SRE Capacity Planning & Scaling 2

Question 1

Which metric is most useful for predicting when a database will run out of disk space?

Accepted Answer

Linear regression on historical growth rate

Answer

Linear regression on historical growth trends provides a time-based forecast, allowing teams to predict when capacity will be exhausted.

Question 2

An SRE observes that CPU utilization spikes to 95% every Monday morning for 30 minutes. What is the best scaling strategy?

Accepted Answer

Configure scheduled auto-scaling to add capacity before Monday morning

Answer

Scheduled auto-scaling proactively adds resources before a known predictable load pattern, avoiding over-provisioning at other times.

Question 3

What does 'headroom' refer to in capacity planning?

Accepted Answer

Reserved capacity above current usage to absorb unexpected demand

Answer

Headroom is the buffer of spare capacity maintained above current utilization to handle unexpected traffic bursts without degrading service.

Question 4

A service's p99 latency degrades significantly when CPU utilization exceeds 70%. What should the SRE set as the scaling threshold?

Accepted Answer

70% or below

Answer

Scaling should trigger at or before the 70% threshold to prevent latency degradation, ensuring performance SLOs are maintained.

Question 5

Which load testing approach best simulates realistic production traffic for capacity planning?

Accepted Answer

Replay of recorded production traffic traces

Answer

Replaying recorded production traffic captures real-world request distributions, user patterns, and payload sizes for accurate capacity modeling.

(SRE) Site Reliability Engineering Foundation Certification Practice Test