The answer is to use a scheduled scaling policy with Spot Instances in the Auto Scaling group for the monthly batch job. This combination directly addresses the need to cost optimize batch job with Auto Scaling and Spot Instances by proactively increasing capacity only during the two-hour batch window, avoiding the cost of idle resources, while Spot Instances provide up to 90% savings compared to On-Demand. On the AWS Certified Solutions Architect Professional SAP-C02 exam, this scenario tests your understanding of predictive scaling versus dynamic scaling, with a common trap being to recommend a simple dynamic policy that would react too slowly for a predictable, short-duration workload. Remember that scheduled scaling is ideal for known, periodic demand spikes, and Spot Instances are perfect for fault-tolerant, interruptible batch processing. A useful memory tip is “Schedule for certainty, Spot for savings”—when you know exactly when capacity is needed, schedule it; when the workload can handle interruptions, use Spot.
SAP-C02 Continuous Improvement for Existing Solutions Practice Question
This SAP-C02 practice question tests your understanding of continuous improvement for existing solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is running a critical application on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer. The application needs to process a large batch job that runs once per month and takes 2 hours. The company wants to optimize costs while ensuring the batch job has sufficient capacity. Which THREE steps should a solutions architect recommend?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a scheduled scaling policy that increases the desired capacity before the batch job starts.
Option A is correct because a scheduled scaling policy allows you to increase the desired capacity of the Auto Scaling group before the batch job starts, ensuring sufficient resources are available exactly when needed. This proactive approach avoids the latency of dynamic scaling and optimizes cost by not maintaining extra capacity outside the batch window.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Create a scheduled scaling policy that increases the desired capacity before the batch job starts.
Why this is correct
Scheduled scaling ensures capacity is available when needed.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use a launch template with multiple instance types to increase the chances of obtaining Spot capacity.
Read the scenario before looking for a memorised answer.
✗
Use On-Demand Instances only for the batch job to ensure availability.
Why it's wrong here
On-Demand is costlier than Spot for this workload.
✓
Use Spot Instances in the Auto Scaling group for the batch job.
Why this is correct
Spot Instances are cost-effective for fault-tolerant batch workloads.
Related concept
Read the scenario before looking for a memorised answer.
✗
Purchase Reserved Instances for the batch job capacity.
Why it's wrong here
Reserved Instances require a 1- or 3-year commitment, not suitable for short monthly jobs.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may assume On-Demand or Reserved Instances are required for reliability, but the question emphasizes cost optimization and the batch job's fault tolerance, making Spot Instances with a scheduled scaling policy the correct approach.
Detailed technical explanation
How to think about this question
Scheduled scaling policies in Auto Scaling use cron-like expressions to define recurring actions, adjusting desired, min, or max capacity at specified times. For batch jobs, combining scheduled scaling with a mixed instances policy that includes Spot Instances (via a launch template with multiple instance types) increases the likelihood of obtaining Spot capacity from different instance pools, reducing the risk of interruption and further lowering costs.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Continuous Improvement for Existing Solutions — This question tests Continuous Improvement for Existing Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a scheduled scaling policy that increases the desired capacity before the batch job starts. — Option A is correct because a scheduled scaling policy allows you to increase the desired capacity of the Auto Scaling group before the batch job starts, ensuring sufficient resources are available exactly when needed. This proactive approach avoids the latency of dynamic scaling and optimizes cost by not maintaining extra capacity outside the batch window.
What should I do if I get this SAP-C02 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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