Initial commit: 2125_NBB project
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Executable
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# GlyphOS Infrastructure Plan
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## Executive Summary
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Proposing a production-grade infrastructure for the 600-glyph monument system. Current prototype (Rust/Axum + JSON files) needs database, auth, observability, and deployment pipeline.
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---
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## 1. Data Layer
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### Current State
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- JSON files in `glyphs/*.json`
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- Meta-glyph archive: `glyph-complete-600.json` (not yet present)
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- In-memory `HashMap` with RwLock
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### Proposed Infrastructure
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```
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┌─────────────────────────────────────────────────────────┐
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│ Data Layer │
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├─────────────────────────────────────────────────────────┤
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│ Primary DB: PostgreSQL 16 │
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│ - glyphs table (600 rows, canonical + semantic) │
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│ - meta_glyphs table (600 rows, full JSONB archive) │
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│ - lineage table (60 lineages, 6 super-families) │
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│ - hash_index table (FNV-1a → glyph_id mapping) │
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│ │
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│ Cache: Redis │
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│ - LRU cache for hot glyphs (TTL: 5min) │
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│ - Search index cache (TTL: 1min) │
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│ - Session/rate-limit counters │
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│ │
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│ Search: Meilisearch (or Elasticsearch) │
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│ - Full-text search across name, meaning, tags │
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│ - Fuzzy matching, typo tolerance │
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│ - Lineage/band/period filtering │
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└─────────────────────────────────────────────────────────┘
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```
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**Why PostgreSQL?**
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- JSONB for meta-glyph archive (flexible schema)
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- ACID compliance for glyph uploads
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- Row-level locking (better than RwLock contention)
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---
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## 2. API Layer Enhancements
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### Current Endpoints (12 total)
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- Health, sample, list, get-by-id, search, reload, stats, upload
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- Meta-glyph: list, get, search, project
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### Proposed Additions
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| Endpoint | Method | Purpose |
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|----------|--------|---------|
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| `/glyph/{id}/resonance` | GET | Compute resonance with other glyphs |
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| `/glyph/batch` | POST | Bulk upload (10-100 glyphs) |
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| `/lineage/{id}` | GET | Get all glyphs in lineage |
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| `/lineage/{id}/activate` | POST | Activate entire lineage cluster |
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| `/meta-glyph/{id}/diff` | GET | Compare meta vs projected |
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| `/admin/backup` | POST | Trigger DB backup |
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| `/admin/restore` | POST | Restore from backup |
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### Authentication Middleware
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```rust
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// Proposed auth flow
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1. API key in `X-API-Key` header
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2. Rate limiting: 100 req/min per key
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3. Upload endpoints require admin scope
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4. JWT for user sessions (optional)
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```
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---
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## 3. Infrastructure Diagram
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```
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┌───────────────┐
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│ Cloudflare │
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│ (CDN + SSL) │
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└───────┬───────┘
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│
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┌───────▼───────┐
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│ Kong/API │
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│ Gateway │
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│ (Auth + RL) │
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└───────┬───────┘
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│
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┌───────────────┼───────────────┐
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│ │ │
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┌───────▼───────┐ ┌────▼─────┐ ┌──────▼──────┐
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│ Glyph API │ │ Monitor │ │ Backup │
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│ (Rust/Axum) │ │ Service │ │ Service │
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│ Port 3000 │ │ (Prometheus)│ │ (Scheduled) │
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└───────┬───────┘ └───────────┘ └──────────────┘
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│
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┌───────┴───────┐
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│ PostgreSQL │
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│ + Redis │
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│ + Meilisearch│
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└───────────────┘
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```
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---
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## 4. Deployment Architecture
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### Containerization
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```dockerfile
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# Multi-stage build
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FROM rust:1.80 AS builder
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WORKDIR /app
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COPY . .
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RUN cargo build --release
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FROM debian:12-slim
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RUN apt-get update && apt-get install -y ca-certificates
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COPY --from=builder /app/target/release/glyph_backend /usr/local/bin
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EXPOSE 3000
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CMD ["glyph_backend"]
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```
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### Orchestration (Kubernetes)
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```yaml
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# Deployment
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replicas: 3
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resources:
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requests: { cpu: "500m", memory: "512Mi" }
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limits: { cpu: "2", memory: "2Gi" }
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# HPA (Horizontal Pod Autoscaler)
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minReplicas: 3
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maxReplicas: 10
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targetCPUUtilization: 70%
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# Pod Disruption Budget
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minAvailable: 2
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```
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### CI/CD Pipeline
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```
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GitHub → Actions → Build → Test → Docker → Deploy
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├─ cargo test
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├─ cargo clippy
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├─ cargo fmt --check
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├─ Integration tests (glyph upload/search)
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└─ Security scan (cargo audit)
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```
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---
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## 5. Observability Stack
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### Metrics (Prometheus + Grafana)
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- Request rate per endpoint
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- Response latency (p50, p95, p99)
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- Glyph cache hit rate
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- DB connection pool usage
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- Error rate by endpoint
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### Logging (Loki or ELK)
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- Structured JSON logs
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- Correlation IDs per request
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- Glyph upload/change audit trail
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### Tracing (OpenTelemetry)
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- Request flow: Gateway → API → DB → Cache
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- Slow query detection
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- Cross-service latency breakdown
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---
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## 6. Backup & Recovery
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### Strategy
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| Type | Frequency | Retention | Storage |
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|------|-----------|-----------|---------|
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| DB Snapshot | Hourly | 7 days | S3/GCS |
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| DB Backup | Daily | 30 days | S3 + Glacier |
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| Glyph JSON Export | Weekly | 90 days | S3 |
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| Meta-glyph Archive | On-change | Permanent | S3 + Versioning |
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### Recovery RTO/RPO
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- **RTO (Recovery Time Objective):** < 1 hour
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- **RPO (Recovery Point Objective):** < 5 minutes
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---
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## 7. Security Hardening
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### Input Validation
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- Glyph JSON schema validation (serde validator)
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- Max payload size: 1MB per glyph
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- Rate limiting: 100 req/min per API key
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### Network Security
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- TLS 1.3 only (Cloudflare)
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- API Gateway (Kong) for auth/rate-limiting
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- Private DB network (no public access)
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### Audit Logging
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- All `/glyph/upload` requests logged
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- User/IP/timestamp in audit table
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- Immutable log storage (WORM)
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---
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## 8. Scaling Strategy
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### Horizontal Scaling
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- Stateless API pods (scale to 10 replicas)
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- DB read replicas for search queries
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- Redis cluster for cache
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### Vertical Scaling
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- Current: 2 CPU / 2GiB per pod
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- Max: 4 CPU / 8GiB per pod (before horizontal)
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### Glyph Count Scaling
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- 600 glyphs: Current architecture fine
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- 6,000 glyphs: Add read replicas, increase cache
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- 60,000 glyphs: Sharding by lineage ID
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---
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## 9. Cost Estimate (Monthly)
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| Component | Provider | Cost |
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|-----------|----------|------|
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| Compute (3 pods) | AWS EKS | $150 |
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| PostgreSQL (managed) | AWS RDS | $100 |
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| Redis (managed) | AWS ElastiCache | $50 |
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| Search (Meilisearch) | Self-hosted | $0 |
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| Storage (S3) | AWS S3 | $20 |
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| CDN + SSL | Cloudflare | $0 (free tier) |
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| **Total** | | **~$320/mo** |
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---
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## 10. Implementation Phases
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### Phase 1: Foundation (Week 1-2)
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- [ ] PostgreSQL schema design + migration
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- [ ] Replace JSON loader with DB loader
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- [ ] Add Redis cache layer
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- [ ] Basic auth middleware
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### Phase 2: Observability (Week 3)
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- [ ] Prometheus metrics export
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- [ ] Structured logging
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- [ ] Grafana dashboards
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### Phase 3: Hardening (Week 4)
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- [ ] Rate limiting
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- [ ] Input validation
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- [ ] Audit logging
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- [ ] Backup automation
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### Phase 4: Deployment (Week 5)
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- [ ] Docker containerization
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- [ ] Kubernetes manifests
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- [ ] CI/CD pipeline
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- [ ] Load testing
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---
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## Tradeoffs & Questions
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### Tradeoffs
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1. **PostgreSQL vs SQLite** - PostgreSQL adds complexity but scales better. SQLite simpler for <10k glyphs.
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2. **Meilisearch vs Postgres FTS** - Meilisearch better UX, but adds infra. Postgres FTS sufficient for 600 glyphs.
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3. **Kubernetes vs Docker Compose** - K8s overkill for single server. Compose simpler for MVP.
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### Questions for You
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1. **Expected glyph count growth?** (600 → 6,000 or stay at 600?)
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2. **Concurrent user load?** (10 users or 10,000?)
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3. **Budget constraints?** (Self-hosted vs managed services)
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4. **Deployment preference?** (Single server, K8s, or serverless?)
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5. **Auth requirements?** (API keys, OAuth, or open?)
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---
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## Recommendation for MVP
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For 600 glyphs with moderate traffic:
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```
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┌─────────────────────┐
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│ Single EC2/Docker │
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│ - Rust API │
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│ - PostgreSQL │
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│ - Redis (optional) │
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│ - Daily S3 backup │
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└─────────────────────┘
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Cost: ~$50/mo
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```
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Scale to full infrastructure when:
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- Glyph count > 5,000
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- Concurrent users > 100
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- Upload frequency > 10/day
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---
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**Ready to proceed with implementation?** I can start with Phase 1 (DB schema + migration) once you confirm the direction.
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