continuous-cost-monitor

Continuous Cost Monitor Skill

Tracks actual infrastructure costs against estimated costs. Alerts when actual spend drifts from projection, identifies cost drivers, and suggests corrective actions.

When to Use

Use this skill to:

1. Detect cost creep — infrastructure spending slowly increases over time
2. Root-cause cost spikes — which service changed? traffic? resource use?
3. Compare actual vs. estimated — am I spending what I projected?
4. Trigger optimization cycles — when do I need to re-optimize?
5. Alert on budget overruns — notify team before exceeding budget

Input

Provide estimated costs + actual spend data:

{
  "estimated_monthly_cost": 8500,
  "actual_monthly_cost": 9200,
  "cost_breakdown_estimated": {
    "backend_compute": 1200,
    "database": 1800,
    "cache": 200,
    "cdn": 300,
    "monitoring": 300,
    "storage": 500,
    "other": 400
  },
  "cost_breakdown_actual": {
    "backend_compute": 1500,
    "database": 2100,
    "cache": 200,
    "cdn": 350,
    "monitoring": 400,
    "storage": 450,
    "other": 200
  },
  "traffic_metrics": {
    "dau_estimated": 100000,
    "dau_actual": 110000,
    "query_volume_estimated": 500000,
    "query_volume_actual": 650000
  },
  "measurement_period_days": 30,
  "budget_threshold": 9000
}

Output

A cost monitoring report:

{
  "period": "April 2026",
  "estimated_vs_actual": {
    "estimated": 8500,
    "actual": 9200,
    "variance": 700,
    "variance_percent": 8.2,
    "status": "YELLOW (over by $700)"
  },
  "cost_breakdown_analysis": {
    "backend_compute": {
      "estimated": 1200,
      "actual": 1500,
      "variance": 300,
      "variance_percent": 25,
      "driver": "Traffic 10% higher than expected (110k vs 100k DAU)"
    },
    "database": {
      "estimated": 1800,
      "actual": 2100,
      "variance": 300,
      "variance_percent": 16.7,
      "driver": "Query volume 30% higher (650k vs 500k queries). Likely N+1 queries or missing cache."
    },
    "cache": {
      "estimated": 200,
      "actual": 200,
      "variance": 0,
      "variance_percent": 0,
      "status": "On budget"
    },
    "cdn": {
      "estimated": 300,
      "actual": 350,
      "variance": 50,
      "variance_percent": 16.7,
      "driver": "Traffic 10% higher (correlates with DAU increase)"
    },
    "monitoring": {
      "estimated": 300,
      "actual": 400,
      "variance": 100,
      "variance_percent": 33,
      "driver": "Increased metric cardinality (added new dashboards or higher scrape frequency)"
    },
    "storage": {
      "estimated": 500,
      "actual": 450,
      "variance": -50,
      "variance_percent": -10,
      "status": "Better than expected"
    },
    "other": {
      "estimated": 400,
      "actual": 200,
      "variance": -200,
      "variance_percent": -50,
      "status": "Significantly better than expected"
    }
  },
  "root_cause_analysis": {
    "primary_driver": "Database query volume 30% higher than expected",
    "contributing_factors": [
      "Traffic 10% higher (110k vs 100k DAU) — accounts for ~$300",
      "Inefficient queries — N+1 patterns or missing caching — accounts for ~$200",
      "Monitoring cost creep — added dashboards — accounts for ~$100"
    ],
    "confidence": 0.85
  },
  "trend_analysis": {
    "month_1_actual": 8100,
    "month_2_actual": 8800,
    "month_3_actual": 9200,
    "trend": "Increasing",
    "monthly_growth": 5.5,
    "projected_next_month": 9700,
    "annualized_growth": 66
  },
  "alerts": [
    {
      "level": "YELLOW",
      "message": "Cost overrun: +$700 (+8.2%) vs. estimate",
      "action": "Review database query patterns and cache hit rates"
    },
    {
      "level": "ORANGE",
      "message": "Database costs growing (16.7% overrun). Query volume 30% higher.",
      "action": "Profile slow queries, implement caching, optimize N+1 patterns"
    },
    {
      "level": "ORANGE",
      "message": "Monitoring cost increasing (33% overrun). Cardinality growth?",
      "action": "Audit new metrics added. Disable unused dashboards."
    },
    {
      "level": "YELLOW",
      "message": "Cost trend: +5.5% per month. At this rate, exceed $10k budget in 2 months.",
      "action": "Run cost optimization (reduce scope or increase efficiency)"
    }
  ],
  "budget_status": {
    "budget": 9000,
    "actual": 9200,
    "over_budget": true,
    "headroom": -200,
    "trajectory": "Will exceed budget next month at current trend"
  },
  "recommendations": [
    {
      "action": "Optimize database queries",
      "potential_savings": 200,
      "effort": "Medium (1-2 weeks)",
      "confidence": "High"
    },
    {
      "action": "Review monitoring cardinality",
      "potential_savings": 100,
      "effort": "Low (1-2 days)",
      "confidence": "High"
    },
    {
      "action": "Consider caching layer for read-heavy queries",
      "potential_savings": 150,
      "effort": "Medium (1 week)",
      "confidence": "Medium"
    },
    {
      "action": "Scale traffic analysis — is 110k DAU sustainable?",
      "potential_savings": 300,
      "effort": "Low (planning only)",
      "confidence": "Medium"
    }
  ],
  "escalation_actions": {
    "if_over_10_percent": "Run `/architect:optimize-costs` to identify quick wins",
    "if_trend_continues": "Trigger roadmap planning discussion (may need rearchitecture)",
    "if_exceeded_budget": "Notify finance and product teams; discuss scope/timeline changes"
  }
}