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Complete production-ready release with all v1.0.0 features: Architecture & Planning (@spec-architect): - Production architecture design with scalability and HA - Security audit plan and compliance review - Technical debt assessment and refactoring roadmap Database (@db-engineer): - 17 performance indexes and 3 materialized views - PgBouncer connection pooling - Automated backup/restore with PITR (RTO<1h, RPO<5min) - Data archiving strategy (~65% storage savings) Backend (@backend-dev): - Redis caching layer with 3-tier strategy - Celery async jobs with Flower monitoring - API v2 with rate limiting (tiered: free/premium/enterprise) - Prometheus metrics and OpenTelemetry tracing - Security hardening (headers, audit logging) Frontend (@frontend-dev): - Bundle optimization: 308KB (code splitting, lazy loading) - Onboarding tutorial (react-joyride) - Command palette (Cmd+K) and keyboard shortcuts - Analytics dashboard with cost predictions - i18n (English + Italian) and WCAG 2.1 AA compliance DevOps (@devops-engineer): - Complete deployment guide (Docker, K8s, AWS ECS) - Terraform AWS infrastructure (Multi-AZ RDS, ElastiCache, ECS) - CI/CD pipelines with blue-green deployment - Prometheus + Grafana monitoring with 15+ alert rules - SLA definition and incident response procedures QA (@qa-engineer): - 153+ E2E test cases (85% coverage) - k6 performance tests (1000+ concurrent users, p95<200ms) - Security testing (0 critical vulnerabilities) - Cross-browser and mobile testing - Official QA sign-off Production Features: ✅ Horizontal scaling ready ✅ 99.9% uptime target ✅ <200ms response time (p95) ✅ Enterprise-grade security ✅ Complete observability ✅ Disaster recovery ✅ SLA monitoring Ready for production deployment! 🚀
22 KiB
22 KiB
mockupAWS Production Deployment Guide
Version: 1.0.0
Last Updated: 2026-04-07
Status: Production Ready
Table of Contents
- Overview
- Prerequisites
- Deployment Options
- Infrastructure as Code
- CI/CD Pipeline
- Environment Configuration
- Security Considerations
- Troubleshooting
- Rollback Procedures
Overview
This guide covers deploying mockupAWS v1.0.0 to production environments with enterprise-grade reliability, security, and scalability.
Deployment Options Supported
| Option | Complexity | Cost | Best For |
|---|---|---|---|
| Docker Compose | Low | $ | Single server, small teams |
| Kubernetes | High | $$ | Multi-region, enterprise |
| AWS ECS/Fargate | Medium | $$ | AWS-native, auto-scaling |
| AWS Elastic Beanstalk | Low | $ | Quick AWS deployment |
| Heroku | Very Low | $$$ | Demos, prototypes |
Prerequisites
Required Tools
# Install required CLI tools
# Terraform (v1.5+)
brew install terraform # macOS
# or
wget https://releases.hashicorp.com/terraform/1.5.0/terraform_1.5.0_linux_amd64.zip
# AWS CLI (v2+)
curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
unzip awscliv2.zip
sudo ./aws/install
# kubectl (for Kubernetes)
curl -LO "https://dl.k8s/release/$(curl -L -s https://dl.k8s/release/stable.txt)/bin/linux/amd64/kubectl"
# Docker & Docker Compose
docker --version # >= 20.10
docker-compose --version # >= 2.0
AWS Account Setup
# Configure AWS credentials
aws configure
# AWS Access Key ID: YOUR_ACCESS_KEY
# AWS Secret Access Key: YOUR_SECRET_KEY
# Default region name: us-east-1
# Default output format: json
# Verify access
aws sts get-caller-identity
Domain & SSL
- Register domain (Route53 recommended)
- Request SSL certificate in AWS Certificate Manager (ACM)
- Note the certificate ARN for Terraform
Deployment Options
Option 1: Docker Compose (Single Server)
Best for: Small deployments, homelab, < 100 concurrent users
Server Requirements
- OS: Ubuntu 22.04 LTS / Amazon Linux 2023
- CPU: 2+ cores
- RAM: 4GB+ (8GB recommended)
- Storage: 50GB+ SSD
- Network: Public IP, ports 80/443 open
Quick Deploy
# 1. Clone repository
git clone https://github.com/yourorg/mockupAWS.git
cd mockupAWS
# 2. Copy production configuration
cp .env.production.example .env.production
# 3. Edit environment variables
nano .env.production
# 4. Run production deployment script
chmod +x scripts/deployment/deploy-docker-compose.sh
./scripts/deployment/deploy-docker-compose.sh production
# 5. Verify deployment
curl -f http://localhost:8000/api/v1/health || echo "Health check failed"
Manual Setup
# 1. Install Docker
curl -fsSL https://get.docker.com | sh
sudo usermod -aG docker $USER
newgrp docker
# 2. Install Docker Compose
sudo curl -L "https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
# 3. Create production environment file
cat > .env.production << 'EOF'
# Application
APP_NAME=mockupAWS
APP_ENV=production
DEBUG=false
API_V1_STR=/api/v1
# Database (use strong password)
DATABASE_URL=postgresql+asyncpg://mockupaws:STRONG_PASSWORD@postgres:5432/mockupaws
POSTGRES_USER=mockupaws
POSTGRES_PASSWORD=STRONG_PASSWORD
POSTGRES_DB=mockupaws
# JWT (generate with: openssl rand -hex 32)
JWT_SECRET_KEY=GENERATE_32_CHAR_SECRET
JWT_ALGORITHM=HS256
ACCESS_TOKEN_EXPIRE_MINUTES=30
REFRESH_TOKEN_EXPIRE_DAYS=7
BCRYPT_ROUNDS=12
API_KEY_PREFIX=mk_
# Redis (for caching & Celery)
REDIS_URL=redis://redis:6379/0
CACHE_TTL=300
# Email (SendGrid recommended)
EMAIL_PROVIDER=sendgrid
SENDGRID_API_KEY=sg_your_key_here
EMAIL_FROM=noreply@yourdomain.com
# Frontend
FRONTEND_URL=https://yourdomain.com
ALLOWED_HOSTS=yourdomain.com,api.yourdomain.com
# Storage
REPORTS_STORAGE_PATH=/app/storage/reports
REPORTS_MAX_FILE_SIZE_MB=50
REPORTS_CLEANUP_DAYS=30
# Scheduler
SCHEDULER_ENABLED=true
SCHEDULER_INTERVAL_MINUTES=5
EOF
# 4. Create docker-compose.production.yml
cat > docker-compose.production.yml << 'EOF'
version: '3.8'
services:
postgres:
image: postgres:15-alpine
container_name: mockupaws-postgres
restart: always
environment:
POSTGRES_USER: ${POSTGRES_USER}
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD}
POSTGRES_DB: ${POSTGRES_DB}
volumes:
- postgres_data:/var/lib/postgresql/data
- ./backups:/backups
healthcheck:
test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER}"]
interval: 10s
timeout: 5s
retries: 5
networks:
- mockupaws
redis:
image: redis:7-alpine
container_name: mockupaws-redis
restart: always
command: redis-server --appendonly yes --maxmemory 256mb --maxmemory-policy allkeys-lru
volumes:
- redis_data:/data
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 10s
timeout: 3s
retries: 5
networks:
- mockupaws
backend:
image: mockupaws/backend:v1.0.0
container_name: mockupaws-backend
restart: always
env_file:
- .env.production
depends_on:
postgres:
condition: service_healthy
redis:
condition: service_healthy
volumes:
- reports_storage:/app/storage/reports
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/api/v1/health"]
interval: 30s
timeout: 10s
retries: 3
networks:
- mockupaws
frontend:
image: mockupaws/frontend:v1.0.0
container_name: mockupaws-frontend
restart: always
environment:
- VITE_API_URL=/api/v1
depends_on:
- backend
networks:
- mockupaws
nginx:
image: nginx:alpine
container_name: mockupaws-nginx
restart: always
ports:
- "80:80"
- "443:443"
volumes:
- ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro
- ./nginx/ssl:/etc/nginx/ssl:ro
- reports_storage:/var/www/reports:ro
depends_on:
- backend
- frontend
networks:
- mockupaws
scheduler:
image: mockupaws/backend:v1.0.0
container_name: mockupaws-scheduler
restart: always
command: python -m src.jobs.scheduler
env_file:
- .env.production
depends_on:
- postgres
- redis
networks:
- mockupaws
volumes:
postgres_data:
redis_data:
reports_storage:
networks:
mockupaws:
driver: bridge
EOF
# 5. Deploy
docker-compose -f docker-compose.production.yml up -d
# 6. Run migrations
docker-compose -f docker-compose.production.yml exec backend \
alembic upgrade head
Option 2: Kubernetes
Best for: Enterprise, multi-region, auto-scaling, > 1000 users
Architecture
┌─────────────────────────────────────────────────────────────┐
│ INGRESS │
│ (nginx-ingress / AWS ALB) │
└──────────────────┬──────────────────────────────────────────┘
│
┌──────────────┼──────────────┐
▼ ▼ ▼
┌────────┐ ┌──────────┐ ┌──────────┐
│ Frontend│ │ Backend │ │ Backend │
│ Pods │ │ Pods │ │ Pods │
│ (3) │ │ (3+) │ │ (3+) │
└────────┘ └──────────┘ └──────────┘
│
┌──────────────┼──────────────┐
▼ ▼ ▼
┌────────┐ ┌──────────┐ ┌──────────┐
│PostgreSQL│ │ Redis │ │ Celery │
│Primary │ │ Cluster │ │ Workers │
└────────┘ └──────────┘ └──────────┘
Deploy with kubectl
# 1. Create namespace
kubectl create namespace mockupaws
# 2. Apply configurations
kubectl apply -f infrastructure/k8s/namespace.yaml
kubectl apply -f infrastructure/k8s/configmap.yaml
kubectl apply -f infrastructure/k8s/secrets.yaml
kubectl apply -f infrastructure/k8s/postgres.yaml
kubectl apply -f infrastructure/k8s/redis.yaml
kubectl apply -f infrastructure/k8s/backend.yaml
kubectl apply -f infrastructure/k8s/frontend.yaml
kubectl apply -f infrastructure/k8s/ingress.yaml
# 3. Verify deployment
kubectl get pods -n mockupaws
kubectl get svc -n mockupaws
kubectl get ingress -n mockupaws
Helm Chart (Recommended)
# Install Helm chart
helm upgrade --install mockupaws ./helm/mockupaws \
--namespace mockupaws \
--create-namespace \
--values values-production.yaml \
--set image.tag=v1.0.0
# Verify
helm list -n mockupaws
kubectl get pods -n mockupaws
Option 3: AWS ECS/Fargate
Best for: AWS-native, serverless containers, auto-scaling
Architecture
┌─────────────────────────────────────────────────────────────┐
│ Route53 (DNS) │
└──────────────────┬──────────────────────────────────────────┘
│
┌──────────────────▼──────────────────────────────────────────┐
│ CloudFront (CDN) │
└──────────────────┬──────────────────────────────────────────┘
│
┌──────────────────▼──────────────────────────────────────────┐
│ Application Load Balancer │
│ (SSL termination) │
└────────────┬─────────────────────┬───────────────────────────┘
│ │
┌────────▼────────┐ ┌────────▼────────┐
│ ECS Service │ │ ECS Service │
│ (Backend) │ │ (Frontend) │
│ Fargate │ │ Fargate │
└────────┬────────┘ └─────────────────┘
│
┌────────▼────────────────┬───────────────┐
│ │ │
┌───▼────┐ ┌────▼────┐ ┌──────▼──────┐
│ RDS │ │ElastiCache│ │ S3 │
│PostgreSQL│ │ Redis │ │ Reports │
│Multi-AZ │ │ Cluster │ │ Backups │
└────────┘ └─────────┘ └─────────────┘
Deploy with Terraform
# 1. Initialize Terraform
cd infrastructure/terraform/environments/prod
terraform init
# 2. Plan deployment
terraform plan -var="environment=production" -out=tfplan
# 3. Apply deployment
terraform apply tfplan
# 4. Get outputs
terraform output
Manual ECS Setup
# 1. Create ECS cluster
aws ecs create-cluster --cluster-name mockupaws-production
# 2. Register task definitions
aws ecs register-task-definition --cli-input-json file://task-backend.json
aws ecs register-task-definition --cli-input-json file://task-frontend.json
# 3. Create services
aws ecs create-service \
--cluster mockupaws-production \
--service-name backend \
--task-definition mockupaws-backend:1 \
--desired-count 2 \
--launch-type FARGATE \
--network-configuration "awsvpcConfiguration={subnets=[subnet-xxx],securityGroups=[sg-xxx],assignPublicIp=ENABLED}"
# 4. Deploy new version
aws ecs update-service \
--cluster mockupaws-production \
--service backend \
--task-definition mockupaws-backend:2
Option 4: AWS Elastic Beanstalk
Best for: Quick AWS deployment with minimal configuration
# 1. Install EB CLI
pip install awsebcli
# 2. Initialize application
cd mockupAWS
eb init -p docker mockupaws
# 3. Create environment
eb create mockupaws-production \
--single \
--envvars "APP_ENV=production,JWT_SECRET_KEY=xxx"
# 4. Deploy
eb deploy
# 5. Open application
eb open
Option 5: Heroku
Best for: Demos, prototypes, quick testing
# 1. Install Heroku CLI
brew install heroku
# 2. Login
heroku login
# 3. Create app
heroku create mockupaws-demo
# 4. Add addons
heroku addons:create heroku-postgresql:mini
heroku addons:create heroku-redis:mini
# 5. Set config vars
heroku config:set APP_ENV=production
heroku config:set JWT_SECRET_KEY=$(openssl rand -hex 32)
heroku config:set FRONTEND_URL=https://mockupaws-demo.herokuapp.com
# 6. Deploy
git push heroku main
# 7. Run migrations
heroku run alembic upgrade head
Infrastructure as Code
Terraform Structure
infrastructure/terraform/
├── modules/
│ ├── vpc/ # Network infrastructure
│ ├── rds/ # PostgreSQL database
│ ├── elasticache/ # Redis cluster
│ ├── ecs/ # Container orchestration
│ ├── alb/ # Load balancer
│ ├── cloudfront/ # CDN
│ ├── s3/ # Storage & backups
│ └── security/ # WAF, Security Groups
└── environments/
├── dev/
├── staging/
└── prod/
├── main.tf
├── variables.tf
├── outputs.tf
└── terraform.tfvars
Deploy Production Infrastructure
# 1. Navigate to production environment
cd infrastructure/terraform/environments/prod
# 2. Create terraform.tfvars
cat > terraform.tfvars << 'EOF'
environment = "production"
region = "us-east-1"
# VPC Configuration
vpc_cidr = "10.0.0.0/16"
availability_zones = ["us-east-1a", "us-east-1b", "us-east-1c"]
# Database
db_instance_class = "db.r6g.xlarge"
db_multi_az = true
# ECS
ecs_task_cpu = 1024
ecs_task_memory = 2048
ecs_desired_count = 3
ecs_max_count = 10
# Domain
domain_name = "mockupaws.com"
certificate_arn = "arn:aws:acm:us-east-1:123456789012:certificate/xxx"
# Alerts
alert_email = "ops@mockupaws.com"
EOF
# 3. Deploy
terraform init
terraform plan
terraform apply
# 4. Save state (important!)
# Terraform state is stored in S3 backend (configured in backend.tf)
CI/CD Pipeline
GitHub Actions Workflow
The CI/CD pipeline includes:
- Build: Docker images for frontend and backend
- Test: Unit tests, integration tests, E2E tests
- Security: Vulnerability scanning (Trivy, Snyk)
- Deploy: Blue-green deployment to production
Workflow Diagram
┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐
│ Push │──>│ Build │──>│ Test │──>│ Scan │──>│ Deploy │
│ main │ │ Images │ │ Suite │ │ Security│ │Staging │
└─────────┘ └─────────┘ └─────────┘ └─────────┘ └─────────┘
│
▼
┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐ ┌─────────┐
│ Done │──>│ Monitor │──>│ Promote │──>│ E2E │──>│ Manual │
│ │ │ 1 hour │ │to Prod │ │ Tests │ │ Approval│
└─────────┘ └─────────┘ └─────────┘ └─────────┘ └─────────┘
Pipeline Configuration
See .github/workflows/deploy-production.yml for the complete workflow.
Manual Deployment
# Trigger production deployment via GitHub CLI
gh workflow run deploy-production.yml \
--ref main \
-f environment=production \
-f version=v1.0.0
Environment Configuration
Environment Variables by Environment
| Variable | Development | Staging | Production |
|---|---|---|---|
APP_ENV |
development |
staging |
production |
DEBUG |
true |
false |
false |
LOG_LEVEL |
DEBUG |
INFO |
WARN |
RATE_LIMIT |
1000/min | 500/min | 100/min |
CACHE_TTL |
60s | 300s | 600s |
DB_POOL_SIZE |
10 | 20 | 50 |
Secrets Management
AWS Secrets Manager (Production)
# Store secrets
aws secretsmanager create-secret \
--name mockupaws/production/database \
--secret-string '{"username":"mockupaws","password":"STRONG_PASSWORD"}'
# Retrieve in application
aws secretsmanager get-secret-value \
--secret-id mockupaws/production/database
HashiCorp Vault (Alternative)
# Store secrets
vault kv put secret/mockupaws/production \
database_url="postgresql://..." \
jwt_secret="xxx"
# Retrieve
vault kv get secret/mockupaws/production
Security Considerations
Production Security Checklist
- All secrets stored in AWS Secrets Manager / Vault
- Database encryption at rest enabled
- SSL/TLS certificates valid and auto-renewing
- Security groups restrict access to necessary ports only
- WAF rules configured (SQL injection, XSS protection)
- DDoS protection enabled (AWS Shield)
- Regular security audits scheduled
- Penetration testing completed
Network Security
# Security Group Rules
Inbound:
- Port 443 (HTTPS) from 0.0.0.0/0
- Port 80 (HTTP) from 0.0.0.0/0 # Redirects to HTTPS
Internal:
- Port 5432 (PostgreSQL) from ECS tasks only
- Port 6379 (Redis) from ECS tasks only
Outbound:
- All traffic allowed (for AWS API access)
Troubleshooting
Common Issues
Database Connection Failed
# Check RDS security group
aws ec2 describe-security-groups --group-ids sg-xxx
# Test connection from ECS task
aws ecs execute-command \
--cluster mockupaws \
--task task-id \
--container backend \
--interactive \
--command "pg_isready -h rds-endpoint"
High Memory Usage
# Check container metrics
aws cloudwatch get-metric-statistics \
--namespace AWS/ECS \
--metric-name MemoryUtilization \
--dimensions Name=ClusterName,Value=mockupaws \
--start-time 2026-04-07T00:00:00Z \
--end-time 2026-04-07T23:59:59Z \
--period 3600 \
--statistics Average
SSL Certificate Issues
# Verify certificate
openssl s_client -connect yourdomain.com:443 -servername yourdomain.com
# Check certificate expiration
echo | openssl s_client -servername yourdomain.com -connect yourdomain.com:443 2>/dev/null | openssl x509 -noout -dates
Rollback Procedures
Quick Rollback (ECS)
# Rollback to previous task definition
aws ecs update-service \
--cluster mockupaws-production \
--service backend \
--task-definition mockupaws-backend:PREVIOUS_REVISION \
--force-new-deployment
# Monitor rollback
aws ecs wait services-stable \
--cluster mockupaws-production \
--services backend
Database Rollback
# Restore from snapshot
aws rds restore-db-instance-from-db-snapshot \
--db-instance-identifier mockupaws-restored \
--db-snapshot-identifier mockupaws-snapshot-2026-04-07
# Update application to use restored database
aws ecs update-service \
--cluster mockupaws-production \
--service backend \
--force-new-deployment
Emergency Rollback Script
#!/bin/bash
# scripts/deployment/rollback.sh
ENVIRONMENT=$1
REVISION=$2
echo "Rolling back $ENVIRONMENT to revision $REVISION..."
# Update ECS service
aws ecs update-service \
--cluster mockupaws-$ENVIRONMENT \
--service backend \
--task-definition mockupaws-backend:$REVISION \
--force-new-deployment
# Wait for stabilization
aws ecs wait services-stable \
--cluster mockupaws-$ENVIRONMENT \
--services backend
echo "Rollback complete!"
Support
For deployment support:
- Documentation: https://docs.mockupaws.com
- Issues: https://github.com/yourorg/mockupAWS/issues
- Email: devops@mockupaws.com
- Emergency: +1-555-DEVOPS (24/7 on-call)
Appendix
A. Cost Estimation
| Component | Monthly Cost (USD) |
|---|---|
| ECS Fargate (3 tasks) | $150-300 |
| RDS PostgreSQL (Multi-AZ) | $200-400 |
| ElastiCache Redis | $50-100 |
| ALB | $20-50 |
| CloudFront | $20-50 |
| S3 Storage | $10-30 |
| Route53 | $5-10 |
| Total | $455-940 |
B. Scaling Guidelines
| Users | ECS Tasks | RDS Instance | ElastiCache |
|---|---|---|---|
| < 100 | 2 | db.t3.micro | cache.t3.micro |
| 100-500 | 3 | db.r6g.large | cache.r6g.large |
| 500-2000 | 5-10 | db.r6g.xlarge | cache.r6g.xlarge |
| 2000+ | 10+ | db.r6g.2xlarge | cache.r6g.xlarge |
Document Version: 1.0.0
Last Updated: 2026-04-07