antipattern-detector
Detect common technical and organizational anti-patterns in proposals, architectures, and plans. Use when strategic-cto-mentor…
Infrastructure and development cost estimation for technical projects. Use when planning budgets, evaluating build vs buy decisions, or projecting TCO for architecture choices.
$ npx -y skills add alirezarezvani/claude-cto-team --skill cost-estimator --agent claude-codeHow it fires
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Infrastructure and development cost estimation for technical projects. Use when planning budgets, evaluating build vs buy decisions, or projecting TCO for architecture choices.
name: cost-estimator description: Infrastructure and development cost estimation for technical projects. Use when planning budgets, evaluating build vs buy decisions, or projecting TCO for architecture choices.
Provides frameworks for estimating infrastructure costs, development effort, and total cost of ownership (TCO) for technical projects.
TCO = Infrastructure + Development + Operations + Opportunity Cost ┌─────────────────────────────────────────────────────────────────┐ │ TOTAL COST OF OWNERSHIP │ ├─────────────────────────────────────────────────────────────────┤ │ │ │ Infrastructure Development Operations Opportunity │ │ ──────────────── ──────────── ────────── ──────────── │ │ • Compute • Engineering • Support • What else │ │ • Storage • QA • Monitoring • could team │ │ • Network • DevOps • On-call • be building? │ │ • Third-party • Management • Training │ │ APIs/SaaS • Contractors • Incidents │ │ │ └─────────────────────────────────────────────────────────────────┘
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| Instance | vCPU | RAM | Monthly Cost | Best For | |----------|------|-----|--------------|----------| | t3.micro | 2 | 1GB | $8 | Dev/test | | t3.medium | 2 | 4GB | $30 | Small apps | | t3.large | 2 | 8GB | $60 | Light production | | m6i.large | 2 | 8GB | $70 | General production | | m6i.xlarge | 4 | 16GB | $140 | Medium workloads | | m6i.2xlarge | 8 | 32GB | $280 | Heavy workloads | | c6i.2xlarge | 8 | 16GB | $250 | CPU-intensive | | r6i.2xlarge | 8 | 64GB | $370 | Memory-intensive |
| Instance | GPU | VRAM | Monthly Cost | Best For | |----------|-----|------|--------------|----------| | g4dn.xlarge | T4 | 16GB | $380 | Inference | | g5.xlarge | A10G | 24GB | $730 | ML training/inference | | p4d.24xlarge | 8x A100 | 320GB | $23,000 | Large model training |
| Plan | Savings | Commitment | |------|---------|------------| | On-Demand | 0% | None | | Reserved (1yr) | 30-40% | 1 year | | Reserved (3yr) | 50-60% | 3 years | | Spot Instances | 60-90% | Can be interrupted |
| Instance | vCPU | RAM | Monthly Cost | Connections | |----------|------|-----|--------------|-------------| | db.t3.micro | 2 | 1GB | $15 | 50 | | db.t3.medium | 2 | 4GB | $50 | 100 | | db.m6g.large | 2 | 8GB | $120 | 200 | | db.m6g.xlarge | 4 | 16GB | $240 | 400 | | db.r6g.xlarge | 4 | 32GB | $350 | 500 | | db.r6g.2xlarge | 8 | 64GB | $700 | 1000 |
**Add for storage**: $0.115/GB/month (gp3) **Add for IOPS**: $0.02/IOPS/month (over 3000 baseline)
| Node Type | RAM | Monthly Cost | |-----------|-----|--------------| | cache.t3.micro | 0.5GB | $12 | | cache.t3.medium | 3GB | $50 | | cache.m6g.large | 6.4GB | $100 | | cache.r6g.large | 13GB | $175 |
| Service | Cost | Use Case | |---------|------|----------| | S3 Standard | $0.023/GB | Frequently accessed | | S3 Infrequent | $0.0125/GB | Backups, archives | | S3 Glacier | $0.004/GB | Long-term archive | | EBS gp3 | $0.08/GB | Block storage | | EBS io2 | $0.125/GB + IOPS | High performance |
| Traffic Type | Cost | |--------------|------| | Data IN | Free | | Data OUT (first 10TB) | $0.09/GB | | Data OUT (next 40TB) | $0.085/GB | | Inter-AZ transfer | $0.01/GB each way | | Inter-region transfer | $0.02/GB | | CloudFront to internet | $0.085/GB |
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Development Cost = (Hours × Hourly Rate) × Complexity Factor × Risk Buffer Hourly Rate (Fully Loaded): - Junior Engineer: $75-100/hr - Mid-level Engineer: $100-150/hr - Senior Engineer: $150-200/hr - Staff/Principal: $200-300/hr Complexity Factors: - Greenfield, known tech: 1.0x - Existing codebase, known tech: 1.2x - New technology for team: 1.5x - Complex integrations: 1.3x - Regulatory/compliance: 1.4x Risk Buffer: - Well-defined requirements: 1.2x - Ambiguous requirements: 1.5x - Experimental/R&D: 2.0x
| Size | Story Points | Hours | Cost (Mid-level) | |------|-------------|-------|------------------| | XS | 1 | 2-4 | $200-400 | | S | 2 | 4-8 | $400-800 | | M | 3 | 8-16 | $800-1,600 | | L | 5 | 16-32 | $1,600-3,200 | | XL | 8 | 32-64 | $3,200-6,400 | | XXL | 13+ | 64+ | $6,400+ |
## Monthly Team Cost Engineering Team: - 2 Senior Engineers × $15,000 = $30,000 - 3 Mid-level Engineers × $10,000 = $30,000 - 1 Engineering Manager × $18,000 = $18,000 Overhead (benefits, tools, etc.): 30% Monthly Burn: ($78,000) × 1.3 = $101,400 Annual Team Cost: ~$1.2M
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Build vs Buy Decision Matrix:
LOW Differentiation HIGH Differentiation
┌────────────────────┬────────────────────┐
HIGH Volume/ │ │ │
Usage │ Consider │ BUILD │
│ Build │ (competitive │
│ (cost savings) │ advantage) │
├────────────────────┼────────────────────┤
LOW Volume/ │ │ │
Usage │ BUYYour personal CTO Team for Claude Code - Custom AI subagents that provide strategic technical leadership, system architecture design, and brutally honest feedback on your technical decisions.
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