- A
Use AWS DMS to continuously replicate metrics to a central RDS instance.
Why wrong: DMS is not for monitoring.
- B
Consolidate all tenants into a single RDS MySQL instance and use separate schemas.
Why wrong: Loss of tenant isolation.
- C
Run an AWS Lambda function that queries each database's performance_schema every minute and stores results in S3.
Why wrong: Lambda queries add overhead and cost.
- D
Use Amazon CloudWatch Agent to collect custom metrics from each Aurora instance and aggregate in CloudWatch.
CloudWatch Agent collects metrics with low overhead.
Question 1,279 of 1,730
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 uses Amazon Aurora MySQL for a SaaS application. Each tenant has a separate database. The company wants to implement a centralized monitoring solution that collects performance metrics from all tenant databases. The solution should be cost-effective and require minimal overhead. Which approach should be used?
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 Amazon CloudWatch Agent to collect custom metrics from each Aurora instance and aggregate in CloudWatch.
Amazon CloudWatch Agent can be installed on each Aurora instance to collect custom performance metrics (e.g., from performance_schema) and publish them as CloudWatch custom metrics. This approach is cost-effective because it uses CloudWatch’s pay-per-metric model and eliminates the need for a separate aggregation database or continuous data movement. It also requires minimal overhead as the agent handles collection and aggregation natively, with no additional infrastructure to manage.
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.
- ✗
Use AWS DMS to continuously replicate metrics to a central RDS instance.
Why it's wrong here
DMS is not for monitoring.
- ✗
Consolidate all tenants into a single RDS MySQL instance and use separate schemas.
Why it's wrong here
Loss of tenant isolation.
- ✗
Run an AWS Lambda function that queries each database's performance_schema every minute and stores results in S3.
Why it's wrong here
Lambda queries add overhead and cost.
- ✓
Use Amazon CloudWatch Agent to collect custom metrics from each Aurora instance and aggregate in CloudWatch.
Why this is correct
CloudWatch Agent collects metrics with low overhead.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume a centralized database or Lambda-based polling is required for aggregation, but the CloudWatch Agent’s native custom metrics capability provides a simpler, serverless, and cost-effective solution that aligns with the ‘minimal overhead’ requirement.
Detailed technical explanation
How to think about this question
The CloudWatch Agent uses the ‘procstat’ plugin on Linux or the ‘Performance Monitor’ on Windows to collect OS-level metrics, and it can be configured with a custom JSON configuration to query MySQL’s performance_schema tables (e.g., ‘events_statements_summary_by_digest’) via the ‘mysql’ plugin. Under the hood, the agent publishes metrics to CloudWatch using the PutMetricData API, which supports up to 150 KB per payload, allowing efficient batching of multiple metrics from multiple tenants. In a real-world scenario, you can set up a CloudWatch dashboard or Contributor Insights to visualize and alert on per-tenant performance without any central database overhead.
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 DBS-C01 question test?
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Amazon CloudWatch Agent to collect custom metrics from each Aurora instance and aggregate in CloudWatch. — Amazon CloudWatch Agent can be installed on each Aurora instance to collect custom performance metrics (e.g., from performance_schema) and publish them as CloudWatch custom metrics. This approach is cost-effective because it uses CloudWatch’s pay-per-metric model and eliminates the need for a separate aggregation database or continuous data movement. It also requires minimal overhead as the agent handles collection and aggregation natively, with no additional infrastructure to manage.
What should I do if I get this DBS-C01 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
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Last reviewed: Jul 4, 2026
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