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)
| 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 |
GPU Instances
| 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 |
Savings Options
| 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 |
Database Pricing
Managed Database (AWS RDS PostgreSQL)
| 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)
Redis/ElastiCache
| 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 |
Storage Pricing
| 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 |
Network Costs (Often Overlooked!)
| 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 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
| 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+ |
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
| 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 |
| Email |
High volume, custom delivery |
Standard transactional |
| ML/AI |
Proprietary models needed |
Pre-trained models work |
Cost Projection by Scale
SaaS Application Cost Model
| 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 |
Cost Per User Benchmarks
| 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 |
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:
Development:
Operations:
Third-Party Services:
Cost Optimization Strategies
Quick Wins
| 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 |
Architecture Optimizations
| 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 |
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