AWS Auto Scaling Predictive and Dynamic Strategy

SAA-C03 By islever Editorial Last updated

Design high-performing and elastic compute solutions.

Short answer

B Enable predictive scaling to forecast and scale resources based on historical trends, while configuring dynamic scaling with target tracking to respond to live changes in utilization.

Question

A company runs a three-tier web application in a VPC across multiple Availability Zones. Amazon EC2 instances run in an Auto Scaling group for the application tier. The company needs to make an automated scaling plan that will analyze each resource's daily and weekly historical workload trends. The configuration must scale resources appropriately according to both the forecast and live changes in utilization. Which scaling strategy should a solutions architect recommend to meet these requirements?
  1. Implement dynamic scaling with step scaling based on average CPU utilization from the EC2 instances.
  2. Enable predictive scaling to forecast and scale. Configure dynamic scaling with target tracking Correct Answer
  3. Create an automated scheduled scaling action based on the traffic patterns of the web application.
  4. Set up a simple scaling policy. Increase the cooldown period based on the EC2 instance startup time.

Key Takeaways

The exam tests the distinction between simple dynamic scaling and hybrid approaches; the trap is choosing only predictive or only dynamic when the requirement explicitly asks for both forecast analysis and live utilization response.

This question addresses designing elastic compute solutions by combining predictive scaling for trend-based forecasting with dynamic target tracking for real-time adjustments to meet workload demands.

Common mistake: Candidates often select Option A (Dynamic Step Scaling) because it is a common default, failing to recognize that step scaling does not utilize historical trends or machine learning forecasts as required by the prompt.

Expert Analysis

Why the Answer Is Correct

Option B is the correct strategy because AWS Auto Scaling supports Predictive Scaling which uses machine learning to analyze historical data and forecast future demand, combined with Dynamic Scaling (specifically Target Tracking) which reacts to immediate changes in resource utilization. The question explicitly requires analyzing "daily and weekly historical workload trends" (Predictive) AND responding to "live changes in utilization" (Dynamic). By enabling Predictive Scaling to pre-provision capacity based on forecasts and configuring Dynamic Scaling to handle spikes beyond those forecasts, the architecture meets both requirements simultaneously.

Why the Other Options Are Wrong

Option A (Step Scaling) is purely reactive to current metrics like CPU and does not use historical trend analysis or forecasting. Option C (Scheduled Scaling) relies on predefined time tables rather than analyzing actual workload patterns or reacting to live fluctuations, making it rigid and unable to handle unpredictable traffic spikes. Option D (Simple Scaling) is an older, less effective policy that lacks the granularity of Target Tracking or Step Scaling and does not incorporate any predictive capabilities or trend analysis.

Community Comment Notes

The community consensus strongly favors Option B, with users noting that it uniquely covers both aspects of the requirement. As user BillaRanga noted, configuring dynamic scaling with target tracking alongside predictive scaling allows automatic adjustment based on forecasted demand while responding to live changes. Another user, sandordini, highlighted that Option A only handles dynamic scaling, missing the pattern-based/predictive component entirely.

Official Reference

https://docs.aws.amazon.com/autoscaling/ec2/userguide/predictive-scaling.html

This link opens the official vendor documentation in a new tab.

Exam Strategy

When a question mentions 'historical trends', 'forecast', or 'machine learning' in the context of EC2 scaling, immediately consider Predictive Scaling. If it also mentions 'real-time', 'current metric', or 'live changes', look for an option that combines Predictive with a Dynamic policy (like Target Tracking).

Frequently Asked Questions

Can I use just Predictive Scaling without Dynamic?

Yes, but it won't handle unexpected spikes. The question requires handling 'live changes', so Dynamic is necessary alongside Predictive.

Why not Scheduled Scaling for known traffic patterns?

Scheduled scaling is rigid and time-based. It cannot react to 'live changes' in utilization or adapt to unpredictable variations in daily/weekly trends.

More SAA-C03 FAQ →

Community Votes

B
100%

100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 4 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 4

  1. BillaRanga 👍 4 Answered B
    By configuring dynamic scaling with target tracking, the company can automatically adjust resources based on the forecasted demand while also responding to live changes in utilization
  2. sandordini 👍 3 Answered B
    Not A: Only handles Dynamic scaling, not pattern-based/predictive scaling. B: Both Predictive and dynamic Not C: Manual version of predictive, lacks live circumstances.. Not D: The question doesn't talk about cool down period...
  3. alawada 👍 2
    https://aws.amazon.com/blogs/aws/new-predictive-scaling-for-ec2-powered-by-machine-learning/
  4. Andy_09 👍 4
    Option B

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