Two Actions to Handle Sudden Traffic Spikes: Predictive Scaling and HTTP/2
A company is deploying a web application that uses an Application Load Balancer and an Auto Scaling group of EC2 instances. The application must be able to handle sudden spikes in traffic. Which TWO actions should the Solutions Architect take to improve scalability and reduce latency? (Choose two.)
Quick Answer
The correct actions are enabling HTTP/2 on the Application Load Balancer and implementing a predictive scaling policy. HTTP/2 reduces latency through multiplexing, allowing multiple requests to be sent over a single TCP connection, which dramatically improves page load times during traffic spikes by eliminating head-of-line blocking. Predictive scaling, part of AWS Auto Scaling, uses machine learning to analyze historical traffic patterns and proactively add capacity before a spike hits, directly improving scalability without waiting for reactive alarms. On the SAP-C02 exam, this question tests your ability to distinguish between horizontal scaling strategies and common traps like increasing cooldown delays, which actually hinder rapid scaling, or choosing vertical scaling with larger instances, which is not elastic. A key memory tip: think of HTTP/2 as “multiplexing for speed” and predictive scaling as “forecasting for capacity”—together they handle both the network and compute layers of a sudden surge.
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
✓
Enable HTTP/2 on the Application Load Balancer.
Options A and D are correct. Option A: Enabling HTTP/2 on the ALB reduces latency through multiplexing and connection reuse. Option D: Using a predictive scaling policy helps prepare for traffic spikes by scaling based on forecasted demand. Option B is incorrect because increasing the cooldown period delays scaling response. Option C is incorrect because using larger instances is vertical scaling, which does not improve horizontal scalability and may increase cost. Option E is incorrect because increasing the health check interval delays detection of unhealthy instances.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable HTTP/2 on the Application Load Balancer.
Why this is correct
HTTP/2 allows multiplexing, reducing latency and improving throughput.
- ✗
Increase the default cooldown period for the Auto Scaling group.
Why it's wrong here
Longer cooldown delays scaling activities, making the application less responsive to spikes.
- ✗
Use larger EC2 instance types for the Auto Scaling group.
Why it's wrong here
Larger instances provide vertical scaling but do not improve horizontal scalability; they may also increase cost.
- ✓
Configure the Auto Scaling group to use a predictive scaling policy.
Why this is correct
Predictive scaling uses historical data to proactively scale, handling spikes better.
- ✗
Increase the health check interval on the Application Load Balancer.
Why it's wrong here
Increasing the interval slows down detection of unhealthy instances, potentially causing routing to failed instances.
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Variation 1. A company is running a 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 that cause increased latency. The company wants to implement a solution to automatically adjust capacity in anticipation of traffic changes. What should a solutions architect do?
medium- A.Configure a simple scaling policy based on CPU utilization.
- B.Configure a scheduled scaling policy to add instances during known peak hours.
- C.Configure a target tracking scaling policy based on average CPU utilization.
- ✓ D.Configure a predictive scaling policy using historical traffic patterns.
Why D: Predictive scaling uses historical traffic patterns to forecast future demand and proactively adjust capacity before traffic spikes occur, which directly addresses the requirement to anticipate changes. This approach reduces latency by ensuring sufficient resources are available ahead of time, unlike reactive policies that only respond after utilization increases.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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