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From cto-team
Estimates infrastructure, development effort, and TCO for technical projects. Use for budgeting, build vs buy decisions, and architecture cost projections.
How this skill is triggered — by the user, by Claude, or both
Slash command
/cto-team:cost-estimatorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Provides frameworks for estimating infrastructure costs, development effort, and total cost of ownership (TCO) for technical projects.
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 │
│ │
└─────────────────────────────────────────────────────────────────┘
| 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 |
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
Build vs Buy Decision Matrix:
LOW Differentiation HIGH Differentiation
┌────────────────────┬────────────────────┐
HIGH Volume/ │ │ │
Usage │ Consider │ BUILD │
│ Build │ (competitive │
│ (cost savings) │ advantage) │
├────────────────────┼────────────────────┤
LOW Volume/ │ │ │
Usage │ BUY │ BUY │
│ (no question) │ (then consider │
│ │ build if scales) │
└────────────────────┴────────────────────┘
## Option A: Build Custom Solution
### Initial Development
- Engineering time: X months × $Y/month = $Z
- Infrastructure setup: $A
### Ongoing Costs (Annual)
- Infrastructure: $B
- Maintenance (20% of dev time): $C
- On-call/support: $D
### 3-Year TCO
Year 1: $Z + $A + $B + $C + $D
Year 2: $B + $C + $D
Year 3: $B + $C + $D
Total: $XXX
---
## Option B: Buy SaaS Solution
### Initial Costs
- Implementation/integration: $X
- Training: $Y
### Ongoing Costs (Annual)
- License fees: $Z/year
- Per-user costs: $A × users
- API costs: $B
### 3-Year TCO
Year 1: $X + $Y + $Z + $A + $B
Year 2: $Z + $A + $B
Year 3: $Z + $A + $B
Total: $XXX
| Capability | Build When | Buy When |
|---|---|---|
| Authentication | Unique security requirements | Standard OAuth/OIDC works |
| Payments | Core business differentiator | Standard e-commerce |
| Search | Domain-specific relevance | Generic search needs |
| Analytics | Proprietary insights needed | Standard dashboards work |
| High volume, custom delivery | Standard transactional | |
| ML/AI | Proprietary models needed | Pre-trained models work |
| Scale | Users | Monthly Infra | Notes |
|---|---|---|---|
| Startup | 0-1K | $200-500 | Single server, managed DB |
| Growth | 1K-10K | $500-2,000 | Load balancer, caching |
| Scale | 10K-100K | $2,000-10,000 | Horizontal scaling |
| Enterprise | 100K-1M | $10,000-50,000 | Multi-region, HA |
| Large | 1M+ | $50,000+ | Global, custom CDN |
| Application Type | Cost/User/Month | Notes |
|---|---|---|
| Simple web app | $0.05-0.20 | Static + API |
| Data-intensive | $0.20-0.50 | Analytics, storage |
| Real-time | $0.50-2.00 | WebSockets, streaming |
| ML-powered | $1.00-5.00 | Inference costs |
| Video/media | $2.00-10.00 | Transcoding, CDN |
## Monthly Infrastructure Cost by GMV
$0-100K GMV/month:
- Basic infrastructure: $500
- Payment processing (2.9%): ~$2,000
- Total: ~$2,500
$100K-1M GMV/month:
- Scaled infrastructure: $2,000
- Payment processing: ~$20,000
- Fraud protection: $500
- Total: ~$22,500
$1M-10M GMV/month:
- HA infrastructure: $10,000
- Payment processing: ~$200,000
- Fraud/security: $5,000
- CDN/performance: $3,000
- Total: ~$218,000
Infrastructure:
Development:
Operations:
Third-Party Services:
| Strategy | Savings | Effort |
|---|---|---|
| Reserved instances | 30-60% | Low |
| Right-sizing instances | 20-40% | Medium |
| Spot instances (non-critical) | 60-90% | Medium |
| Storage tiering | 50-80% | Low |
| CDN caching | 30-50% bandwidth | Low |
| Optimization | Impact | Complexity |
|---|---|---|
| Caching (Redis) | 50-80% DB load reduction | Medium |
| Queue-based processing | Smooth traffic spikes | Medium |
| Auto-scaling | Pay for what you use | Medium |
| Serverless (appropriate use) | Variable → zero when idle | High |
| Multi-region read replicas | Reduce cross-region costs | High |
# Project: [Name]
# Duration: [X months]
## Development Costs
| Phase | Duration | Team Size | Cost |
|-------|----------|-----------|------|
| Discovery/Design | 2 weeks | 2 | $X |
| MVP Development | 8 weeks | 4 | $X |
| Testing/QA | 2 weeks | 3 | $X |
| Deployment | 1 week | 2 | $X |
| **Total Development** | | | **$X** |
## Infrastructure Costs (First Year)
| Component | Monthly | Annual |
|-----------|---------|--------|
| Compute | $X | $X |
| Database | $X | $X |
| Storage | $X | $X |
| Network | $X | $X |
| Third-party APIs | $X | $X |
| Monitoring/Tools | $X | $X |
| **Total Infrastructure** | **$X** | **$X** |
## Ongoing Costs (Annual)
| Category | Cost |
|----------|------|
| Infrastructure | $X |
| Maintenance (20% of dev) | $X |
| Support/On-call | $X |
| Tool licenses | $X |
| **Total Annual** | **$X** |
## Summary
| Metric | Value |
|--------|-------|
| Total First Year | $X |
| Annual Run Rate | $X |
| 3-Year TCO | $X |
| Cost per User (at scale) | $X |
## Quick Infrastructure Estimate
Inputs:
- Expected users: [X]
- Requests per user/day: [Y]
- Data storage per user: [Z GB]
- Growth rate: [W%/month]
Calculations:
- Daily requests: X × Y
- Monthly requests: Daily × 30
- Required compute: (Monthly requests / 100K) × $50
- Storage: X × Z × $0.10
- Database: (X / 10K) × $200
- Estimated monthly: Compute + Storage + Database × 1.3
12-month projection with growth:
Sum of (Monthly × (1 + W%)^month) for months 1-12
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