3c3d3ce042
Frontend Changes: - Fix runtime error: Remove undefined handleModify reference from ActionQueueCard in DashboardPage - Migrate PurchaseOrderDetailsModal to use correct PurchaseOrderItem type from purchase_orders service - Fix item display: Parse unit_price as string (Decimal) instead of number - Use correct field names: item_notes instead of notes - Remove deprecated PurchaseOrder types from suppliers.ts to prevent type conflicts - Update CreatePurchaseOrderModal to use unified types - Clean up API exports: Remove old PO hooks re-exported from suppliers - Add comprehensive translations for PO modal (en, es, eu) Documentation Reorganization: - Move WhatsApp implementation docs to docs/03-features/notifications/whatsapp/ - Move forecast validation docs to docs/03-features/forecasting/ - Move specification docs to docs/03-features/specifications/ - Move deployment docs (Colima, K8s, VPS sizing) to docs/05-deployment/ - Archive completed implementation summaries to docs/archive/implementation-summaries/ - Delete obsolete FRONTEND_CHANGES_NEEDED.md - Standardize filenames to lowercase with hyphens 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
346 lines
9.6 KiB
Markdown
346 lines
9.6 KiB
Markdown
# VPS Sizing for Production Deployment
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## Executive Summary
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This document provides detailed resource requirements for deploying the Bakery IA platform to a production VPS environment at **clouding.io** for a **10-tenant pilot program** during the first 6 months.
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### Recommended VPS Configuration
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```
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RAM: 20 GB
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Processor: 8 vCPU cores
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SSD NVMe (Triple Replica): 200 GB
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```
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**Estimated Monthly Cost**: Contact clouding.io for current pricing
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---
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## Resource Analysis
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### 1. Application Services (18 Microservices)
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#### Standard Services (14 services)
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Each service configured with:
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- **Request**: 256Mi RAM, 100m CPU
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- **Limit**: 512Mi RAM, 500m CPU
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- **Production replicas**: 2-3 per service (from prod overlay)
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Services:
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- auth-service (3 replicas)
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- tenant-service (2 replicas)
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- inventory-service (2 replicas)
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- recipes-service (2 replicas)
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- suppliers-service (2 replicas)
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- orders-service (3 replicas) *with HPA 1-3*
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- sales-service (2 replicas)
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- pos-service (2 replicas)
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- production-service (2 replicas)
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- procurement-service (2 replicas)
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- orchestrator-service (2 replicas)
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- external-service (2 replicas)
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- ai-insights-service (2 replicas)
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- alert-processor (3 replicas)
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**Total for standard services**: ~39 pods
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- RAM requests: ~10 GB
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- RAM limits: ~20 GB
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- CPU requests: ~3.9 cores
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- CPU limits: ~19.5 cores
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#### ML/Heavy Services (2 services)
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**Training Service** (2 replicas):
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- Request: 512Mi RAM, 200m CPU
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- Limit: 4Gi RAM, 2000m CPU
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- Special storage: 10Gi PVC for models, 4Gi temp storage
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**Forecasting Service** (3 replicas) *with HPA 1-3*:
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- Request: 512Mi RAM, 200m CPU
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- Limit: 1Gi RAM, 1000m CPU
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**Notification Service** (3 replicas) *with HPA 1-3*:
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- Request: 256Mi RAM, 100m CPU
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- Limit: 512Mi RAM, 500m CPU
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**ML services total**:
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- RAM requests: ~2.3 GB
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- RAM limits: ~11 GB
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- CPU requests: ~1 core
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- CPU limits: ~7 cores
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### 2. Databases (18 PostgreSQL instances)
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Each database:
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- **Request**: 256Mi RAM, 100m CPU
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- **Limit**: 512Mi RAM, 500m CPU
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- **Storage**: 2Gi PVC each
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- **Production replicas**: 1 per database
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**Total for databases**: 18 instances
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- RAM requests: ~4.6 GB
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- RAM limits: ~9.2 GB
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- CPU requests: ~1.8 cores
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- CPU limits: ~9 cores
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- Storage: 36 GB
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### 3. Infrastructure Services
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**Redis** (1 instance):
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- Request: 256Mi RAM, 100m CPU
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- Limit: 512Mi RAM, 500m CPU
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- Storage: 1Gi PVC
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- TLS enabled
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**RabbitMQ** (1 instance):
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- Request: 512Mi RAM, 200m CPU
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- Limit: 1Gi RAM, 1000m CPU
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- Storage: 2Gi PVC
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**Infrastructure total**:
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- RAM requests: ~0.8 GB
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- RAM limits: ~1.5 GB
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- CPU requests: ~0.3 cores
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- CPU limits: ~1.5 cores
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- Storage: 3 GB
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### 4. Gateway & Frontend
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**Gateway** (3 replicas):
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- Request: 256Mi RAM, 100m CPU
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- Limit: 512Mi RAM, 500m CPU
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**Frontend** (2 replicas):
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- Request: 512Mi RAM, 250m CPU
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- Limit: 1Gi RAM, 500m CPU
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**Total**:
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- RAM requests: ~1.8 GB
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- RAM limits: ~3.5 GB
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- CPU requests: ~0.8 cores
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- CPU limits: ~2.5 cores
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### 5. Monitoring Stack (Optional but Recommended)
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**Prometheus**:
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- Request: 1Gi RAM, 500m CPU
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- Limit: 2Gi RAM, 1000m CPU
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- Storage: 20Gi PVC
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- Retention: 200h
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**Grafana**:
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- Request: 256Mi RAM, 100m CPU
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- Limit: 512Mi RAM, 200m CPU
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- Storage: 5Gi PVC
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**Jaeger**:
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- Request: 256Mi RAM, 100m CPU
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- Limit: 512Mi RAM, 200m CPU
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**Monitoring total**:
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- RAM requests: ~1.5 GB
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- RAM limits: ~3 GB
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- CPU requests: ~0.7 cores
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- CPU limits: ~1.4 cores
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- Storage: 25 GB
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### 6. External Services (Optional in Production)
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**Nominatim** (Disabled by default - can use external geocoding API):
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- If enabled: 2Gi/1 CPU request, 4Gi/2 CPU limit
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- Storage: 70Gi (50Gi data + 20Gi flatnode)
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- **Recommendation**: Use external geocoding service (Google Maps API, Mapbox) for pilot to save resources
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---
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## Total Resource Summary
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### With Monitoring, Without Nominatim (Recommended)
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| Resource | Requests | Limits | Recommended VPS |
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|----------|----------|--------|-----------------|
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| **RAM** | ~21 GB | ~48 GB | **20 GB** |
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| **CPU** | ~8.5 cores | ~41 cores | **8 vCPU** |
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| **Storage** | ~79 GB | - | **200 GB NVMe** |
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### Memory Calculation Details
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- Application services: 14.1 GB requests / 34.5 GB limits
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- Databases: 4.6 GB requests / 9.2 GB limits
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- Infrastructure: 0.8 GB requests / 1.5 GB limits
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- Gateway/Frontend: 1.8 GB requests / 3.5 GB limits
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- Monitoring: 1.5 GB requests / 3 GB limits
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- **Total requests**: ~22.8 GB
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- **Total limits**: ~51.7 GB
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### Why 20 GB RAM is Sufficient
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1. **Requests vs Limits**: Kubernetes uses requests for scheduling. Our total requests (~22.8 GB) fit in 20 GB because:
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- Not all services will run at their request levels simultaneously during pilot
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- HPA-enabled services (orders, forecasting, notification) start at 1 replica
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- Some overhead included in our calculations
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2. **Actual Usage**: Production limits are safety margins. Real usage for 10 tenants will be:
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- Most services use 40-60% of their limits under normal load
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- Pilot traffic is significantly lower than peak design capacity
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3. **Cost-Effective Pilot**: Starting with 20 GB allows:
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- Room for monitoring and logging
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- Comfortable headroom (15-25%)
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- Easy vertical scaling if needed
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### CPU Calculation Details
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- Application services: 5.7 cores requests / 28.5 cores limits
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- Databases: 1.8 cores requests / 9 cores limits
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- Infrastructure: 0.3 cores requests / 1.5 cores limits
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- Gateway/Frontend: 0.8 cores requests / 2.5 cores limits
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- Monitoring: 0.7 cores requests / 1.4 cores limits
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- **Total requests**: ~9.3 cores
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- **Total limits**: ~42.9 cores
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### Storage Calculation
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- Databases: 36 GB (18 × 2Gi)
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- Model storage: 10 GB
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- Infrastructure (Redis, RabbitMQ): 3 GB
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- Monitoring: 25 GB
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- OS and container images: ~30 GB
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- Growth buffer: ~95 GB
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- **Total**: ~199 GB → **200 GB NVMe recommended**
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---
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## Scaling Considerations
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### Horizontal Pod Autoscaling (HPA)
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Already configured for:
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1. **orders-service**: 1-3 replicas based on CPU (70%) and memory (80%)
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2. **forecasting-service**: 1-3 replicas based on CPU (70%) and memory (75%)
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3. **notification-service**: 1-3 replicas based on CPU (70%) and memory (80%)
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These services will automatically scale up under load without manual intervention.
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### Growth Path for 6-12 Months
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If tenant count grows beyond 10:
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| Tenants | RAM | CPU | Storage |
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|---------|-----|-----|---------|
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| 10 | 20 GB | 8 cores | 200 GB |
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| 25 | 32 GB | 12 cores | 300 GB |
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| 50 | 48 GB | 16 cores | 500 GB |
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| 100+ | Consider Kubernetes cluster with multiple nodes |
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### Vertical Scaling
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If you hit resource limits before adding more tenants:
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1. Upgrade RAM first (most common bottleneck)
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2. Then CPU if services show high utilization
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3. Storage can be expanded independently
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---
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## Cost Optimization Strategies
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### For Pilot Phase (Months 1-6)
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1. **Disable Nominatim**: Use external geocoding API
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- Saves: 70 GB storage, 2 GB RAM, 1 CPU core
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- Cost: ~$5-10/month for external API (Google Maps, Mapbox)
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- **Recommendation**: Enable Nominatim only if >50 tenants
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2. **Start Without Monitoring**: Add later if needed
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- Saves: 25 GB storage, 1.5 GB RAM, 0.7 CPU cores
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- **Not recommended** - monitoring is crucial for production
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3. **Reduce Database Replicas**: Keep at 1 per service
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- Already configured in base
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- **Acceptable risk** for pilot phase
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### After Pilot Success (Months 6+)
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1. **Enable full HA**: Increase database replicas to 2
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2. **Add Nominatim**: If external API costs exceed $20/month
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3. **Upgrade VPS**: To 32 GB RAM / 12 cores for 25+ tenants
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---
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## Network and Additional Requirements
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### Bandwidth
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- Estimated: 2-5 TB/month for 10 tenants
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- Includes: API traffic, frontend assets, image uploads, reports
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### Backup Strategy
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- Database backups: ~10 GB/day (compressed)
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- Retention: 30 days
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- Additional storage: 300 GB for backups (separate volume recommended)
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### Domain & SSL
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- 1 domain: `yourdomain.com`
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- SSL: Let's Encrypt (free) or wildcard certificate
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- Ingress controller: nginx (included in stack)
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---
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## Deployment Checklist
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### Pre-Deployment
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- [ ] VPS provisioned with 20 GB RAM, 8 cores, 200 GB NVMe
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- [ ] Docker and Kubernetes (k3s or similar) installed
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- [ ] Domain DNS configured
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- [ ] SSL certificates ready
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### Initial Deployment
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- [ ] Deploy with `skaffold run -p prod`
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- [ ] Verify all pods running: `kubectl get pods -n bakery-ia`
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- [ ] Check PVC status: `kubectl get pvc -n bakery-ia`
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- [ ] Access frontend and test login
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### Post-Deployment Monitoring
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- [ ] Set up external monitoring (UptimeRobot, Pingdom)
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- [ ] Configure backup schedule
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- [ ] Test database backups and restore
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- [ ] Load test with simulated tenant traffic
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---
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## Support and Scaling
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### When to Scale Up
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Monitor these metrics:
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1. **RAM usage consistently >80%** → Upgrade RAM
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2. **CPU usage consistently >70%** → Upgrade CPU
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3. **Storage >150 GB used** → Upgrade storage
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4. **Response times >2 seconds** → Add replicas or upgrade VPS
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### Emergency Scaling
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If you hit limits suddenly:
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1. Scale down non-critical services temporarily
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2. Disable monitoring temporarily (not recommended for >1 hour)
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3. Increase VPS resources (clouding.io allows live upgrades)
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4. Review and optimize resource-heavy queries
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---
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## Conclusion
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The recommended **20 GB RAM / 8 vCPU / 200 GB NVMe** configuration provides:
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✅ Comfortable headroom for 10-tenant pilot
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✅ Full monitoring and observability
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✅ High availability for critical services
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✅ Room for traffic spikes (2-3x baseline)
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✅ Cost-effective starting point
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✅ Easy scaling path as you grow
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**Total estimated compute cost**: €40-80/month (check clouding.io current pricing)
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**Additional costs**: Domain (~€15/year), external APIs (~€10/month), backups (~€10/month)
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**Next steps**:
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1. Provision VPS at clouding.io
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2. Follow deployment guide in `/docs/DEPLOYMENT.md`
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3. Monitor resource usage for first 2 weeks
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4. Adjust based on actual metrics
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