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/cost-optimization-patterns

Cloud cost optimization, token/API cost tracking, build time optimization, and FinOps patterns

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vibecosystem
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$ npx -y skills add vibeeval/vibecosystem --skill cost-optimization-patterns --agent claude-code

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  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/cost-optimization-patterns

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Cloud cost optimization, token/API cost tracking, build time optimization, and FinOps patterns

SKILL.md

cost-optimization-patterns.SKILL.md
name: cost-optimization-patterns
description: Cloud cost optimization, token/API cost tracking, build time optimization, and FinOps patterns

Cost Optimization Patterns

Cloud Cost Optimization

Right-Sizing

# AWS - Compute Optimizer önerileri
aws compute-optimizer get-ec2-instance-recommendations

# CPU/Memory utilization < 20% → downsize
# CPU/Memory utilization > 80% → upsize veya auto-scale

Instance Strategy

| Strateji | Tasarruf | Risk | Use Case | |----------|---------|------|----------| | On-Demand | 0% | Düşük | Değişken workload | | Reserved (1yr) | %30-40 | Orta | Steady-state | | Reserved (3yr) | %50-60 | Yüksek | Uzun vadeli | | Spot/Preemptible | %60-90 | Yüksek | Batch, CI/CD | | Savings Plans | %30-50 | Düşük | Flexible commitment |

Serverless Cost

Lambda cost = (requests × $0.20/1M) + (GB-seconds × $0.0000166)

Optimizasyon:
1. Memory right-sizing (power tuning)
2. Provisioned concurrency (cold start vs cost tradeoff)
3. ARM architecture (%20 ucuz)
4. Batch processing (SQS batch size)

LLM/API Token Cost

// Token maliyet takibi
const MODEL_COSTS = {
  'claude-opus-4-6':   { input: 15.0, output: 75.0 },   // per 1M tokens
  'claude-sonnet-4-6': { input: 3.0,  output: 15.0 },
  'claude-haiku-4-5':  { input: 0.80, output: 4.0 }
} as const

function estimateCost(model: string, inputTokens: number, outputTokens: number) {
  const costs = MODEL_COSTS[model]
  return (inputTokens * costs.input + outputTokens * costs.output) / 1_000_000
}

Build Time Optimization

| Teknik | Tasarruf | Karmaşıklık | |--------|---------|-------------| | Dependency caching | %30-50 | Düşük | | Parallel test execution | %40-60 | Düşük | | Incremental builds | %50-70 | Orta | | Docker layer caching | %20-40 | Düşük | | Affected-only (monorepo) | %60-80 | Orta |

Database Cost

-- Pahalı query'leri bul
SELECT query, calls, mean_exec_time, total_exec_time
FROM pg_stat_statements
ORDER BY total_exec_time DESC
LIMIT 20;

-- Unused index'leri bul (gereksiz storage + write overhead)
SELECT indexrelname, idx_scan
FROM pg_stat_user_indexes
WHERE idx_scan = 0 AND indexrelname NOT LIKE '%pkey%';

Checklist

  • [ ] Cloud cost alerting aktif (budget alarm)
  • [ ] Unused resources temizlenmiş
  • [ ] Right-sizing review (aylık)
  • [ ] Reserved/Spot instance kullanımı
  • [ ] CDN cache hit ratio >90%
  • [ ] Database query optimization
  • [ ] Build cache aktif
  • [ ] Tag-based cost allocation

Anti-Patterns

  • Over-provisioned "just in case" resources
  • Unused EBS volumes, idle load balancers
  • Data transfer between regions (pahalı)
  • CloudWatch log retention unlimited
  • Her environment production-grade
Read more
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