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cost-estimator

Infrastructure and development cost estimation for technical projects. Use when planning budgets, evaluating build vs buy decisions, or projecting TCO for architecture choices.

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Cost Estimator

Provides frameworks for estimating infrastructure costs, development effort, and total cost of ownership (TCO) for technical projects.

When to Use

  • Planning infrastructure budgets
  • Evaluating build vs. buy decisions
  • Projecting costs at different scale points
  • Comparing technology options by cost
  • Creating business cases for technical investments

Cost Categories

Total Cost of Ownership (TCO)

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                    │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘

Infrastructure Cost Reference

Cloud Compute Pricing (2024-2025)

AWS EC2 On-Demand (US regions)

InstancevCPURAMMonthly CostBest For
t3.micro21GB$8Dev/test
t3.medium24GB$30Small apps
t3.large28GB$60Light production
m6i.large28GB$70General production
m6i.xlarge416GB$140Medium workloads
m6i.2xlarge832GB$280Heavy workloads
c6i.2xlarge816GB$250CPU-intensive
r6i.2xlarge864GB$370Memory-intensive

GPU Instances

InstanceGPUVRAMMonthly CostBest For
g4dn.xlargeT416GB$380Inference
g5.xlargeA10G24GB$730ML training/inference
p4d.24xlarge8x A100320GB$23,000Large model training

Savings Options

PlanSavingsCommitment
On-Demand0%None
Reserved (1yr)30-40%1 year
Reserved (3yr)50-60%3 years
Spot Instances60-90%Can be interrupted

Database Pricing

Managed Database (AWS RDS PostgreSQL)

InstancevCPURAMMonthly CostConnections
db.t3.micro21GB$1550
db.t3.medium24GB$50100
db.m6g.large28GB$120200
db.m6g.xlarge416GB$240400
db.r6g.xlarge432GB$350500
db.r6g.2xlarge864GB$7001000

Add for storage: $0.115/GB/month (gp3) Add for IOPS: $0.02/IOPS/month (over 3000 baseline)

Redis/ElastiCache

Node TypeRAMMonthly Cost
cache.t3.micro0.5GB$12
cache.t3.medium3GB$50
cache.m6g.large6.4GB$100
cache.r6g.large13GB$175

Storage Pricing

ServiceCostUse Case
S3 Standard$0.023/GBFrequently accessed
S3 Infrequent$0.0125/GBBackups, archives
S3 Glacier$0.004/GBLong-term archive
EBS gp3$0.08/GBBlock storage
EBS io2$0.125/GB + IOPSHigh performance

Network Costs (Often Overlooked!)

Traffic TypeCost
Data INFree
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 Estimation

Engineering Cost Framework

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

Story Point to Cost Mapping

SizeStory PointsHoursCost (Mid-level)
XS12-4$200-400
S24-8$400-800
M38-16$800-1,600
L516-32$1,600-3,200
XL832-64$3,200-6,400
XXL13+64+$6,400+

Team Cost Calculator

## 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 Analysis

Decision Framework

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) │
                   └────────────────────┴────────────────────┘

TCO Comparison Template

## 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

Common Build vs Buy Scenarios

CapabilityBuild WhenBuy When
AuthenticationUnique security requirementsStandard OAuth/OIDC works
PaymentsCore business differentiatorStandard e-commerce
SearchDomain-specific relevanceGeneric search needs
AnalyticsProprietary insights neededStandard dashboards work
EmailHigh volume, custom deliveryStandard transactional
ML/AIProprietary models neededPre-trained models work

Cost Projection by Scale

SaaS Application Cost Model

ScaleUsersMonthly InfraNotes
Startup0-1K$200-500Single server, managed DB
Growth1K-10K$500-2,000Load balancer, caching
Scale10K-100K$2,000-10,000Horizontal scaling
Enterprise100K-1M$10,000-50,000Multi-region, HA
Large1M+$50,000+Global, custom CDN

Cost Per User Benchmarks

Application TypeCost/User/MonthNotes
Simple web app$0.05-0.20Static + API
Data-intensive$0.20-0.50Analytics, storage
Real-time$0.50-2.00WebSockets, streaming
ML-powered$1.00-5.00Inference costs
Video/media$2.00-10.00Transcoding, CDN

E-commerce Cost Model

## 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

Hidden Cost Checklist

Often Missed in Estimates

Infrastructure:

  • Data transfer costs (egress)
  • Backup storage
  • Log storage (CloudWatch: $0.50/GB)
  • SSL certificates
  • DNS queries
  • Load balancer hours

Development:

  • Code reviews (add 20-30% to dev time)
  • Documentation
  • Testing infrastructure
  • CI/CD pipeline (GitHub Actions: $0.008/min)
  • Staging environments

Operations:

  • Monitoring tools (Datadog: ~$15/host/month)
  • Error tracking (Sentry: $26+/month)
  • Log management
  • On-call compensation
  • Incident response time

Third-Party Services:

  • Email (SendGrid: $0.00025-0.001/email)
  • SMS (Twilio: $0.0075/message)
  • Video (encoding, streaming)
  • Maps/geocoding (Google: $7/1K requests)

Cost Optimization Strategies

Quick Wins

StrategySavingsEffort
Reserved instances30-60%Low
Right-sizing instances20-40%Medium
Spot instances (non-critical)60-90%Medium
Storage tiering50-80%Low
CDN caching30-50% bandwidthLow

Architecture Optimizations

OptimizationImpactComplexity
Caching (Redis)50-80% DB load reductionMedium
Queue-based processingSmooth traffic spikesMedium
Auto-scalingPay for what you useMedium
Serverless (appropriate use)Variable → zero when idleHigh
Multi-region read replicasReduce cross-region costsHigh

Cost Estimation Templates

Project Budget Template

# 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 Estimate Calculator

## 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

References

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