Capacity Planning & Toil Reduction
Learn capacity planning strategies and toil reduction techniques that keep systems reliable while freeing engineers to work on impactful projects.
45 min•By Priygop Team•Last updated: Feb 2026
Capacity Planning
- Demand Forecasting: Use historical data + growth rates to predict future resource needs — organic growth (5% month-over-month) plus planned launches/events
- Load Testing: Regularly test system capacity — find breaking points before users do. Use tools like k6, Locust, or Gatling for realistic load simulation
- Headroom: Maintain 30-50% capacity headroom — this absorbs traffic spikes, allows for maintenance, and gives time to scale before hitting limits
- Auto-scaling: Configure horizontal auto-scaling based on CPU, memory, or custom metrics — scale up fast (2 min), scale down slowly (10 min) to handle traffic patterns
- Cost Optimization: Right-size instances, use spot/preemptible instances for batch jobs, reserved instances for baseline, and implement cleanup for orphaned resources
- Regional Distribution: Distribute across availability zones and regions — provides both capacity and fault tolerance