name: ‘step-04d-subagent-scalability’ description: ‘Subagent: Scalability NFR evidence audit’ subagent: true

outputFile: ‘/tmp/tea-nfr-scalability-{{timestamp}}.json’

Subagent 4D: Scalability NFR Evidence Audit

SUBAGENT CONTEXT

This is an isolated subagent running in parallel with other NFR domain evidence audits.

Your task: Assess SCALABILITY NFR domain only.

SUBAGENT TASK

1. Scalability Evidence Audit 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.

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