AWS Certified Solutions Architect Professional SAP-C02 Practice Question
A media analytics company hosts a latency-sensitive REST API in a single AWS Region. The API runs on an Auto Scaling group of EC2 instances behind an Application Load Balancer. Traffic follows a predictable daily pattern that peaks around 9:00 A.M. and tapers off in the evening. The operations team currently uses two scheduled scaling actions to add capacity 1 hour before the expected peak and to scale in after business hours. The API containers require about 10 minutes to initialize. During the last month, unexpected marketing events caused the traffic spike to occur 30-40 minutes earlier than normal on several days, pushing CPU utilization above 90 percent and increasing p95 latency.
The company wants to eliminate manual schedule tuning while ensuring that additional instances are launched before the workload surge begins. Which solution will best improve performance with the least operational overhead?
Replace the scheduled actions with a target tracking scaling policy that keeps ALBRequestCountPerTarget at 1200 requests per minute.
Increase the Auto Scaling group's minimum capacity by 50 percent during business hours to absorb early traffic spikes.
Configure a predictive scaling policy for the Auto Scaling group that uses the predefined ASGCPUUtilization metric, then remove the existing scheduled actions.
Create a step scaling policy that adds one instance when average CPU utilization exceeds 70 percent and another when it exceeds 85 percent.
Predictive scaling analyzes historical load patterns, forecasts the next day's demand, and launches EC2 instances ahead of the predicted increase. Because the traffic spike follows a daily pattern but may begin earlier on some days, a predictive scaling policy that uses the ASGCPUUtilization (or another predefined) metric can start new instances 10-60 minutes before the surge, giving the containers time to initialize and preventing high latency. Target-tracking or step-scaling policies react only after a metric threshold is breached, so the application would still experience degraded performance during instance warm-up. Simply raising the minimum capacity keeps unneeded instances running every day and does not adapt to changes in demand, increasing cost and operational overhead.
Ask Bash
Bash is our AI bot, trained to help you pass your exam. AI Generated Content may display inaccurate information, always double-check anything important.
What is predictive scaling in AWS Auto Scaling?
Open an interactive chat with Bash
How do predefined metrics like ASGCPUUtilization work with predictive scaling?
Open an interactive chat with Bash
Why is predictive scaling better than target tracking or step scaling for this use case?
Open an interactive chat with Bash
AWS Certified Solutions Architect Professional SAP-C02
Continuous Improvement for Existing Solutions
Your Score:
Report Issue
Bash, the Crucial Exams Chat Bot
AI Bot
Loading...
Loading...
Loading...
IT & Cybersecurity Package Join Premium for Full Access