MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company wants to reduce costs for a real-time inference endpoint that experiences predictable traffic spikes during business hours and low traffic at night. Which auto-scaling policy is MOST cost-effective while maintaining performance?
⚠ Common exam trap
A common mix-up: candidates choose reactive scaling options (like step scaling or target tracking) because they seem 'automated,' but they fail to recognize that for predictable, time-based traffic patterns, scheduled scaling is both more cost-effective and more performant than any reactive policy.
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
✓
Scheduled scaling that increases instances before business hours and decreases after
Scheduled scaling directly aligns capacity with the predictable traffic pattern (business hours vs. night), allowing you to proactively add instances before demand increases and remove them afterward. This avoids the cost of over-provisioning during low-traffic periods and the latency of reactive scaling, making it the most cost-effective approach for a known, recurring schedule.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Step scaling based on CPU utilization
Why it's wrong here
Step scaling based on CPU utilisation reacts to server load rather than the predictable schedule of business-hour spikes, so it cannot proactively scale down during low-traffic nights, leaving idle capacity running and incurring unnecessary cost. It is tempting because CPU-based scaling is a standard reactive mechanism for variable workloads, and it would be correct for an endpoint with unpredictable traffic bursts where load itself is the trigger.
- ✗
Manual scaling by the operations team
Why it's wrong here
Manual scaling is not automated and may be error-prone.
- ✓
Scheduled scaling that increases instances before business hours and decreases after
Why this is correct
Scheduled scaling proactively adjusts capacity, minimizing idle instances during low traffic.
- ✗
Target tracking with a custom metric for response time
Why it's wrong here
Target tracking is reactive and may not align with predictable schedules as efficiently as scheduled scaling.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.