- A
Create a CloudWatch Logs metric filter for each log group to count ERROR entries, and then create a CloudWatch dashboard
Why wrong: Metric filters require one filter per log group and do not aggregate easily across groups.
- B
Use CloudWatch Logs Insights to run a query that counts ERROR entries across all log groups and add the query to a CloudWatch dashboard
Logs Insights can query multiple log groups and be added to a dashboard.
- C
Export logs to Amazon S3 and use Amazon Athena to query and visualize in Amazon QuickSight
Why wrong: This is not real-time due to export delays.
- D
Create a Kinesis Data Firehose delivery stream to stream logs to Amazon OpenSearch Service and build a dashboard in OpenSearch Dashboards
Why wrong: This is more complex and expensive than needed.
DOP-C02 Monitoring and Logging Practice Question
This DOP-C02 practice question tests your understanding of monitoring and logging. 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 CloudWatch Logs to store application logs. A DevOps engineer needs to create a real-time dashboard that displays the count of ERROR-level log entries across all instances. Which approach is the MOST efficient and cost-effective?
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 CloudWatch Logs Insights to run a query that counts ERROR entries across all log groups and add the query to a CloudWatch dashboard
Option B is correct because CloudWatch Logs Insights allows you to run a query across all log groups in real time using a single query, and you can add that query directly to a CloudWatch dashboard. This approach is both efficient (no need to create per-log-group metric filters) and cost-effective (you pay only for the data scanned by the query, not for ongoing metric filter evaluation).
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 CloudWatch Logs metric filter for each log group to count ERROR entries, and then create a CloudWatch dashboard
Why it's wrong here
Metric filters require one filter per log group and do not aggregate easily across groups.
- ✓
Use CloudWatch Logs Insights to run a query that counts ERROR entries across all log groups and add the query to a CloudWatch dashboard
Why this is correct
Logs Insights can query multiple log groups and be added to a dashboard.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Export logs to Amazon S3 and use Amazon Athena to query and visualize in Amazon QuickSight
Why it's wrong here
This is not real-time due to export delays.
- ✗
Create a Kinesis Data Firehose delivery stream to stream logs to Amazon OpenSearch Service and build a dashboard in OpenSearch Dashboards
Why it's wrong here
This is more complex and expensive than needed.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume metric filters (Option A) are the only native way to get counts into a dashboard, overlooking that CloudWatch Logs Insights queries can be embedded directly into dashboards for real-time, cross-log-group analysis without the overhead of per-group filters.
Detailed technical explanation
How to think about this question
CloudWatch Logs Insights queries use a purpose-built query engine that can scan multiple log groups in parallel, returning results in seconds for recent data. The query syntax supports aggregation functions like count() and filtering with fields @message like /ERROR/, and the results can be visualized as a time-series line chart on a dashboard. Under the hood, CloudWatch Logs Insights indexes log data by timestamp and uses a distributed query execution model, so it can handle high-volume log streams without pre-aggregation.
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 DOP-C02 question test?
Monitoring and Logging — This question tests Monitoring and Logging — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use CloudWatch Logs Insights to run a query that counts ERROR entries across all log groups and add the query to a CloudWatch dashboard — Option B is correct because CloudWatch Logs Insights allows you to run a query across all log groups in real time using a single query, and you can add that query directly to a CloudWatch dashboard. This approach is both efficient (no need to create per-log-group metric filters) and cost-effective (you pay only for the data scanned by the query, not for ongoing metric filter evaluation).
What should I do if I get this DOP-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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Last reviewed: Jul 4, 2026
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