CV0-004 Cloud Architecture and Design Practice Question
A company uses an auto-scaling group to handle variable web traffic. The scaling policy is based on CPU utilization. However, during a flash sale, the application experiences a sudden spike in traffic, and the auto-scaling group takes too long to launch new instances. Which design change would most effectively reduce the time to scale out?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use scheduled scaling to pre-warm instances before the sale
Using a predictive scaling policy or scheduled scaling can anticipate traffic spikes and pre-warm instances, reducing launch delay. Alternatively, increasing the cooldown period would slow scaling. Lowering the threshold would cause earlier scaling but not necessarily reduce launch time. Using larger instances is vertical scaling, not addressing launch delay.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use larger instance types to handle more traffic
Why it's wrong here
Vertical scaling doesn't improve scaling speed.
- ✗
Lower the CPU utilization threshold
Why it's wrong here
This triggers scaling earlier but doesn't reduce instance launch time.
- ✗
Increase the cooldown period
Why it's wrong here
Increasing cooldown delays further scaling actions.
- ✓
Use scheduled scaling to pre-warm instances before the sale
Why this is correct
Proactive scaling reduces response time.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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