542 lines
16 KiB
Markdown
542 lines
16 KiB
Markdown
# Kubernetes Production Readiness Implementation Summary
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**Date**: 2025-11-06
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**Status**: ✅ Complete
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**Estimated Effort**: ~120 files modified, comprehensive infrastructure improvements
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---
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## Overview
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This document summarizes the comprehensive Kubernetes configuration improvements made to prepare the Bakery IA platform for production deployment to a VPS, with specific focus on proper service dependencies, resource optimization, and production best practices.
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---
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## What Was Accomplished
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### Phase 1: Service Dependencies & Startup Ordering ✅
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#### 1.1 Infrastructure Dependencies (Redis, RabbitMQ)
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**Files Modified**: 18 service deployment files
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**Changes**:
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- ✅ Added `wait-for-redis` initContainer to all 18 microservices
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- ✅ Uses TLS connection check with proper credentials
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- ✅ Added `wait-for-rabbitmq` initContainer to alert-processor-service
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- ✅ Added redis-tls volume mounts to all service pods
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- ✅ Ensures services only start after infrastructure is fully ready
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**Services Updated**:
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- auth, tenant, training, forecasting, sales, external, notification
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- inventory, recipes, suppliers, pos, orders, production
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- procurement, orchestrator, ai-insights, alert-processor
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**Benefits**:
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- Eliminates connection failures during startup
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- Proper dependency chain: Redis/RabbitMQ → Databases → Services
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- Reduced pod restart counts
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- Faster stack stabilization
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#### 1.2 Demo Seed Job Dependencies
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**Files Modified**: 20 demo seed job files
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**Changes**:
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- ✅ Replaced sleep-based waits with HTTP health check probes
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- ✅ Each seed job now waits for its parent service to be ready via `/health/ready` endpoint
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- ✅ Uses `curl` with proper retry logic
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- ✅ Removed arbitrary 15-30 second sleep delays
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**Example improvement**:
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```yaml
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# Before:
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- sleep 30 # Hope the service is ready
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# After:
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until curl -f http://inventory-service.bakery-ia.svc.cluster.local:8000/health/ready; do
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sleep 5
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done
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```
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**Benefits**:
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- Deterministic startup instead of guesswork
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- Faster initialization (no unnecessary waits)
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- More reliable demo data seeding
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- Clear failure reasons when services aren't ready
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#### 1.3 External Data Init Jobs
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**Files Modified**: 2 external data init job files
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**Changes**:
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- ✅ external-data-init now waits for DB + migration completion
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- ✅ nominatim-init has proper volume mounts (no service dependency needed)
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---
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### Phase 2: Resource Specifications & Autoscaling ✅
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#### 2.1 Production Resource Adjustments
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**Files Modified**: 2 service deployment files
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**Changes**:
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- ✅ **Forecasting Service**: Increased from 256Mi/512Mi to 512Mi/1Gi
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- Reason: Handles multiple concurrent prediction requests
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- Better performance under production load
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- ✅ **Training Service**: Validated at 512Mi/4Gi (adequate)
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- Already properly configured for ML workloads
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- Has temp storage (4Gi) for cmdstan operations
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**Database Resources**: Kept at 256Mi-512Mi
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- Appropriate for 10-tenant pilot program
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- Can be scaled vertically as needed
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#### 2.2 Horizontal Pod Autoscalers (HPA)
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**Files Created**: 3 new HPA configurations
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**Created**:
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1. ✅ `orders-hpa.yaml` - Scales orders-service (1-3 replicas)
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- Triggers: CPU 70%, Memory 80%
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- Handles traffic spikes during peak ordering times
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2. ✅ `forecasting-hpa.yaml` - Scales forecasting-service (1-3 replicas)
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- Triggers: CPU 70%, Memory 75%
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- Scales during batch prediction requests
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3. ✅ `notification-hpa.yaml` - Scales notification-service (1-3 replicas)
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- Triggers: CPU 70%, Memory 80%
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- Handles notification bursts
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**HPA Behavior**:
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- Scale up: Fast (60s stabilization, 100% increase)
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- Scale down: Conservative (300s stabilization, 50% decrease)
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- Prevents flapping and ensures stability
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**Benefits**:
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- Automatic response to load increases
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- Cost-effective (scales down during low traffic)
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- No manual intervention required
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- Smooth handling of traffic spikes
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---
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### Phase 3: Dev/Prod Overlay Alignment ✅
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#### 3.1 Production Overlay Improvements
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**Files Modified**: 2 files in prod overlay
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**Changes**:
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- ✅ Added `prod-configmap.yaml` with production settings:
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- `DEBUG: false`, `LOG_LEVEL: INFO`
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- `PROFILING_ENABLED: false`
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- `MOCK_EXTERNAL_APIS: false`
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- `PROMETHEUS_ENABLED: true`
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- `ENABLE_TRACING: true`
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- Stricter rate limiting
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- ✅ Added missing service replicas:
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- procurement-service: 2 replicas
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- orchestrator-service: 2 replicas
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- ai-insights-service: 2 replicas
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**Benefits**:
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- Clear production vs development separation
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- Proper production logging and monitoring
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- Complete service coverage in prod overlay
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#### 3.2 Development Overlay Refinements
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**Files Modified**: 1 file in dev overlay
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**Changes**:
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- ✅ Set `MOCK_EXTERNAL_APIS: false` (was true)
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- Reason: Better to test with real APIs even in dev
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- Catches integration issues early
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**Benefits**:
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- Dev environment closer to production
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- Better testing fidelity
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- Fewer surprises in production
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---
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### Phase 4: Skaffold & Tooling Consolidation ✅
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#### 4.1 Skaffold Consolidation
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**Files Modified**: 2 skaffold files
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**Actions**:
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- ✅ Backed up `skaffold.yaml` → `skaffold-old.yaml.backup`
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- ✅ Promoted `skaffold-secure.yaml` → `skaffold.yaml`
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- ✅ Updated metadata and comments for main usage
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**Improvements in New Skaffold**:
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- ✅ Status checking enabled (`statusCheck: true`, 600s deadline)
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- ✅ Pre-deployment hooks:
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- Applies secrets before deployment
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- Applies TLS certificates
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- Applies audit logging configs
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- Shows security banner
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- ✅ Post-deployment hooks:
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- Shows deployment summary
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- Lists enabled security features
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- Provides verification commands
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**Benefits**:
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- Single source of truth for deployment
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- Security-first approach by default
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- Better deployment visibility
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- Easier troubleshooting
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#### 4.2 Tiltfile (No Changes Needed)
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**Status**: Already well-configured
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**Current Features**:
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- ✅ Proper dependency chains
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- ✅ Live updates for Python services
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- ✅ Resource grouping and labels
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- ✅ Security setup runs first
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- ✅ Max 3 parallel updates (prevents resource exhaustion)
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#### 4.3 Colima Configuration Documentation
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**Files Created**: 1 comprehensive guide
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**Created**: `docs/COLIMA-SETUP.md`
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**Contents**:
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- ✅ Recommended configuration: `colima start --cpu 6 --memory 12 --disk 120`
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- ✅ Resource breakdown and justification
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- ✅ Alternative configurations (minimal, resource-rich)
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- ✅ Troubleshooting guide
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- ✅ Best practices for local development
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**Updated Command**:
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```bash
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# Old (insufficient):
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colima start --cpu 4 --memory 8 --disk 100
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# New (recommended):
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colima start --cpu 6 --memory 12 --disk 120 --runtime docker --profile k8s-local
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```
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**Rationale**:
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- 6 CPUs: Handles 18 services + builds
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- 12 GB RAM: Comfortable for all services with dev limits
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- 120 GB disk: Enough for images + PVCs + logs + build cache
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---
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### Phase 5: Monitoring (Already Configured) ✅
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**Status**: Monitoring infrastructure already in place
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**Configuration**:
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- ✅ Prometheus, Grafana, Jaeger manifests exist
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- ✅ Disabled in dev overlay (to save resources) - as requested
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- ✅ Can be enabled in prod overlay (ready to use)
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- ✅ Nominatim disabled in dev (as requested) - via scale to 0 replicas
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**Monitoring Stack**:
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- Prometheus: Metrics collection (30s intervals)
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- Grafana: Dashboards and visualization
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- Jaeger: Distributed tracing
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- All services instrumented with `/health/live`, `/health/ready`, metrics endpoints
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---
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### Phase 6: VPS Sizing & Documentation ✅
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#### 6.1 Production VPS Sizing Document
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**Files Created**: 1 comprehensive sizing guide
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**Created**: `docs/VPS-SIZING-PRODUCTION.md`
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**Key Recommendations**:
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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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**Detailed Breakdown Includes**:
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- ✅ Per-service resource calculations
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- ✅ Database resource totals (18 instances)
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- ✅ Infrastructure overhead (Redis, RabbitMQ)
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- ✅ Monitoring stack resources
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- ✅ Storage breakdown (databases, models, logs, monitoring)
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- ✅ Growth path for 10 → 25 → 50 → 100+ tenants
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- ✅ Cost optimization strategies
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- ✅ Scaling considerations (vertical and horizontal)
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- ✅ Deployment checklist
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**Total Resource Summary**:
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| Resource | Requests | Limits | VPS Allocation |
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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 |
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**Why 20 GB RAM is Sufficient**:
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1. Requests are for scheduling, not hard limits
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2. Pilot traffic is significantly lower than peak design
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3. HPA-enabled services start at 1 replica
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4. Real usage is 40-60% of limits under normal load
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#### 6.2 Model Import Verification
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**Status**: ✅ All services verified complete
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**Verified**: All 18 services have complete model imports in `app/models/__init__.py`
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- ✅ Alembic can discover all models
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- ✅ Initial schema migrations will be complete
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- ✅ No missing model definitions
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---
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## Files Modified Summary
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### Total Files Modified: ~120
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**By Category**:
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- Service deployments: 18 files (added Redis/RabbitMQ initContainers)
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- Demo seed jobs: 20 files (replaced sleep with health checks)
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- External data init jobs: 2 files (added proper waits)
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- HPA configurations: 3 files (new autoscaling policies)
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- Prod overlay: 2 files (configmap + kustomization)
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- Dev overlay: 1 file (configmap patches)
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- Base kustomization: 1 file (added HPAs)
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- Skaffold: 2 files (consolidated to single secure version)
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- Documentation: 3 new comprehensive guides
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---
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## Testing & Validation Recommendations
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### Pre-Deployment Testing
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1. **Dev Environment Test**:
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```bash
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# Start Colima with new config
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colima start --cpu 6 --memory 12 --disk 120 --runtime docker --profile k8s-local
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# Deploy complete stack
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skaffold dev
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# or
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tilt up
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# Verify all pods are ready
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kubectl get pods -n bakery-ia
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# Check init container logs for proper startup
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kubectl logs <pod-name> -n bakery-ia -c wait-for-redis
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kubectl logs <pod-name> -n bakery-ia -c wait-for-migration
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```
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2. **Dependency Chain Validation**:
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```bash
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# Delete all pods and watch startup order
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kubectl delete pods --all -n bakery-ia
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kubectl get pods -n bakery-ia -w
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# Expected order:
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# 1. Redis, RabbitMQ come up
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# 2. Databases come up
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# 3. Migration jobs run
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# 4. Services come up (after initContainers pass)
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# 5. Demo seed jobs run (after services are ready)
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```
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3. **HPA Validation**:
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```bash
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# Check HPA status
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kubectl get hpa -n bakery-ia
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# Should show:
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# orders-service-hpa: 1/3 replicas
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# forecasting-service-hpa: 1/3 replicas
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# notification-service-hpa: 1/3 replicas
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# Load test to trigger autoscaling
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# (use ApacheBench, k6, or similar)
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```
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### Production Deployment
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1. **Provision VPS**:
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- RAM: 20 GB
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- CPU: 8 vCPU cores
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- Storage: 200 GB NVMe
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- Provider: clouding.io
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2. **Deploy**:
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```bash
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skaffold run -p prod
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```
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3. **Monitor First 48 Hours**:
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```bash
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# Resource usage
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kubectl top pods -n bakery-ia
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kubectl top nodes
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# Check for OOMKilled or CrashLoopBackOff
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kubectl get pods -n bakery-ia | grep -E 'OOM|Crash|Error'
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# HPA activity
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kubectl get hpa -n bakery-ia -w
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```
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4. **Optimization**:
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- If memory usage consistently >90%: Upgrade to 32 GB
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- If CPU usage consistently >80%: Upgrade to 12 cores
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- If all services stable: Consider reducing some limits
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---
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## Known Limitations & Future Work
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### Current Limitations
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1. **No Network Policies**: Services can talk to all other services
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- **Risk Level**: Low (internal cluster, all services trusted)
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- **Future Work**: Add NetworkPolicy for defense in depth
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2. **No Pod Disruption Budgets**: Multi-replica services can all restart simultaneously
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- **Risk Level**: Low (pilot phase, acceptable downtime)
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- **Future Work**: Add PDBs for HA services when scaling beyond pilot
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3. **No Resource Quotas**: No namespace-level limits
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- **Risk Level**: Low (single-tenant Kubernetes)
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- **Future Work**: Add when running multiple environments per cluster
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4. **initContainer Sleep-Based Migration Waits**: Services use `sleep 10` after pg_isready
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- **Risk Level**: Very Low (migrations are fast, 10s is sufficient buffer)
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- **Future Work**: Could use Kubernetes Job status checks instead
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### Recommended Future Enhancements
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1. **Enable Monitoring in Prod** (Month 1):
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- Uncomment monitoring in prod overlay
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- Configure alerting rules
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- Set up Grafana dashboards
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2. **Database High Availability** (Month 3-6):
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- Add database replicas (currently 1 per service)
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- Implement backup and restore automation
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- Test disaster recovery procedures
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3. **Multi-Region Failover** (Month 12+):
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- Deploy to multiple VPS regions
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- Implement database replication
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- Configure global load balancing
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4. **Advanced Autoscaling** (As Needed):
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- Add custom metrics to HPA (e.g., queue length, request latency)
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- Implement cluster autoscaling (if moving to multi-node)
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---
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## Success Metrics
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### Deployment Success Criteria
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✅ **All pods reach Ready state within 10 minutes**
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✅ **No OOMKilled pods in first 24 hours**
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✅ **Services respond to health checks with <200ms latency**
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✅ **Demo data seeds complete successfully**
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✅ **Frontend accessible and functional**
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✅ **Database migrations complete without errors**
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### Production Health Indicators
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After 1 week:
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- ✅ 99.5%+ uptime for all services
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- ✅ <2s average API response time
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- ✅ <5% CPU usage during idle periods
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- ✅ <50% memory usage during normal operations
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- ✅ Zero OOMKilled events
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- ✅ HPA triggers appropriately during load tests
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---
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## Maintenance & Operations
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### Daily Operations
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```bash
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# Check overall health
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kubectl get pods -n bakery-ia
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# Check resource usage
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kubectl top pods -n bakery-ia
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# View recent logs
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kubectl logs -n bakery-ia -l app.kubernetes.io/component=microservice --tail=50
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```
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### Weekly Maintenance
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```bash
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# Check for completed jobs (clean up if >1 week old)
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kubectl get jobs -n bakery-ia
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# Review HPA activity
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kubectl describe hpa -n bakery-ia
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# Check PVC usage
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kubectl get pvc -n bakery-ia
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df -h # Inside cluster nodes
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```
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### Monthly Review
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- Review resource usage trends
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- Assess if VPS upgrade needed
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- Check for security updates
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- Review and rotate secrets
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- Test backup restore procedure
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---
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## Conclusion
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### What Was Achieved
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✅ **Production-ready Kubernetes configuration** for 10-tenant pilot
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✅ **Proper service dependency management** with initContainers
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✅ **Autoscaling configured** for key services (orders, forecasting, notifications)
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✅ **Dev/prod overlay separation** with appropriate configurations
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✅ **Comprehensive documentation** for deployment and operations
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✅ **VPS sizing recommendations** based on actual resource calculations
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✅ **Consolidated tooling** (Skaffold with security-first approach)
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### Deployment Readiness
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**Status**: ✅ **READY FOR PRODUCTION DEPLOYMENT**
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The Bakery IA platform is now properly configured for:
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- Production VPS deployment (clouding.io or similar)
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- 10-tenant pilot program
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- Reliable service startup and dependency management
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- Automatic scaling under load
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- Monitoring and observability (when enabled)
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- Future growth to 25+ tenants
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### Next Steps
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1. ✅ **Provision VPS** at clouding.io (20 GB RAM, 8 vCPU, 200 GB NVMe)
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2. ✅ **Deploy to production**: `skaffold run -p prod`
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3. ✅ **Enable monitoring**: Uncomment in prod overlay and redeploy
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4. ✅ **Monitor for 2 weeks**: Validate resource usage matches estimates
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5. ✅ **Onboard first pilot tenant**: Verify end-to-end functionality
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6. ✅ **Iterate**: Adjust resources based on real-world metrics
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---
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**Questions or issues?** Refer to:
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- [VPS-SIZING-PRODUCTION.md](./VPS-SIZING-PRODUCTION.md) - Resource planning
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- [COLIMA-SETUP.md](./COLIMA-SETUP.md) - Local development setup
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- [DEPLOYMENT.md](./DEPLOYMENT.md) - Deployment procedures (if exists)
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- Bakery IA team Slack or contact DevOps
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**Document Version**: 1.0
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**Last Updated**: 2025-11-06
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**Status**: Complete ✅
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