Capacity Planning Calculator
Size your infrastructure correctly from day one. Input your traffic patterns and workload characteristics to get instant recommendations for instance types, node counts, and cost estimates.
🎯Why Capacity Planning Matters
Under-provisioned systems fail under load. Over-provisioned systems waste money. This interactive playground helps you find the right balance by modeling your workload characteristics and recommending infrastructure that meets your performance and availability targets.
Interactive Learning
Adjust sliders and see immediate impact on infrastructure recommendations
Real Metrics
Based on actual AWS instance types and pricing models
Cost Awareness
Understand the financial impact of your architecture decisions
How to Use This Playground
Define your workload
Enter expected transaction rates, message sizes, and concurrent user counts
Account for peaks
Set your peak traffic multiplier to handle burst scenarios
Set availability targets
Choose your SLA (99%, 99.9%, or 99.99%)
Review results
Get instant recommendations for instance types, node counts, latency estimates, and annual costs
Iterate and learn
Adjust inputs to explore different scenarios and trade-offs
Workload Parameters
Medium messages (API responses)
Sustained throughput under normal conditions
Active connections at any given time
Peak TPS: 2,000
Downtime: ~8.8 hours/year
Read: 70% / Write: 30%
Infrastructure Recommendations
Performance Estimates
Cost Estimate
💡Recommendations
- ✓For 99.9% availability, deploy across at least 2 availability zones
Capacity Planning Best Practices
✓Do
- •Plan for 2-3x peak traffic capacity
- •Include N+1 redundancy for high availability
- •Monitor actual vs. predicted performance
- •Use reserved instances for predictable workloads
- •Implement auto-scaling for burst traffic
- •Test failover and degradation scenarios
✗Don't
- •Run production at >70% CPU utilization
- •Ignore network bandwidth requirements
- •Assume linear scaling without testing
- •Skip load testing before launch
- •Forget to account for data growth over time
- •Rely solely on vertical scaling
💡Pro Tip: The 70% Rule
Keep your steady-state utilization below 70% of capacity. This headroom provides buffer for traffic spikes, maintenance operations, and failover scenarios. Running consistently above 70% leaves no margin for error and increases the risk of cascading failures.