Architecture Tooling

Infrastructure Capacity 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.

✓Real-time calculations
✓Cost optimization
✓Performance targets

Why Capacity Planning Matters

Under-provisioned systems fail under load. Over-provisioned systems waste money. This calculator helps you find the right balance by modeling your workload characteristics and recommending infrastructure that meets your performance and availability targets.

How to Use This Calculator

  1. Define your workload: Enter expected transaction rates, message sizes, and concurrent user counts
  2. Account for peaks: Set your peak traffic multiplier to handle burst scenarios
  3. Set availability targets: Choose your SLA (99%, 99.9%, or 99.99%)
  4. Review results: Get instant recommendations for instance types, node counts, latency estimates, and annual costs
  5. Iterate: 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

Instance Type
c5.xlarge
Node Count
2
Total CPU Cores
8
Total Memory
16 GB
Network Bandwidth
10 Gbps per instance

Performance Estimates

Throughput19.5 MB/s
Latency Percentiles
p50
4ms
p95
7ms
p99
10ms

Cost Estimate

$288/month
$3,456 per year (on-demand pricing)
💡 Consider reserved instances for ~30-50% savings on predictable workloads

💡Recommendations

  • ✓For 99.9% availability, deploy across at least 2 availability zones

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Related Resources

📊

Observability & Operations

Building Block

Learn how to monitor and operate your infrastructure

Learn the Concepts→
📈

Scalability Patterns

Pattern

Explore patterns for handling load and scale

Learn the Concepts→

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