Capacity Planning

How This Differs From SLOs

SLOs (Service Level Objectives) define your reliability target. Capacity planning is the separate discipline of making sure you have enough infrastructure — compute, storage, network — to actually hit that target under real and projected load. An SRE needs both, but they answer different questions: "what reliability do we promise?" vs "do we have enough headroom to deliver it?"

The Core Capacity Planning Loop

1.Measure current utilization — CPU, memory, disk I/O, network throughput per service, at peak and average.

2.Forecast demand — using historical growth trends, planned feature launches, and seasonal patterns (e.g. e-commerce Diwali/Black Friday spikes).

3.Determine headroom needed — typically size for peak load + a safety margin (commonly 20–40%, higher for unpredictable traffic).

4.Provision or set autoscaling policy — either pre-provision capacity or configure autoscaling to react within an acceptable time window.

5.Re-measure after changes — capacity planning is continuous, not a one-time exercise.

Load Testing

You can't plan capacity you haven't tested. Common approaches:

•Load testing — simulate expected peak traffic to confirm the system holds up.

•Stress testing — push well beyond expected peak to find the actual breaking point.

•Soak testing — sustained moderate load over hours/days to catch memory leaks and slow degradation.

bash

# Example: simple load test with k6
k6 run --vus 500 --duration 10m load-test.js

Scaling Thresholds

Signal	Typical trigger	Action

|---|---|---|

CPU utilization	> 70% sustained for 5 min	Scale out (add instances)
Memory utilization	> 80% sustained	Scale out or investigate leak
Queue depth	Growing faster than consumption rate	Add consumers / scale workers
P99 latency	Breaching SLO threshold	Immediate scale + investigate

Cost-Aware Headroom

Over-provisioning "just to be safe" is a real cost — capacity planning at senior level is about finding the minimum headroom that reliably meets demand, not maximum headroom. This is where capacity planning and FinOps/cost optimization directly intersect.

Forecasting for Planned Events

Before a known high-traffic event (product launch, sale, marketing campaign), capacity planning becomes proactive: pre-scale ahead of the event, run a dedicated load test at expected peak + margin, and have a rollback/circuit-breaker plan if actual traffic exceeds the forecast.

ℹ️ Relationship to SLOs

An SLO tells you when you're in trouble (error budget burning). Capacity planning is what you do before that happens — provisioning ahead of demand so the error budget never has to be spent on a preventable capacity shortfall.

Capacity Planning — Overview