Combining Proactive and Reactive Scaling Strategies for Traffic Spikes
A company runs a critical web application on EC2 instances behind an Application Load Balancer (ALB) with Auto Scaling. During a recent traffic spike, the application became unavailable for 10 minutes. Analysis shows that the ALB's healthy host count dropped to zero because the instances failed health checks due to high CPU load. What is the MOST effective design change to improve resilience during future traffic spikes?
Quick Answer
The answer is to use predictive scaling with a scheduled scaling policy for known peak times. This is correct because predictive scaling leverages historical traffic data to forecast demand and proactively add capacity before a spike hits, preventing CPU load from reaching the critical threshold that causes health check failures. On the AWS Certified DevOps Engineer Professional DOP-C02 exam, this scenario tests your understanding of combining proactive and reactive scaling for traffic spikes, where predictive scaling handles anticipated surges and dynamic scaling covers unexpected bursts. A common trap is choosing only scheduled scaling, which fails for unplanned spikes, or only dynamic scaling, which reacts too slowly when instances are already overwhelmed. Remember the memory tip: “Predict for the known, react for the unknown”—proactive capacity prevents the crash, while reactive scaling catches what the forecast misses.
⚠ Common exam trap
Many candidates confuse reactive scaling (step/target tracking) with proactive scaling (predictive/scheduled), assuming any CPU-based policy will suffice, but the question explicitly states the spike caused a drop to zero healthy hosts—meaning reactive scaling was too slow to prevent the outage.
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 predictive scaling with a scheduled scaling policy for known peak times.
Predictive scaling uses historical traffic data to forecast future demand and proactively adjust capacity before a spike occurs. This prevents the CPU from reaching critical levels that cause health check failures, ensuring the ALB always has healthy hosts. Scheduled scaling alone would not adapt to unexpected spikes, but predictive scaling combined with dynamic scaling provides both proactive and reactive resilience.
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 predictive scaling with a scheduled scaling policy for known peak times.
Why this is correct
Predictive scaling anticipates demand and scales out in advance, preventing overload.
- ✗
Increase the instance size to handle higher load.
Why it's wrong here
Larger instances still have a fixed capacity and may still become overwhelmed; also cost-inefficient.
- ✗
Configure step scaling policies based on CPU utilization.
Why it's wrong here
Step scaling reacts after the threshold is breached, which may be too slow to prevent downtime.
- ✗
Set a higher CPU threshold for health checks.
Why it's wrong here
Raising the threshold only masks the problem; instances may still become unresponsive.
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Same concept, more angles
1 more way this is tested on DOP-C02
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company runs a critical web application on AWS using an Application Load Balancer (ALB) in front of an Auto Scaling group of EC2 instances. The application experiences periodic traffic spikes. To handle these spikes, the company wants to use a combination of proactive scaling based on a predictable schedule and reactive scaling based on CPU utilization. What is the MOST resilient scaling strategy?
medium- ✓ A.Use a scheduled scaling policy for the predictable spikes and a step scaling policy for CPU utilization.
- B.Use predictive scaling based on historical traffic patterns.
- C.Use manual scaling by increasing the desired capacity before expected spikes.
- D.Use a target tracking scaling policy based on average CPU utilization.
Why A: It combines scheduled scaling for predictable traffic spikes with step scaling for reactive adjustments based on CPU utilization, providing both proactive and reactive resilience. Scheduled scaling adjusts capacity in advance of known events, while step scaling allows for larger, more aggressive adjustments when CPU utilization exceeds thresholds, avoiding the slower, linear response of target tracking. This dual approach ensures the application can handle spikes without over-provisioning or under-provisioning.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DOP-C02 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 DOP-C02 exam.