- A
Aggregate logs into a central S3 bucket and query with Amazon Athena
Athena allows serverless SQL queries on S3 data, cost-effective for historical analysis.
- B
Stream logs to Amazon Elasticsearch Service and use Kibana
Why wrong: Elasticsearch can be costly for large volumes.
- C
Load logs into Amazon Redshift for analysis
Why wrong: Redshift is more expensive and complex for this use case.
- D
Use Amazon CloudWatch Logs Insights across all accounts
Why wrong: CloudWatch Logs has limited retention and is not ideal for cross-account analysis.
SCS-C02 Threat Detection and Incident Response Practice Question
This SCS-C02 practice question tests your understanding of threat detection and incident response. 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 security team needs to analyze historical CloudTrail logs across multiple AWS accounts to detect patterns of suspicious activity. Which solution provides the MOST cost-effective and scalable analysis?
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
Aggregate logs into a central S3 bucket and query with Amazon Athena
Aggregating CloudTrail logs into a central S3 bucket and querying with Amazon Athena is the most cost-effective and scalable solution because Athena uses a serverless, pay-per-query model with no infrastructure to manage, and it can directly analyze large volumes of structured log data stored in S3 using standard SQL. This approach avoids the cost of provisioning and maintaining dedicated clusters (as with Redshift or Elasticsearch) and avoids the per-GB ingestion and storage fees of CloudWatch Logs Insights, making it ideal for historical analysis across multiple accounts.
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.
- ✓
Aggregate logs into a central S3 bucket and query with Amazon Athena
Why this is correct
Athena allows serverless SQL queries on S3 data, cost-effective for historical analysis.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Stream logs to Amazon Elasticsearch Service and use Kibana
Why it's wrong here
Elasticsearch can be costly for large volumes.
- ✗
Load logs into Amazon Redshift for analysis
Why it's wrong here
Redshift is more expensive and complex for this use case.
- ✗
Use Amazon CloudWatch Logs Insights across all accounts
Why it's wrong here
CloudWatch Logs has limited retention and is not ideal for cross-account analysis.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose CloudWatch Logs Insights (Option D) because it seems convenient for log analysis, but they overlook its high ingestion costs and limited retention for historical data, whereas Athena's serverless, pay-per-query model is far more cost-effective for large-scale, infrequent queries of archived logs.
Detailed technical explanation
How to think about this question
Athena leverages Presto under the hood to execute SQL queries directly on data in S3, and it supports partitioning (e.g., by account, region, or date) to dramatically reduce scan costs and improve performance. A common best practice is to use AWS CloudTrail's built-in S3 bucket integration with a lifecycle policy to transition older logs to cheaper storage classes (like S3 Glacier) while still allowing Athena to query them via S3 Select or restore operations. In a real-world multi-account scenario, you can use AWS Organizations to centralize CloudTrail trails into a single S3 bucket, then create Athena partitioned tables with Glue Data Catalog for efficient cross-account analysis.
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.
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FAQ
Questions learners often ask
What does this SCS-C02 question test?
Threat Detection and Incident Response — This question tests Threat Detection and Incident Response — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Aggregate logs into a central S3 bucket and query with Amazon Athena — Aggregating CloudTrail logs into a central S3 bucket and querying with Amazon Athena is the most cost-effective and scalable solution because Athena uses a serverless, pay-per-query model with no infrastructure to manage, and it can directly analyze large volumes of structured log data stored in S3 using standard SQL. This approach avoids the cost of provisioning and maintaining dedicated clusters (as with Redshift or Elasticsearch) and avoids the per-GB ingestion and storage fees of CloudWatch Logs Insights, making it ideal for historical analysis across multiple accounts.
What should I do if I get this SCS-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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jun 24, 2026
This SCS-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 SCS-C02 exam.
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