolto
- ASPNETCORE_URLS=http://+:7550
# Livello di logging
- Logging__LogLevel__Default=Information
- Logging__LogLevel__Microsoft.AspNetCore=Warning
restart: unless-stopped
# Limiti risorse (opzionale)
deploy:
resources:
limits:
cpus: '2'
memory: 2G
reservations:
cpus: '0.5'
memory: 512M
# Nota: Windows containers non supportano completamente tutte le funzionalità di Docker Compose
# Alcune features potrebbero richiedere configurazione aggiuntiva
docker-compose.yml
+51
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@@ -0,0 +1,51 @@
version: '3.8'
services:
data-coupler:
image: ghcr.io/alessiodalsi/data-coupler:latest
container_name: data-coupler
ports:
- "7550:7550"
volumes:
# Volume per persistenza database e configurazioni
- data-coupler-data:/var/lib/Data_Coupler
# (Opzionale) Mount file di configurazione custom
# - ./appsettings.Production.json:/app/appsettings.Production.json:ro
environment:
# Ambiente di esecuzione
- ASPNETCORE_ENVIRONMENT=Production
# URL di ascolto
- ASPNETCORE_URLS=http://+:7550
# Livello di logging (Information, Warning, Error, Debug)
- Logging__LogLevel__Default=Information
- Logging__LogLevel__Microsoft.AspNetCore=Warning
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:7550/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 60s
# Limiti risorse (opzionale ma raccomandato per produzione)
deploy:
resources:
limits:
cpus: '2'
memory: 2G
reservations:
cpus: '0.5'
memory: 512M
volumes:
data-coupler-data:
driver: local
# (Opzionale) Specifica un path specifico sull'host
# driver_opts:
# type: none
# device: /path/to/data
# o: bind
# (Opzionale) Network personalizzato per isolamento
# networks:
# data-coupler-network:
# driver: bridge