Mathias STRASSER
b7dc27f2a5
Les enseignants ont besoin de moyennes à jour immédiatement après la publication ou modification des notes, sans attendre un batch nocturne. Le système recalcule via Domain Events synchrones : statistiques d'évaluation (min/max/moyenne/médiane), moyennes matières pondérées (normalisation /20), et moyenne générale par élève. Les résultats sont stockés dans des tables dénormalisées avec cache Redis (TTL 5 min). Trois endpoints API exposent les données avec contrôle d'accès par rôle. Une commande console permet le backfill des données historiques au déploiement.
2.0 KiB
2.0 KiB
name, description, subagent, outputFile
| name | description | subagent | outputFile |
|---|---|---|---|
| step-04d-subagent-scalability | Subagent: Scalability NFR assessment | true | /tmp/tea-nfr-scalability-{{timestamp}}.json |
Subagent 4D: Scalability NFR Assessment
SUBAGENT CONTEXT
This is an isolated subagent running in parallel with other NFR domain assessments.
Your task: Assess SCALABILITY NFR domain only.
SUBAGENT TASK
1. Scalability Assessment Categories
A) Horizontal Scaling:
- Stateless architecture
- Load balancer configuration
- Container orchestration (K8s)
- Auto-scaling policies
B) Vertical Scaling:
- Resource allocation
- Database size limits
- Memory management
- CPU optimization
C) Data Scaling:
- Database partitioning/sharding
- Read replicas
- Caching layers
- Data archival strategy
D) Traffic Handling:
- CDN for static assets
- Rate limiting
- Queue systems for async work
- WebSocket scaling
OUTPUT FORMAT
{
"domain": "scalability",
"risk_level": "MEDIUM",
"findings": [
{
"category": "Horizontal Scaling",
"status": "PASS",
"description": "Stateless architecture with container orchestration",
"evidence": ["Docker + Kubernetes setup", "Auto-scaling configured"],
"recommendations": []
},
{
"category": "Data Scaling",
"status": "CONCERN",
"description": "No database sharding strategy for large data growth",
"evidence": ["Single database instance", "No partitioning"],
"recommendations": ["Plan database sharding strategy", "Implement read replicas", "Consider database clustering"]
}
],
"compliance": {
"1M_users": "PASS",
"10M_users": "CONCERN",
"100M_users": "FAIL"
},
"priority_actions": ["Design database sharding strategy for future growth", "Implement read replicas for read-heavy workloads"],
"summary": "Scalability is good up to 1M users, concerns for 10M+ users"
}
EXIT CONDITION
Subagent completes when JSON output written to temp file.